When Tina Hannagan joined Fusable (formerly part of Randall Riley) in 2022, she encountered a company with tremendous potential but fragmented by individual product brands. Each sales team member literally wore different branded polo shirts depending on which product they were selling and which tradeshow they were attending. This fragmentation wasn't just cosmetic—it created barriers to delivering complete solutions to customers who often didn't realize the full scope of what the company offered, which meant significant revenue was being left on the table.
Key Transformation Points:
As Tina noted: "We had a customer that came to us and said, I have a lot full of combines. What are they worth? Who might be in the market to buy them? And we have the answers to those questions, but we have them in different products... that process is far from efficient, right? But they're very critical decisions that our clients are trying to make."
Rather than implementing sweeping changes overnight, Hannagan took a methodical approach to transforming Fusable's revenue organization. She recognized the value of the company's tenured employees while systematically introducing new capabilities, compensation models, and customer segmentation approaches.
Change Management Highlights:
"Transformation isn't easy and it's not easy when you're going at it really fast," Hannagan explained. "For me personally, I have to always take that step back and recognize that not everyone is on the same page or thinks the same way about change and transformation that I do."
One of the most innovative aspects of Fusable's transformation has been their approach to partnerships. Rather than trying to acquire every complementary capability, they've developed a strategic partnership program that serves multiple purposes. By integrating their data into platforms like CamoAg, Arcadium, and Voze, Fusable is expanding their reach, creating a new pipeline source, and making their data more accessible and valuable to customers.
Partnership Strategy Highlights:
"If they're using any of our products today, which they do for prospecting, for example, they'd have to log into that tool, do their prospecting, extract the file, then potentially they go load it into a CRM or wherever they're going to do their work. And it becomes multiple touch points and swivel chairs where you've got a lot of manual entry, you've got the potential of human error," Tina emphasized.
Key Benefits:
The transformation required consolidating multiple CRM systems and creating a streamlined tech stack that would empower rather than burden the sales team. This meant moving from systems primarily used for order entry to true sales enablement tools that provide actionable insights.
Tech Stack Evolution:
Fusable's transformation continues as they build out self-service capabilities for certain customer segments and expand their partnership ecosystem. The company's evolution from a traditional media business to a mission-critical data provider shows how thoughtful leadership and strategic change management can unlock tremendous value while bringing employees along on the journey.
Success Indicators:
Fusable’s transformation stands as a powerful example for any company seeking to evolve their revenue organization while preserving the unique qualities that set them apart.
In my latest episode of The Revenue Room podcast, I sat down with Narisa Wild, Chief Digital Officer at Clarion Events North America, for a dynamic discussion about the future of B2B events and media. According to recent research from UFI's Global Exhibition Barometer, digital transformation has become more than just a buzzword – it's a critical journey that organizations must navigate thoughtfully to remain competitive in the events and media industry.
"It's not about us - it's about the customer," Wild emphasized early in our conversation, challenging the traditional approach to digital transformation in events. This simple yet powerful statement sets the tone for her entire philosophy about organizational change. As highlighted in McKinsey's latest digital transformation report, rather than viewing digital transformation as a technological upgrade, organizations must see it as a fundamental shift in how they serve and connect with their B2B customers.
Wild's comprehensive framework is built on three essential pillars:
-Customer-focused digital initiatives
-Internal culture transformation
-Operational agility in event technology
In our discussion, I emphasized how the concept of "customer" extends beyond traditional boundaries. From my experience working with numerous organizations (as shared in a previous blog on customer-centricity), I've observed that companies should consider all different stakeholders, including their employees, as customers. Successful companies understand that the definition of “customer” is broad and wide.
When it comes to artificial intelligence in events, Narisa’s approach stands out for its practicality and focus on tangible results. The latest CEIR research states that 83% of event professionals are now incorporating AI. At Clarion, AI isn't just a shiny new tool – it's a means to solve real business challenges -internally and externally - while enhancing how revenue is captured, retained and grown and how the event experience is improved in meaningful ways.
One of Clarion's innovative AI initiatives involves partnering with 60 Seconds, a platform that combines bespoke video creation with AI messaging to power the entire customer journey. Narisa shared how this technology has transformed their top-of-funnel prospecting by creating highly personalized video outreach that adapts based on the sender and recipient. For example, a sponsor outreach might come from one team member, while an attendee outreach features an executive vice president from that portfolio – complete with their face and voice speaking directly to the recipient. This personalization has led to significantly higher engagement rates.
Narisa then shared another transformative AI implementation: their "second screen experience" powered by RozieAI. RozieAI addresses a critical challenge at large events – how to help attendees extract maximum value when they can't physically attend all relevant sessions, which can number over 150 at a single event.
The system works by providing real-time, contextual summaries of sessions that include:
At the end of each busy event day, attendees receive a comprehensive debrief.
As Narisa explains,"Imagine you've gotten your 27,000 steps, you've met with 120 people on the show floor, you've had your one-to-one meetings, you've attended maybe three sessions, you've stood in line at Starbucks for 14 minutes for a coffee. You're absolutely whipped. Now you've got to go to the opening reception and you get an hour back at your room. You get delivered your debrief for the day." This debrief helps attendees stay informed about everything discussed at the event, including sessions they couldn't attend in person.
I love these two use cases…they are keepers!
According to Deloitte's 2024 Events Industry Outlook, several key trends are shaping the future of events and media. As PwC's latest research on Gen Z in the workforce indicates, we're experiencing what I characterized as "the tsunami of change."
The evolution includes:
What makes Narisa’s insights so valuable is their practical nature combined with a clear vision for the future of B2B media events. For more insights from industry leaders, check out our full podcast series on digital transformation in media and events.
To dive deeper into these insights and learn more about the future of events and media, listen to the full conversation with Narisa Wild on The Revenue Room™ podcast. The discussion includes additional examples, practical implementation strategies, and valuable lessons from her extensive experience in digital transformation.
Apple: https://podcasts.apple.com/us/podcast/the-revenue-room-by-h2k-labs/id1690675143?i=1000684916845
Spotify: https://open.spotify.com/episode/1RysU0aMG1MTsn5qhaz4ZP?si=0521e4497758491a
YouTube: https://www.youtube.com/watch?v=Tww1Vh0ihso&t=168s
In today's complex B2B media and events landscape, revenue leaks can significantly impact your bottom line. Understanding and addressing these leaks is crucial for maintaining healthy business growth. Let's explore the top 10 causes of revenue leak and their solutions, based on industry case studies.
One of the most common sources of revenue leak starts at the very beginning of the sales process. Poor lead qualification, slow follow-up times, and inadequate nurturing can cause potential customers to slip through the cracks.
Solution: Implement an AI-driven lead scoring system that analyzes historical data, engagement metrics, and firmographics. According to a B2B publisher case study, this approach led to a 30% increase in conversion rates and 20% reduction in sales cycle length.
Inconsistent pricing across channels and excessive discounting can severely impact your revenue potential. When pricing strategies aren't properly managed, you're essentially leaving money on the table.
Solution: Develop a dynamic pricing model, particularly for event sponsorships and exhibition spaces. A trade show organizer implementing dynamic pricing based on demand, location quality, and sponsor profile saw a 15% increase in overall sponsorship revenue.
Siloed customer information and the lack of a comprehensive customer view prevent organizations from making data-driven decisions and delivering personalized experiences.
Solution: Implement a Customer Data Platform (CDP) that integrates information from all touchpoints - web, events, subscriptions, and advertising. Case studies from multi-channel B2B media companies show this approach can lead to a 25% increase in customer lifetime value and 40% improvement in campaign performance.
Existing customers often present the greatest opportunity for revenue growth, but also tend to be a sales organization’s most untapped cohort. Missing opportunities for account expansion and poorly timed upsell offers represent significant revenue leaks in many organizations.
Solution: Deploy AI-powered recommendation systems that analyze customer behavior and purchase history. A B2B publisher implementing this solution achieved a 35% increase in revenue per account and 20% improvement in customer satisfaction.
It’s all too common for marketing, sales, and customer success teams to lose focus on existing customers once deals have closed. New business is vital, but how are you ensuring continuity of quality service for existing accounts? Failing to identify at-risk customers and having inadequate customer success processes can result in preventable customer losses.
Solution: Implement predictive churn prevention programs using machine learning models. A subscription-based industry information provider using this approach documented a 40% reduction in churn rate and 15% increase in renewal rates.
Manual processes, inefficient quote-to-cash workflows, and poor inventory management create costly errors and delays.
Solution: Automate your quote-to-cash process with integrated systems for CRM, event management, and financials. An event organizer implementing this solution achieved a 50% reduction in billing errors and 30% faster cash collection.
When sales and marketing teams operate in silos with inconsistent messaging and strategies, revenue opportunities are missed.
Solution: Deploy a revenue operations platform that serves as a single source of truth for both teams. A B2B media company using this approach saw a 20% increase in marketing-attributed revenue and 30% improvement in lead quality.
Poor user experiences, ineffective engagement strategies, and misalignment between product offerings and customer needs can significantly impact revenue across all business lines.
Solution: Implement robust data collection and analysis across key performance indicators. Essential metrics to track include:
Case studies show that conference organizers implementing comprehensive engagement analytics achieved a 45% increase in attendee satisfaction scores and 25% improvement in exhibitor ROI.
Ineffective paywalls and undervalued advertising inventory represent significant missed revenue opportunities.
Solution: Implement machine learning models to optimize paywall strategies and personalize subscription offers. A digital publisher using this approach documented a 30% increase in subscription conversions and 20% improvement in ad revenue.
What isn’t measurable isn’t manageable. Without proper tracking and attribution, organizations struggle to identify and address revenue leaks effectively.
Solution: Deploy real-time analytics dashboards that integrate data from all revenue sources. A media conglomerate implementing comprehensive analytics saw a 15% improvement in forecast accuracy and identified new revenue opportunities worth 10% of annual revenue.
Revenue leaks can significantly impact your organization's growth and profitability, but they're not insurmountable. By identifying these common causes and implementing data-driven, AI-powered solutions, you can plug these leaks and optimize your revenue operations. The key is to approach these challenges systematically and leverage modern technology to create more efficient, effective processes.
Remember that addressing revenue leaks is not a one-time fix but an ongoing process of optimization and improvement. Start by identifying your most significant areas of revenue leak and prioritize solutions that will have the biggest impact on your bottom line.
All statistics cited are from case studies documented in industry research on B2B media and events companies.
In our first episode of Season 2 of The Revenue Room™ podcast, Constance Sayers, President and Chief Revenue Officer of GovExec, shared invaluable insights on transforming a traditional B2B media company into a sophisticated data and intelligence platform. As a member of Revenue Room™ Connect's Executive Advisory Board and featured speaker at the upcoming RevvedUP event in Sarasota this February, Sayers offered a masterclass in leveraging data to drive enterprise value and revenue growth.
One of the most compelling aspects of GovExec's transformation was its strategic approach to acquisitions and data integration. After completing 16 acquisitions in 2021, the company faced the challenge of unifying disparate data sources and technologies. Rather than maintaining multiple platforms, the GovExec team boldly decided to consolidate around GovTribe as its central platform, investing significantly in building a comprehensive data lake.
This investment proved prescient. By combining GovTribe's contract data with real-time analytics from their news properties reaching 4.3 million government buyers, GovExec created a unique capability that set them apart from competitors.
"No one else is doing this," Sayers emphasized. "You can have contract data, but nobody has news sites that minute-by-minute are generating intent signals through searches and downloads."
The robust data foundation enabled GovExec to rapidly develop AI-powered solutions when the technology emerged. Instead of rushing to implement AI without proper infrastructure, they were able to leverage their existing data lake to create valuable tools for government contractors. These include:
GovExec's evolution in sales presentation represents a significant departure from traditional B2B selling. Instead of overwhelming prospects with technical features or multiple product offerings, they developed an innovative "placemat" approach - an 11x17 printed visualization that transforms complex data capabilities into actionable insights for their top 50 clients.
The placemat consolidates multiple data points into a comprehensive view of the client's position, including:
"When clients look down at this single sheet, they immediately see their world reflected back to them," Sayers explained. "They can instantly identify where they're perceived poorly, where competitors are outperforming them, and which agencies offer the best opportunities."
The transformation from product-centric to solution-centric selling has required a fundamental shift in how GovExec approaches the market. "Clients don't care about our 16 logos," Sayers emphasized. "They care about capabilities that solve their specific challenges."
This new approach has led to several key changes in their sales strategy:
GovExec now actively targets two distinct buyer personas:
These two buyer personas are interconnected from a pipeline outcome. Marketing teams are charged with driving inbound leads from campaigns and sales and business development teams are charged with filling pipeline and accelerating through the buying journey using inbound leads from marketing and outbound leads they generate themselves. Sales and business development teams require a significant amount of data about prospects including purchase intent, organizational environment, past select processes and RFPs and more.
GovExec can now successfully impact end-to-end pipeline and understands that these two buyer personas, while interconnected, are distinct and require different GTM motions.
Rather than leading with product features, conversations now start with customer challenges:
The shift required significant investment in customer education:
Each client engagement is now powered by specific data insights:
This modernized approach has not only transformed how GovExec sells but has also changed how clients perceive and utilize their services. "We're no longer just a media company or a data provider," Sayers noted. "We've become a strategic partner in our clients' go-to-market success."
The transformation has fundamentally changed how GovExec approaches revenue generation. They now operate across three primary revenue streams:
This diversification has created new challenges in revenue operations, requiring careful attention to both traditional and emerging revenue streams. As Sayers explains, "You're spinning different types of revenue plates...you've got to spin those plates all constantly and really reinvent."
The complexity of managing these diverse revenue streams is particularly evident in how they've adapted their sales approach. As we mentioned above, GovExec now works with two distinct buyer personas: sales and business development teams seeking tools for contract pursuit, and marketing teams focused on demand generation. This dual-persona approach requires careful orchestration of resources and messaging.
A key innovation in their revenue operations has been the development of GovProspect, a product that bridges their traditional lead generation business with their new data capabilities. The tool enriches leads with GovTribe data to help clients better qualify and pursue opportunities, demonstrating how GovExec is finding synergies between their revenue streams.
The shift in work patterns post-pandemic has also influenced their revenue strategy. With government employees working remotely more frequently, contractors have struggled to maintain their traditional in-person relationships. This has led to increased demand for both data services (to understand agency priorities and decision-makers) and events (which have become crucial networking opportunities). GovExec has responded by ensuring their revenue streams complement each other, using data insights to enhance event value and event relationships to inform data services.
Sayers emphasizes the importance of maintaining focus on core revenue while pursuing innovation: "You can't take your eye off your core business... you've got to make sure that the products aren't going stale because they can go stale quickly." This has led to a strategy of continuous reinvention, where insights from their data platforms are used to refresh and enhance traditional products while new offerings are developed in response to emerging customer needs.
For media companies looking to make a similar transformation, Sayers offered pragmatic advice based on GovExec's successful journey. Her key recommendations for B2B media companies include:
"Understanding what your audience needs can help you provide a roadmap to other data-driven revenue streams," she explained. "Start solving problems and revenue will follow."
Constance will share more detailed insights on GovExec's transformation journey at RevvedUP in Sarasota February 25-27.
Her session, "Accelerating New Revenue Streams: How GovExec Turned Data into Dollars," will take place on Wednesday, February 26th, offering attendees a deeper look at how to evaluate data infrastructure investments and modernize sales organizations for new go-to-market motions.
The full conversation with Constance Sayers offers even more insights on navigating the intersection of media, data, and revenue.
Listen to the complete episode to hear her thoughts on women in revenue leadership, the changing dynamics of government contracting, and the unexpected benefits of their data transformation journey.
You can learn more about RevvedUP and register here.
In a wide-ranging conversation on the Revenue Room Podcast, Adweek CEO Will Lee shared his vision for transforming the 45-year-old trade publication into what he calls a "business intelligence resource platform." With over two decades of experience at major media brands including NPR, People, and Entertainment Weekly, Lee brings a unique perspective to leading Adweek during a transformative period in media and advertising.
Lee's journey with Adweek began unexpectedly in his youth, reading the magazine while waiting at his local library. Now as CEO, he sees Adweek as "a startup with a great head start," positioning the brand to evolve beyond its trade publication roots to become an essential resource for the entire marketing ecosystem.
Will Lee’s leadership philosophy is grounded in what he calls the "three T's":
Tenacity - the ability to navigate constant industry change;
Timeliness - a sense of urgency in execution; and
Taste - maintaining high standards that extend beyond content to every aspect of the business.
Under his leadership, Adweek is evolving its revenue model. While advertising remains central, Lee envisions expanding direct-to-consumer revenue through high-value intelligence products and services designed to help professionals make better decisions.
Lee has implemented a dual data strategy to drive this transformation. On one side, consumer-facing data is leveraged through their data editor to deliver actionable insights for stories ranging from major mergers to brand analyses. On the other, operational data accumulated over 45 years is being used to optimize advertiser relationships and improve the subscriber experience. This data-driven approach also extends to content evolution, with an interesting trend emerging: direct traffic to Adweek.com has increased since ChatGPT's launch, as readers increasingly seek authoritative source material over AI-summarized content. To deepen this advantage, Lee plans to harness AI to unlock historical archives and provide greater context, such as tracing the evolution of holding companies.
Rather than resisting AI, Lee encourages his team to embrace it as a tool to expand creative possibilities, analyze large datasets more effectively, and test and optimize content with unprecedented speed and scale. A recent partnership with Perplexity enhances search capabilities while providing valuable insights into user interaction data.
Lee’s vision is built on four strategic pillars: editorial content, events and convening, peer-to-peer community building, and business intelligence and analytics. He aims to expand Adweek's reach beyond marketing professionals to include CEOs, CFOs, CIOs, and other C-suite executives who need to understand marketing's broader business impact. This strategy is guided by three key principles, or "I's": investment-grade journalism that drives financial decisions, inspiration through community and peer interactions, and intelligence that enhances professional effectiveness.
What's particularly striking about Lee's approach is his emphasis on utility and actionable intelligence. As he puts it,
I only want seven minutes of your day, but I want it to be the first seven in the morning."
This focus on becoming an essential part of professionals' daily workflow reflects a broader transformation of media brands from pure information providers to integrated business tools.
Looking ahead, Lee sees significant industry disruption on the horizon and positions Adweek to be both a provocateur and practical resource helping professionals navigate change. With a clear vision and strategic framework in place, the next chapter of Adweek's evolution will be fascinating to watch.The conversation underscores a broader trend in B2B media: the shift from traditional publishing models to comprehensive platforms that combine content, community, and intelligence to drive business value. As Lee notes, "We have to unmess the mess" – helping professionals make sense of an increasingly complex marketing and advertising landscape.
Apple Podcasts: https://podcasts.apple.com/us/podcast/the-revenue-room-by-h2k-labs/id1690675143?i=1000680987954
Spotify: https://open.spotify.com/episode/5E5ArR43RPMeTJo8l0jbhY?si=672GM2NSTCKai8s3lCKL6w
YouTube: https://youtu.be/RygZMTUYZjM?si=S2GLbmF1l4l2V9vE
"If you don't have common data sets, it doesn't matter what LLM you put over the top of it, you're not going to get very far." - Matt Yorke, CEO, The Channel Company
In an era of rapid technological change, media companies must be agile, strategic, and forward-thinking to remain competitive. I recently sat down with Matt Yorke, CEO of the Channel Company and Revenue Room™ Connect executive advisory board member, who embodies this adaptive approach, bringing a wealth of experience from diverse leadership roles to reimagine how B2B media and technology intersect.
Yorke's international background has been instrumental in the Company's expansion strategy. In just 11 months, the organization has launched into new markets like Germany and Singapore, leveraging their powerhouse CRN brand. The approach isn't about simply replicating US strategies globally, but creating localized content and experiences that resonate with regional audiences.
A key innovation has been using AI to accelerate market entry. For instance, in their German market, a single editor can now produce extensive localized content by translating and adapting existing content through AI tools, dramatically reducing time and resource constraints.
Yorke offers a refreshingly pragmatic view of AI. He compares its potential to the Industrial Revolution—not about replacing people, but "dislocating" work and creating opportunities for higher-value contributions.
The Company is already implementing AI across multiple functions:- Creative teams can now generate multiple content variations in hours instead of days- Editorial teams can transform written content into video quickly- Localization processes have been streamlined, enabling faster international expansion
The Channel Company isn’t just a media company - it’s a data powerhouse. Matt Yorke emphasizes that clean, consistent data and a unified taxonomy are essential for unlocking AI's potential. "If you don't have common data sets," he notes, "it doesn’t matter what LLM you use—it won't get very far." At the Channel Company, data hygiene is ingrained in the culture, ensuring accurate forecasts, informed decisions, and streamlined operations.
Unified taxonomy plays a crucial role, providing consistency across global operations. "60% must mean 60% everywhere," Yorke explains, highlighting the need for predictable, reliable data. This disciplined approach enables AI to function effectively as a practical tool, creating scalable insights and driving higher-value work. For organizations, Yorke’s strategy underscores that the path to AI success begins with strong data fundamentals.
Yorke's leadership approach focuses on three key areas: people, process, and product. By breaking down organizational silos, standardizing processes, and continuously refining their offerings, the Channel Company is positioning itself at the forefront of B2B media transformation.
This strategy not only fosters a culture of collaboration but also ensures that every team is aligned with the company’s overarching goals. By streamlining operations and enhancing efficiency, Yorke creates an environment where innovation can thrive, enabling the Channel Company to respond swiftly to market changes. The emphasis on refining products also highlights the organization’s commitment to delivering unparalleled value to its clients, solidifying its position as a leader in B2B media and marketing.
The Channel Company represents a blueprint for media organizations navigating the complex landscape of technology, data, and AI. By maintaining a clear vision, investing in systematic processes, and embracing technological innovation, they're not just adapting to change—they're driving it.
Join us at the upcoming RevvedUP conference, where we will hear from Matt Yorke and a lineup of visionary leaders shaping the future of AI. These trailblazers are redefining the rules of the AI landscape, offering transformative insights and strategies for leveraging data and technology to drive innovation and enterprise value.
In a recent episode of the Revenue Room™ Podcast, host Heather Holst-Knudsen interviewed Anna Anisin, founder of Data Science Salon and a pioneer in the data science community. Their conversation revealed valuable insights for business professionals looking to harness the power of data science and AI. Let's explore four key areas discussed in depth:
Anisin's entrepreneurial journey highlights the importance of community-building in business success. This approach offers multiple benefits:
1. Customer Retention: By fostering a community around your product or service, you can increase customer loyalty and reduce churn.
2. Product Development: Communities provide valuable feedback and insights, helping you refine and improve your offerings.
3. Marketing Efficiency: A strong community can become a powerful marketing tool, reducing customer acquisition costs through word-of-mouth referrals.
4. Market Intelligence: Engaged communities offer real-time insights into customer needs and market trends, allowing you to stay ahead of the competition.
To build a community-centric business:
• Identify your target audience and their specific needs
• Create platforms for engagement (e.g., forums, events, social media groups)
• Consistently provide value through content, resources, and interactions
• Encourage user-generated content and peer-to-peer support
Anisin's work in eliminating bias in recruitment and algorithms is crucial for businesses leveraging AI. Here's why it matters:
1. Improved Decision-Making: Unbiased algorithms lead to more accurate and fair decisions, benefiting your business and customers.
2. Expanded Market Reach: By avoiding bias, you can better serve diverse customer segments, potentially increasing your market share.
3. Risk Mitigation: Addressing bias helps prevent potential legal and reputational risks associated with discriminatory practices.
4. Enhanced Innovation: Diverse perspectives in your data science teams can lead to more creative and comprehensive solutions.
To address bias in your data science initiatives:
• Regularly audit your data sets and algorithms for potential biases
• Implement diverse hiring practices in your data science teams
• Use tools and techniques designed to detect and mitigate bias in AI models
• Establish ethical guidelines for AI development and usage in your organization
Anisin's insights reveal that not all businesses need an AI strategy immediately. Here's how to determine if AI is right for your business:
1. Data Readiness: Assess your current data infrastructure and quality. AI requires clean, well-organized data to be effective.
2. Cost-Benefit Analysis: Compare the potential efficiency gains and cost savings of AI implementation against the investment required.
3. Business Objectives: Identify specific business problems that AI could solve or processes it could optimize.
4. Industry Relevance: Consider whether AI solutions are mature enough for your industry and use cases.
To strategically approach AI implementation:
• Conduct a thorough assessment of your data assets and infrastructure
• Identify high-impact areas where AI could provide significant value
• Start with small, pilot projects to test AI's effectiveness in your business context
• Develop a roadmap for scaling successful AI initiatives across your organization
Anisin's work with B2B marketing offers valuable insights for tracking marketing effectiveness and attributing revenue. Here's how businesses can benefit:
1. Improved ROI: By accurately tracking marketing efforts, you can optimize spend and focus on high-performing channels.
2. Better Customer Understanding: Multi-touch attribution models provide insights into the customer journey, allowing for more targeted marketing.
3. Sales and Marketing Alignment: Clear attribution helps align sales and marketing efforts, improving overall efficiency.
4. Budget Justification: Accurate revenue attribution makes it easier to justify marketing budgets and investments.
To implement data-driven marketing and revenue attribution:
- Implement robust tracking tools like HubSpot or Salesforce
- Develop a clear funnel structure (e.g., MQLs, SQLs) and define conversion metrics
- Use multi-touch attribution models to account for various customer touchpoints
- Regularly analyze and adjust your marketing mix based on attribution data
By focusing on these four areas - community building, addressing bias in AI, strategic AI implementation, and data-driven marketing - business professionals can leverage data science and AI to drive growth, improve decision-making, and enhance customer experiences.
The events industry is undergoing a seismic shift, driven by evolving customer expectations, technological advancements, and the lingering aftereffects of the COVID-19 pandemic. In a recent episode of the Revenue Room podcast, Mike Carlucci, Chief Operating Officer at Clarion Events North America, shared actionable insights into how his organization has embraced data-driven strategies to adapt to these changes. This article explores his approach in detail, offering valuable lessons for businesses aiming to enhance their operations and customer engagement.
Carlucci began by highlighting how the events industry has transformed more in the past three years than in the prior two decades. This acceleration has been fueled by generational shifts, with millennials and Gen Z taking on decision-making roles, and by the pandemic forcing businesses to innovate at an unprecedented pace. At the heart of this transformation is data.
Clarion Events has shifted its focus to becoming a "data business," using insights to improve decision-making and customer experiences. For example, they conducted a forensic analysis of their customer journey by examining every touchpoint—from sales to operations and service teams. This holistic approach allowed them to identify friction points and opportunities for improvement.
By involving all stakeholders—internal teams and external partners alike—Clarion created an ecosystem where everyone is aligned toward a shared goal. Carlucci described this as their "North Star," a guiding principle that ensures every decision prioritizes the customer experience.
One of the most impactful ways Clarion uses data is to optimize pricing strategies. Carlucci shared an example of analyzing when most sales occur for events. Their data revealed that sales typically peak three months before an event, during the event itself (due to rebooking), and shortly afterward. Armed with this knowledge, they adjusted pricing models to incentivize earlier bookings and create steadier revenue streams throughout the year.
Additionally, Clarion conducts deep dives into historical data for each event. They analyze what was sold, when it was sold, and at what margin. This allows them to identify trends and adjust pricing or product offerings accordingly. For instance, rather than applying blanket price increases across all events—an approach that risks alienating customers—they use data to pinpoint specific areas where value can be added without overburdening attendees or exhibitors.
Carlucci also emphasized that data helps uncover gaps in demand and emerging trends. By constantly engaging with customers and analyzing feedback, Clarion ensures they remain responsive to market needs.
A key takeaway from Carlucci’s approach is the importance of personalization. Clarion uses data not just to optimize operations but also to deliver tailored experiences for their attendees and exhibitors. For example, their connection program, Clarion Connect, focuses on facilitating meaningful interactions between buyers and sellers at events.
Using technology like AI, Clarion enhances matchmaking processes and designs event environments that encourage networking. They also gather feedback from participants after each event to refine their approach continually. Carlucci stressed that creating bespoke experiences is about delivering what customers want for them, by them—a mantra that underscores Clarion’s commitment to customer-centricity.
One of the most significant challenges Carlucci tackled was breaking down silos between sales, operations, and service functions. Traditionally, these departments operate independently in many organizations, leading to disjointed customer experiences. At Clarion, however, they have fostered a culture of collaboration.
This transformation required a cultural shift within the organization. Carlucci acknowledged that mistakes were made along the way but emphasized that failure is an essential part of learning. By empowering team members at all levels and ensuring everyone had a voice in decision-making processes, Clarion created a unified strategy focused on the customer journey.
For example:
- Sales teams were encouraged to work closely with operations and service teams to understand how their actions impact the overall customer experience.
- External vendors—such as decorators or AV providers—were treated as extensions of the Clarion brand rather than separate entities.
- Regular meetings were held where all stakeholders shared insights and aligned on goals.
This alignment has paid off significantly. Carlucci noted that during one of their largest events in Las Vegas (InsureTech Connect), even new hires were fully engaged in delivering exceptional customer experiences—a testament to the success of this unified approach.
Another critical factor driving change in the events industry is generational shifts among attendees. Millennials and Gen Z now dominate decision-making roles, bringing with them different expectations for event experiences. These generations demand personalization, value for time spent at events, and seamless digital integration.
Carlucci recognized that adapting to these changes required a mindset shift but embraced it as an opportunity rather than a challenge. He encouraged businesses to think like their customers: Why should someone attend your event? What makes it worth their time? By answering these questions through thoughtful planning and execution, organizations can stay relevant in an increasingly competitive landscape.
Carlucci’s insights offer several actionable lessons for businesses across industries:
1. Leverage Data Holistically: Use data not just for operational efficiency but also to enhance customer experiences.
2. Focus on Key Priorities: Rather than trying to tackle everything at once, identify three critical initiatives that will drive meaningful change.
3. Foster Collaboration: Break down silos between departments and involve external partners in your strategy.
4. Adapt Quickly: Embrace failure as part of innovation and remain agile in responding to market changes.
5. Prioritize Personalization: Tailor your offerings based on customer feedback and preferences.
By adopting these strategies, businesses can not only navigate the challenges of a rapidly changing market but also position themselves for long-term success. As Carlucci aptly put it: "If you’re doing wash-rinse-repeat in this industry, you will be irrelevant."
RevvedUP 2025 is your pit stop for premium networking, cutting-edge tech insights, and strategies that'll put you ahead of the curve.
You can get more hands-on strategies direct from Mike at RevvedUP 2025. RevvedUP 2025 is your pit stop for premium networking, cutting-edge insights, and practical strategies that'll put you ahead of the curve. Fuel your enterprise growth with data and AI-driven strategies, and position your organization for success.
Join us to network with Mike Carlucci and other industry leaders at RevvedUP.
According to Gong's newest State of Revenue Growth Report, when asked if their CRM provides a comprehensive understanding of their customers, only 10% of respondents strongly agreed. This statistic is even more striking for media and events businesses, where revenue streams are uniquely interconnected and complex.
Media and events companies operate as sophisticated orchestrators, managing multiple interdependent customer segments. Consider a trade show organizer: exhibitors need attendees to justify their investment, while attendees rely on exhibitor quality and diversity to validate their participation. Similarly, B2B media platforms must balance subscriber value with advertiser reach, while ensuring content quality maintains audience engagement across digital, print, and in-person channels.
This interconnected ecosystem generates data across numerous touchpoints - from webinar participation rates to exhibition floor dwell time, content engagement metrics to advertising performance. While CRM systems excel at managing direct customer relationships, they weren't designed to capture these industry-specific interactions and dependencies that truly drive revenue performance.
To build an accurate revenue picture, media and events leaders need to integrate data from multiple specialized systems that capture the unique dynamics of their business model. The impact on top and bottom lines can include the ability to:
1. Detect and address customer churn effectively.2. Spot and capitalize on upselling and cross-selling opportunities.3. Scale top-performing sales strategies to help elevate B players into A players.4. Refine and implement high-converting sales processes, pricing strategies, and packaging tailored to specific customer segments.5. Identify and grow “outlier” revenue streams.6. Enhance the accuracy and reliability of sales forecasts.7. Minimize the time and resources spent on reforecasting.8. Improve unit-level economics and profit margins, even down to individual customer insights.9. Optimize pricing and packaging strategies to ensure maximum value delivery.10. Uncover program performance issues and pivot
And more….
Here are the 10 essential non-CRM data sources that provide crucial insights for revenue leaders in media and events:
1. Event management platforms (attendance patterns, exhibitor ROI metrics, session engagement, buyer-seller matching data)2. Digital content platforms (subscriber behavior, content consumption patterns, topic preferences, gated content conversions)3. Advertising operations systems (campaign performance, yield metrics, advertiser engagement scores)4. Marketing automation platforms (email engagement, lead scoring, nurture campaign effectiveness across audience segments)5. Community/networking platforms (member interactions, discussion topics, peer-to-peer connections, expert engagement)6. Virtual event platforms (attendance duration, interaction rates, networking effectiveness, sponsor visibility metrics)7. Mobile event apps (attendee behavior, meeting scheduling, live polling results, exhibitor lead scanning)8. Business intelligence tools (cross-platform audience overlap, segment profitability, lifetime value analysis)9. Social media analytics (community engagement, influencer impact, content sharing patterns, sentiment analysis)10. Customer data platforms (unified profiles, cross-channel journey mapping, segment propensity modeling)
The data universe for the media and events landscape is so much more complex than what tends to be reflected in traditional CRMs, and often the signals from beyond the digital walled garden and even offline sources are where the keys to robust customer understanding lie. For an industry that is truly at its best when it supports and represents the nuances of all its audiences’ behaviors, it deserves an equally nuanced and inclusive, while highly sophisticated, data strategy.
"AI's real value lies in its ability to drive new growth curves and transform customer experiences, but success requires strategic vision and cross-functional collaboration."
The Revenue Room™ podcast recently featured Peter Cohan, an associate professor at Babson College and a strategic consultant. This engaging discussion explored the transformative impact of artificial intelligence (AI) on business strategies, particularly in driving revenue growth and creating competitive advantages.
Cohan's insights are particularly relevant as we navigate the current AI revolution, which is reminiscent of the early 2000s internet boom but with potentially more far-reaching consequences. While the internet primarily disrupted information flow and marketing, AI is transforming multiple facets of business operations, including work processes, product development, operational efficiencies, marketing, customer engagement, and decision-making.
One of the key concepts introduced by Cohan is the "value pyramid," which categorizes AI applications into three distinct levels. At the base level, many companies are using AI to overcome creator's block—essentially aiding productivity but not providing a competitive edge since this application is widely accessible. The middle level focuses on enhancing functional productivity; for example, AI can improve efficiency in coding and customer service by training systems to replicate the best practices of high-performing employees. The top level of the pyramid, which is the rarest and most impactful, involves using AI to create new growth curves that drive significant business transformation and innovation.
Despite its potential, businesses face significant hurdles in implementing generative AI. Cohan highlights several challenges:
• Fear of Reputational Damage: Companies worry about public relations issues stemming from AI errors or hallucinations.
• Balancing Innovation with Risk: CEOs fear being left behind in the AI race while boards are cautious about potential negative consequences.
• Implementation Hurdles: Of the 200-300 AI applications typically developed by large companies, only a handful are released internally or tested externally due to these concerns.
These challenges underscore a critical point: while many organizations are exploring AI applications, few are successfully leveraging this technology to create new growth opportunities.
Cohan provides examples of companies that have successfully implemented AI in innovative ways. ServiceNow has rolled out generative AI agents for process automation across various functions. Initially focused on customer service ticket resolution, they have expanded their use of AI to streamline onboarding processes and other cross-functional tasks. This approach not only improves efficiency but also allows employees to focus on higher-value activities.
Salesforce is another company making strides with its Agent Force technology. By employing an agentic approach that enables AI to solve entire problems autonomously—from marketing campaigns to customer service—Salesforce is positioning itself for rapid growth. Early adopters of this technology have reported significant improvements in operational efficiency and customer satisfaction.
The landscape of the AI industry today is markedly different from that of the dot-com era. During the dot-com boom from 1996 to 2001, there were 2,888 IPOs of internet companies; however, there have been no IPOs for generative AI companies thus far. This shift indicates that while startups drove innovation during the dot-com boom, the current wave of AI advancements is largely being propelled by established tech giants operating cloud services platforms.
Cohan emphasizes that businesses should focus on leveraging proprietary data when developing their AI solutions. This strategy can provide a competitive advantage through unique value propositions that are difficult for competitors to replicate. Additionally, he advocates for cross-functional integration within organizations to break down silos and fully leverage AI's capabilities.
As industries continue to evolve under the influence of AI, several sectors stand out as particularly poised for growth opportunities. The media industry, for instance, possesses rich data environments that can be harnessed effectively with AI technologies. Companies in this space can leverage audience data—from engagement metrics to purchasing behaviors—to create personalized experiences and enhance content delivery.
The insights shared by Cohan during this episode of The Revenue Room™ podcast highlight the critical role of AI in reshaping business strategies and driving growth. By focusing on customer-centric applications, leveraging proprietary data effectively, and fostering collaboration across functions, businesses can harness AI's full potential while mitigating associated risks. As companies navigate this rapidly changing landscape, success will depend on their ability to strategically leverage technology to create genuine value and maintain a competitive edge in an increasingly dynamic market environment.
We are a people-based business and it's our people, our ideas, how they are able to communicate that actually gives us a competitive advantage.
Paul Miller, CEO of Questex, has led a remarkable transformation of the company over the past six years, focusing on three key areas that offer valuable insights for leaders in the media and events industry:
When Miller joined Questex, the company operated as 20 small, independent businesses with disparate data systems. He recognized that this structure limited the company's potential and took decisive action:
- Consolidated databases into a single, centralized Questex database
- Implemented a unified customer data platform (CDP)
- Centralized key functions like product development, brand and experience, data management, and event operations
This centralization allowed Questex to:
- Hire higher-caliber talent by offering roles within a $120 million operation rather than $5 million units
- Enable cross-pollination of ideas and best practices across the organization
- Force market-focused teams to concentrate on customers rather than operational tasks
Miller emphasizes that this was not a simple process, stating, "When I talk about it, sounds kind of simple, it really was a rip the company down to its studs and rebuild it as a fit for purpose for the new generation, really".
With a centralized data infrastructure in place, Questex now uses real-time audience insights to drive content creation and customer engagement:
- Editorial teams receive reports on trending articles across Questex properties and the broader internet
- Content creators use this data to steer interviews, panel recruitment, and conference programming
- Sales teams leverage audience interest data to identify relevant accounts for targeted outreach
Miller provided a concrete example: "They now see that there's a huge surge in people reading about affordability of prescription drugs. Actually happens to be a real thing. And once they get that, the editors can then steer their content, their interviews, their panel recruitment, their conference programs to affordability as being a key section".
This data-driven approach allows Questex to:
- Deliver highly relevant content across digital and event platforms
- Personalize marketing messages based on demonstrated interests
- Increase the value proposition for advertisers and sponsors
Having worked with private equity-owned companies throughout his career, Miller has observed a shift in focus from PE investors:
- Board meetings have become increasingly data-driven, with members demanding supporting data for strategic decisions
- While EBITDA remains important, there's a growing emphasis on top-line growth
- PE firms are more willing to invest in growth initiatives based on data-backed strategies
Miller notes, "I'm certainly finding that growth, top line growth, is actually a much more significant part of my current conversations with private equity. And I'm not saying it never was, I mean, it was always there. But now it's almost like a, listen, let's invest for top line growth based on the data".
This shift has led to new types of data requests from PE owners, including:
- New logo performance metrics
- Customer churn analysis
- Pricing strategy evaluations
By aligning with these evolving PE expectations, Questex is positioning itself for sustainable growth and increased enterprise value in a rapidly changing media landscape.
Join us at RevvedUP 2025 to hear more from Paul Miller and other visionary leaders shaping the future of AI. These trailblazers are redefining the rules of the AI landscape, offering transformative insights and strategies for leveraging data and technology to drive innovation and enterprise value.
"There's no AI without data, and there's no success without people." - Doug Llewellyn, CEO, Data Society Group
In today's data-driven business landscape, staying ahead of the curve is not just an advantage—it's a necessity. For business owners in the tech and data industries, Doug Llewellyn, CEO of Data Society Group, offers valuable insights into bridging the gap between data capabilities and workforce skills. His unique perspective, combining over 25 years of experience in digital transformation with leadership of a fast-growing data transformation company, provides a roadmap for organizations looking to unlock untapped potential.
Llewellyn emphasizes the critical intersection of people and data. This approach recognizes that while data is crucial, it's the people who interpret and act on it that truly drive value.
Key areas of focus include:
For business owners seeking to maximize their AI investments and transform data challenges into opportunities for growth and innovation, Llewellyn's perspective offers a valuable guide to navigating the rapidly evolving landscape of data and AI in business.
At the heart of Data Society Group's mission is the recognition that people and data are an organization's two most valuable assets. Doug Llewellyn emphasizes this point, stating, "We are at the intersection of people and data. And that intersection is even more important now when you throw in what I don't even think is a buzzword anymore of AI, right?"
This perspective is crucial because:
1. Data alone is not enough: Organizations can have the cleanest, most accessible data, but without people who can interpret and act on it, its value is limited.
2. Skills are essential: Even the best data analysts and scientists can't create value if they can't access clean, relevant data.
Llewellyn introduces the concept of a value graph, where the X-axis represents data infrastructure and the Y-axis represents analytics capabilities. The 45-degree line between these axes represents the "V" or value creation. This model illustrates the need for balance between technological capabilities and human skills to drive business impact.
One of the most striking statistics mentioned in the podcast is that only 11% of employees feel confident working with data. This gap presents a significant challenge for organizations aiming to become data-driven. Data Society Group is addressing this issue through a multi-faceted approach:
1. Data Literacy Programs: The Data Lodge offers advisory services, executive sessions, and change management programs to help organizations build a data culture.
2. Instructor-Based Training: Data Society provides hands-on training ranging from "Gen AI 101" to advanced topics like R and Python programming.
3. Community Building: CDO Magazine facilitates knowledge sharing among data leaders through events, summits, and intimate executive dinners.
A notable example of this approach in action is Data Society Group's recent project with a 100-year-old publisher, where they trained 7,000 non-technical employees on generative AI. This initiative demonstrates the growing recognition that upskilling existing workforce is often more effective than trying to hire new data science talent.
Llewellyn sheds light on the challenges faced by Chief Data Officers (CDOs), a role that has gained prominence in recent years but often struggles with high turnover rates. He points out that the average tenure for a CDO is less than 2.5 years.
According to Llewellyn, key factors contributing to this issue include:
1. Misaligned Expectations: Many organizations hire CDOs expecting them to solve all data-related problems, without recognizing the complexity of the role.
2. Lack of Business Acumen: Some CDOs excel in technical aspects but struggle to translate data initiatives into business value.
3. Overwhelming Demands: CDOs face pressure to address multiple priorities simultaneously, from data governance to AI strategy implementation.
To address these challenges, Llewellyn suggests that CDOs need to be empowered to collaborate across the organization. He emphasizes the importance of clear communication channels, particularly with roles like the Chief Information Security Officer (CISO) to ensure data security.
By focusing on these three aspects – the intersection of people and data, the democratization of data skills, and the evolving role of the CDO – organizations can better position themselves to create value from their data and AI initiatives. As Doug Llewellyn aptly puts it, " "There's no AI without data, and there's no success without people."
You can get more hands-on strategies direct from Doug at RevvedUP 2025, where he’ll be joining us as a speaker!
RevvedUP, coming February 25 – 27 in Sarasota, is your pit stop for premium networking, cutting-edge insights, and practical strategies that'll put you ahead of the curve. Fuel your enterprise growth with data and AI-driven strategies, and position your organization for success.
Join us to network with Doug Llewellyn and other industry leaders at RevvedUP!
"How do we help people be fully engaged? And so whether it's fully engaged at work or fully engaged in your marriage or fully engaged in your friendships or whatever that is, how do you show up all the way and in a way that's healthy?"
Imagine transforming your workplace into a thriving hub of innovation, collaboration, and employee satisfaction—all while operating remotely. Sounds too good to be true? Not according to Chris Dyer, a renowned company culture and remote work expert who recently shared his insights on The Revenue Room™ Podcast with Heather Holst-Knudsen.
In an era where remote work has become the norm for many businesses, leaders are grappling with new challenges: How do you foster innovation, maintain team cohesion, and keep employees engaged when they're not in the same physical space? Chris Dyer's expertise offers a beacon of hope for organizations navigating these uncharted waters.
Drawing from his experience as a former CEO who successfully transitioned his company to remote work in 2008, Dyer provides practical strategies that can revolutionize how companies operate in virtual environments. His insights are particularly crucial for:
1. CEOs and executives struggling to maintain productivity and innovation in remote settings
2. HR professionals seeking to improve employee engagement and reduce turnover in distributed teams
3. Managers looking for effective ways to lead and develop their remote team members
4. Entrepreneurs aiming to build strong company cultures from the ground up in a digital-first world
Let's dive into three key areas Dyer explored that can transform your remote work experience:
Dyer introduced two unique meeting concepts that can significantly enhance team collaboration and problem-solving in remote settings:
1. Cockroach Meetings: These are short, impromptu meetings designed to address small issues quickly. Key features include:
- 15-minute maximum duration
- 5-7 participants maximum
- Anyone can call the meeting and invite anyone else
- Attendance is entirely optional
This format encourages cross-departmental interaction and rapid problem-solving, which is particularly effective in remote settings where casual office interactions are less frequent. Cockroach meetings help prevent employees from spending hours trying to solve problems on their own, instead leveraging the collective knowledge of the team.
2. Tsunami Planning Meetings: These monthly team meetings focus on hypothetical scenarios to stimulate creativity and improve meeting dynamics. The process involves:
- The leader choosing an imaginary scenario (e.g., "What if our business doubled?")
- 30 minutes of team discussion with minimal leader intervention
- Leaders observing team dynamics to identify areas for coaching
These meetings serve dual purposes: they foster innovation by allowing free-form brainstorming on hypothetical situations, and they provide leaders with insights into team members' meeting behaviors, enabling targeted coaching to improve overall meeting effectiveness.
Dyer shared strategies for successfully transitioning to and maintaining a remote work environment:
1. Intentional Communication: Replace accidental office interactions with structured communication:
- Move coaching and goal-setting discussions from one-on-one meetings to team meetings
- Implement regular team check-ins (daily, weekly, or as needed)
- Use group settings to discuss individual and team progress
2. Conscious Gatherings: Plan deliberate in-person meetings to maintain team cohesion:
- Annual all-employee gatherings for team building and brainstorming
- Quarterly in-person meetings for specific teams (e.g., sales team)
- Monthly in-person meetings for leadership teams
3. Virtual Collaboration Tools: Utilize technology to replicate in-office collaboration:
- Implement virtual whiteboarding tools for brainstorming sessions
- Use project management platforms to track progress and ideas
Dyer addressed the challenge of workplace loneliness in remote settings:
1. Setting Expectations: Clearly communicate to employees that remote work may change the nature of workplace relationships:
- Explain that work may no longer be the primary source of social interaction
- Encourage employees to seek social connections outside of work
2. Balancing Work and Personal Life: Help employees understand the need to:
- Separate work from personal time more distinctly in a remote setting
- Actively pursue social activities and relationships outside of work
3. Team Building Activities: Implement virtual team-building exercises to maintain a sense of connection:
- Regular video check-ins that include personal updates
- Virtual social events or game sessions
By implementing these strategies, companies can create a more engaging, productive, and satisfying remote work environment. Dyer's approach emphasizes intentional communication, structured collaboration, and a realistic view of workplace relationships in the digital age.
The focus has shifted from "selling data by the pound" to understanding clients' businesses and configuring data solutions to solve specific problems.
In a recent episode of The Revenue Room™ Podcast, Matt Reilly, CEO of Fusable, shared insights into the company's transformation from a traditional media entity to a data-first business. This evolution offers valuable lessons for CEOs managing legacy businesses and aiming to leverage data for growth.
Fusable emerged as a spin-off from Randall Riley, a 110-year-old established media brand in the trucking and transportation space. The transition began when leadership recognized the intrinsic value of their data assets, which were initially acquired to find more customers. As Reilly explains, "When I came aboard, our mission was really to pivot this part of the company fully into the data space."
The company consolidated its critical mass in the data business, including digital assets, and made strategic acquisitions to enhance its data portfolio. This focus led to the decision to separate from Randall Riley and launch Fusable as an independent entity on May 1, 2024.
The name "Fusable" organically emerged during a marketing team meeting, reflecting the company's core function of fusing data sets to create more value for clients. This rebranding signifies a clear shift in focus and identity.
Fusable's unique position as a "110-year-old startup" presents both opportunities and challenges in the modern business landscape. The company has successfully retained valuable assets from its media heritage while pivoting to a data-first business model. This approach allows Fusable to combine the strengths of established industry presence with cutting-edge data capabilities.
One of Fusable's key legacy assets is the Commercial Carrier Journal (CCJ), which Reilly describes as "sort of like the Wall Street Journal for the trucking industry". This publication, along with other media properties, continues to play a crucial role in Fusable's data strategy:
1. Industry Attraction: These established media brands attract professionals from the trucking, transportation, construction, and agriculture sectors to Fusable's online assets.
2. Continuous Data Collection: The engagement with these media properties allows Fusable to continuously collect and refresh its databases.
3. Enhanced Value Proposition: The up-to-date information gathered through these channels enhances the value proposition for Fusable's clients, primarily large OEMs in the industries they serve.
At the heart of Fusable's business model lies a sophisticated flywheel strategy that seamlessly integrates their legacy media assets with their cutting-edge data capabilities. This approach creates a self-reinforcing cycle of value creation, benefiting both Fusable and its clients. Reilly emphasizes the critical role this strategy plays in the company's success, stating, "Our platform assets are really an important part of our flywheel."
The flywheel strategy is rooted in the synergistic relationship between Fusable's established media properties and its data-driven services. By leveraging the strengths of both components, the company has created a powerful ecosystem that drives continuous growth and innovation. Here's how the flywheel operates:
1. Content Creation: At the core of the flywheel are Fusable's prestigious media properties, such as the Commercial Carrier Journal (CCJ), which Reilly describes as "sort of like the Wall Street Journal for the trucking industry". These publications, along with other media assets, produce high-quality, industry-specific content that attracts professionals from various sectors, including trucking, transportation, construction, and agriculture.
2. Audience Engagement: The compelling content draws industry professionals to Fusable's online platforms and events. This engagement is crucial, as it provides multiple touchpoints for data collection and audience interaction.
3. Data Collection and Refinement: As users interact with Fusable's content and platforms, the company continuously collects and refines its data. This process ensures that Fusable's databases are constantly updated with fresh, relevant information about industry trends, user behavior, and market dynamics.
4. Enhanced Client Solutions: The rich, up-to-date data collected through media engagement is then leveraged to create more powerful and accurate solutions for Fusable's clients, particularly large OEMs in the construction, agriculture, trucking, and transportation sectors.
5. Client Success and Industry Impact: As clients utilize Fusable's data-driven insights to make better decisions and grow their businesses, they contribute to overall industry activity and trends. This, in turn, generates new topics and insights for Fusable's media properties to cover, completing the cycle.
The genius of this flywheel strategy lies in its self-reinforcing nature. Each component strengthens the others, creating a virtuous cycle of growth and value creation. As Reilly explains, "It's an important part of the flywheel strategy where we're creating content. People come to this content to learn from our editors. And then we have our relationships with our OEMs and our dealers and distributors who want to find out where should they go market or should they go sell".
By maintaining this delicate balance between media and data, Fusable ensures that its databases are "very updated and organically refreshing". This approach not only provides a competitive edge in data accuracy and relevance but also deepens Fusable's relationships with both its audience and clients, solidifying its position as a crucial player in the industries it serves.
Reilly emphasizes the importance of carefully selecting which elements of the legacy business to retain as Fusable evolves. He stresses the need to be "really crisp about communicating the things that we're going to bring along on the journey with us and the things that we're going to leave behind." This approach allows the company to leverage its historical strengths while embracing modern business practices.
The company has chosen to keep aspects of the business that create competitive advantage and help build a moat around their offerings.These include valuable assets, parts of the culture that make them unique, and deep industry relationships. Some of these relationships stretch back 70 years or more, providing Fusable with a level of trust and industry insight that pure startups cannot easily replicate.
At the same time, Fusable has intentionally left behind elements of the culture that were perhaps family-oriented or not aligned with modern business practices. This selective approach allows the company to maintain its valuable legacy while positioning itself as a forward-thinking, data-driven enterprise.
The result is a unique market position that combines the best of both worlds. Fusable benefits from decades-long relationships with clients and data assets that have been market-leading for up to 78 years, as in the case of their agricultural asset, Iron Solutions or Iron Guides. This longevity has built significant trust and reliance within their respective industries. At the same time, the company now offers an artificial intelligence platform backed by half a century of market-relevant data and industry relationships.
By carefully leveraging these legacy assets while embracing new technologies and data-driven approaches, Fusable has positioned itself as a unique player in the market. The company combines the credibility and depth of a century-old business with the agility and innovation of a modern data company, creating a powerful value proposition for its clients in critical infrastructure industries.
The shift from a media company with data offerings to a data-first company with media solutions has required significant changes in approach and mindset. Reilly highlights two key differences:
1. Client Interaction: As a data company, Fusable aims to be crucial to clients' operations rather than just an interesting or relevant source of information. Reilly illustrates this with an example: "If you're in the ag space and you're taking a trade on a half a million dollar combine, you have to look at our asset to make sure you don't lose money."
2. Solution Selling: The focus has shifted from "selling data by the pound" to understanding clients' businesses and configuring data solutions to solve specific problems. This approach aims to help clients make more money and embed Fusable deeper into their workflows.
To succeed in this transition, Fusable has implemented several key strategies:
1. Clear Communication: Reilly stresses the importance of being "crisp about communicating the things that we're going to bring along on the journey with us and the things that we're going to leave behind."
2. Customer Success Focus: The company has invested in upgrading its client success function, led by Chris Gertzma. This team works to ensure clients are accessing and deriving maximum value from Fusable's products, which drives up client satisfaction and NPS scores.
3. Board-Level Education: Reilly describes a careful approach to managing board expectations, including establishing credibility, delivering results in chunks, and using pilot projects to demonstrate ROI.
4. Pilot Approach: Fusable conducted a pilot project that yielded a 10x ROI, which helped secure board support for larger investments in data integration and automation.
5. Cultural Openness: Reilly emphasizes the importance of creating a culture where mistakes are openly discussed and quickly addressed, which is crucial for managing complex data projects.
Fusable's transformation into a data-first company involves integrating various data assets into a single, unified data layer. This project, described by Reilly as being in its "7th inning," aims to provide clients with seamless access to all of Fusable's data functionality, similar to how Netflix offers access to multiple channels through a single login.
To manage board expectations and mitigate risks associated with this large-scale project, Fusable adopted a pilot approach. Reilly explains, "when you're a private equity owned business, these transformations involve huge investments in data, people, platforms, and cultural change. There's a lot of education and expectation setting that needs to take place at the board level."
The pilot project demonstrated the power of combining data sets with artificial intelligence. For instance, what previously required 38 man-hours of analysis could now be accomplished in less than 30 seconds using a natural language processing interface. This dramatic improvement in efficiency and insight generation is at the heart of Fusable's value proposition.
The success of the pilot project, which delivered a 10x ROI, has been crucial in building credibility with the board and maintaining momentum for further development. It also helped in selecting the right implementation partner for the larger project.
As Fusable expands this integrated data layer to encompass all of their assets, they're fundamentally changing how their clients interact with and derive value from data. This transformation represents a significant shift from their legacy as a media company, positioning Fusable at the forefront of data-driven business intelligence in their target industries. By combining data sets and leveraging AI, Fusable has been able to dramatically increase the number of leads generated for clients while significantly reducing processing time.
As Fusable continues its transformation, it serves as a compelling case study for how legacy media businesses can reinvent themselves in the data-driven economy, balancing the value of established brands and relationships with cutting-edge data capabilities.
In a recent episode of The Revenue Room™ podcast, DeniseMedved, Chief Commercial Officer at Informa Markets North America, shared herextensive experience in leveraging data to drive sales strategies. With a richbackground in B2B and B2C events, Denise has held executive roles in variousorganizations, including Money 2020 USA and the Consumer TechnologyAssociation. At Informa, she focuses on data-fueled revenue and profitacceleration, making her a pivotal figure in the evolving landscape of sales.
Denise began her career with a finance degree from GeorgeWashington University, where she developed a keen understanding of numbers andtheir implications in business. However, her journey took an unexpected turnwhen she stumbled into the trade show industry. "I knew that I didn't wantto be in finance," she recalled, explaining her transition into sales andevents. This shift laid the foundation for her future success in understandinghow to connect data with sales outcomes.
During the interview, Denise emphasized the critical role ofdata in sales management. She stated, "Data is not just numbers; it's thestory behind the numbers that drives decision-making." This perspectiveunderscores the importance of understanding data to craft effective salesstrategies. By interpreting data trends and customer behaviors, sales teams cantailor their approaches to meet specific needs, ultimately driving betterresults.
Denise also highlighted the generational differences in theworkforce and their relationship with data. "We are in a transition periodnow where we still have people who didn't grow up on data, alongside those whodid," she explained. This divide presents both challenges andopportunities for sales teams as they adapt to new tools and technologies. Shenoted that while some team members are digital natives who seamlessly integratedata into their workflows, others require more guidance and training to embracethese changes.
A significant part of her role involves normalizing dataacross various business units within Informa, which has grown through multipleacquisitions. "Unlocking all of that data so it becomes usable is agigantic lift," she noted, pointing out the complexities of integratingdifferent tech stacks and processes. With multiple instances of Salesforce andvarious other systems in play, Denise's mission is to create consistency in howdata is managed and utilized across the organization.
One of the key strategies Denise employs is buildingdashboards that tell a story with the data. "If you help them understandhow to use the data, particularly by building dashboards and telling the storyfor them, you get a whole lot more user adoption," she said. This approachnot only enhances efficiency but also empowers sales teams to leverage dataeffectively. By providing clear visualizations and actionable insights, salesprofessionals can make informed decisions that drive growth.
Denise also discussed the importance of understanding thetalent within the sales teams. By utilizing a talent assessment tool, she andher team were able to match individuals' instinctive behaviors with their jobfunctions. "We could see how well someone’s natural affinity aligned withtheir performance data," she explained. This dual approach allowed them toidentify the right people for the right roles, optimizing the overalleffectiveness of the sales organization.
In her efforts to streamline processes, Denise tackled thechallenge of excessive pipeline stages within the sales framework. "Wewent from 70 pipeline stages to just 7," she shared, illustrating hercommitment to simplifying operations. By focusing on the essential elements ofthe sales process, she was able to create a more efficient system that enhancesforecasting and reporting capabilities.
Denise's insights extend beyond just data management; shealso emphasizes the importance of fostering a culture of collaboration andopen-mindedness. "You have to be very patient and learn from the youngergeneration," she advised, acknowledging the diverse work styles andphilosophies present in today’s workforce. By encouraging mentorship andknowledge sharing, Denise aims to bridge the gap between different generationsand create a cohesive team dynamic.
In conclusion, Denise Medved's insights on data and sales underscorethe transformative power of data-driven strategies in today's businessenvironment. Her expertise serves as a guiding light for organizations lookingto harness the full potential of data to drive revenue growth. As she aptly putit, "Understanding how to leverage data is key to driving salessuccess." With leaders like Denise at the forefront, the future of salesis undoubtedly data-driven and poised for growth.
Revenue Room Connect, an initiative by H2K Labs, is a platform that brings together industry leaders to share knowledge and insights about data, digital, AI, and revenue strategies in the B2B media and events space. Nino Tasca's decision to join the Executive Advisory Board of Revenue Room Connect reflects his commitment to knowledge sharing and networking within the industry. As a board member, Tasca brings his unique blend of experience from both Google and traditional B2B media companies, offering valuable perspectives on data transformation and AI integration. The platform provides an opportunity for executives like Tasca to engage with other curious and innovative minds, fostering an environment of mutual learning and growth. Through initiatives like RevvedUP and Lunch Lab events, Revenue Room Connect aims to drive discussions and strategies that can help B2B media companies navigate the evolving landscape of data-driven business models and revenue acceleration.
For me, engagement matters these days more than ever. It's not just about impressions and getting lots out. It’s about how meaningful is what we sent you and are you finding value in what we're providing?
In a recent episode of The Revenue Room™ podcast, host Heather Holst-Knudsen sat down with Liz Irving, President of Clarion Events North America, for an insightful discussion on data-driven strategies and digital innovation in the events industry, which is undergoing a significant transformation in how it measures success and drives growth. Irving shared her valuable insights on this evolution during her interview.
Liz Irving, with over 25 years of experience in the events industry, has been instrumental in guiding Clarion Events from a small team of 16 to a thriving organization with over 270 employees. Under her leadership, Clarion Events has embraced data-driven decision-making and customer-centric approaches to drive growth and innovation.
During the interview, Irving shared her perspectives on the evolving landscape of the events industry, the importance of digital revenue streams, and the role of AI in shaping future experiences. She also discussed Clarion Event's innovative strategies for leveraging data to enhance customer experiences and create new revenue opportunities.
Liz Irving is part of the upcoming RevvedUP conference, taking place February 25-27 at the Art Ovation Hotel in Sarasota, Florida. This gathering brings together CEOs and their revenue-critical C-suite teams to explore data-enabled enterprise value creation and business transformation.
In our conversation, Irving highlighted that the industry has moved beyond traditional metrics like square footage. Instead, there's a growing emphasis on more customer-centric measurements:
- Lifetime customer value
- Number of people per logo
- Levels of engagement
She emphasized the critical role of data in shaping business strategies and improving customer experiences. At Clarion Events, data analytics is used to understand customer needs, optimize event experiences, and measure success. This approach has led to more personalized and effective events, driving revenue growth and customer satisfaction.
One of the key innovations at Clarion Events is the development of a Needs Purpose Value (NPV) model to analyze customer responses and tailor experiences accordingly. The company also conducts pulse surveys throughout the customer journey to gather real-time feedback and make immediate improvements. Irving highlighted the use of Power BI for data visualization, which has enhanced their ability to track engagement and conversion rates, enabling more informed decision-making.
To implement these data-driven strategies effectively, Irving shared some key approaches:
• Building a dedicated team focused on digital product and strategy
• Developing the NPV model to understand and respond to customer needs
• Conducting pulse surveys throughout the customer journey
• Utilizing Power BI for data visualization and insights
• Restructuring the marketing team into digital and brand-focused groups
The critical importance of digital engagement in today's events industry is recognized by Irving, "For me, engagement matters these days more than ever. It's not just about impressions and getting lots out. It's about how meaningful is what we sent you and are you finding value in what we're providing?" This perspective underscores a shift from traditional metrics to a more nuanced understanding of audience interaction and satisfaction.
Clarion Event's approach to digital engagement goes beyond simply offering online components to their events. They've developed bespoke programs that guide customers through the marketing funnel, starting with broad digital touchpoints and ultimately leading to face-to-face interactions at events. This strategy allows Clarion Event to maintain a year-round presence in the communities they serve, rather than just connecting with customers during annual events.
The COVID-19 pandemic further accelerated Clarion Event's digital transformation efforts. Irving shared an example from their firefighter event, where they launched a learning management software for online training when in-person events weren't possible. This digital innovation not only allowed them to continue serving their community during a critical time but also created a new, subscription-based revenue stream, illustrating how Clarion Event is leveraging digital engagement to diversify their offerings and create value for their customers beyond traditional event formats.
We also touched on the digital transformation sweeping the events industry. Clarion Events has invested in mobile apps, online learning platforms, and AI-powered tools to enhance attendee experiences and provide year-round engagement opportunities. A notable example is the learning management software developed for the FDIC Firefighter show during the COVID-19 pandemic, which allowed Clarion Event to continue providing critical training to firefighters when in-person events were not possible.
The value of strategic partnerships with technology providers and the adoption of new technologies like AI and facial analysis to improve event experiences and gather customer insights cannot be overlooked. In one innovative example, Clarion Events is working with Zenith to use ethical facial analysis technology to assess customer sentiment and optimize event layouts and product placements.
It’s not enough to add in technology. The business operational structure itself needs to be assessed and reworked to allow the new strategies to flourish. She shared details on how Clarion Events restructured its marketing team to better address changing market needs. The company split its marketing function into two specialized groups: digital marketers focused on all things digital and data, and brand marketers who drive customer insights and brand strategies. This restructuring has allowed Clarion Events to accelerate both digital innovation and brand development while supporting each other and the customer.
The customer-centric approach at Clarion Events has led to innovations like bespoke events for specific customer segments. For instance, they created a specialized program for metro fire chiefs at the FDIC Firefighter show, based on data from their mobile app and direct customer engagement.
As the events industry evolves, there's an increasing focus on yield management, particularly in sponsorships. Irving noted that they're no longer just selling booth space but offering more complex sponsorship opportunities. This shift requires a deeper understanding of:
- The yield of various sponsorship types
- The costs associated with delivering these sponsorships
This focus on yield management is part of a broader trend of "rewriting the rulebook" for how events are sold, marketed, and delivered.
When asked about the challenges of implementing a data-driven strategy, Irving acknowledged the complexity: "We capture data in so many ways, right? We capture behavior, we capture what people tell us. And we're like, Oh my gosh, we have so much. It's, what do you do with it? How do you make it usable?" She emphasized the importance of narrowing your focus: "For me, it was about getting clearer on what matters. "
Irving also discussed the role of digital solutions in the events industry: "Digital is super important, right? I think it, as a whole, strengthens what the in-person brings. And when I step back and think about who we are as digital, we are actually a data company. That means we have the ability to help connect you with the people that really matter to you."
She went deeper into the aforementioned example of fire chiefs, and how data-driven insights led to innovation: "We created a whole bespoke program for them [metro fire chiefs]. That allowed them to learn and educate at that level of a metro chief officer. We brought in sponsorships to connect them. We understood their individual needs and help match them up with people who would be like minded for them to discuss challenges and opportunities."
Overall, this episode of The Revenue Room™ podcast with Liz Irving offers valuable insights into the evolving landscape of the events industry. Irving's journey from marketing to leadership, her emphasis on data-driven decision-making, and Clarion Event's innovative approaches to customer engagement and digital transformation provide a roadmap for success in the modern events sector. You’ll glean insights to help your business from her candid discussion of challenges, from implementing data strategies to restructuring teams, offers practical advice for industry leaders.
As the events industry continues to evolve, Irving's insights and Clarion's strategies serve as a beacon for others looking to navigate this dynamic landscape successfully.
Listen to the full podcast to hear all the insights from Liz Irving of Clarion Events. And of course, join Liz and other industry leaders at RevvedUP at the Art Ovation Hotel in Sarasota on February 25-27, 2025. RevvedUP 2025 is your pit stop for premium networking, cutting-edge insights, and practical strategies that'll put you ahead of the curve. Fuel your enterprise growth with data and AI-driven strategies, and position your organization for success.
Join us to network with Liz Irving and other industry leaders: Learn more here.
"It's not about getting a model that performs 0.5 percent better in certain use cases. It's actually about using data and AI to help our core fundamentals.” - Nino Tasca, Chief Product Officer, Northstar Travel Group
Nino Tasca, Chief Product Officer at Northstar Travel Group, is spearheading a data transformation that's reshaping the landscape of B2B media in the travel industry. With a background that includes a decade at Google and extensive experience in media technology, Tasca brings a unique perspective to the challenges and opportunities facing B2B media companies today.
At Northstar Travel Group, data is not just a buzzword—it's the cornerstone of their strategy. Tasca emphasizes a 70-20-10 approach to prioritize the company's efforts in data and technology initiatives:- 70% of resources are focused on core business needs and improving existing products
- 20% is allocated to future-oriented experimentation and innovation
- 10% is dedicated to employee skill development in AI and data
This structured approach allows Northstar to leverage data effectively while maintaining a balance between immediate business needs, innovation, and workforce development. "We're spending 70 percent of our effort focusing on this core need and how do we actually prove the value that Northstar provides through data," Tasca explains.
The company is building a comprehensive data warehouse to support its full suite of products, aiming to enhance user experiences and provide more value to advertisers. This data-first initiative is driving improvements across all aspects of the business, from event planning to digital content delivery.
Nino Tasca will be sharing his insights on data-driven strategies at RevvedUP, taking place February 25-27 at the Art Ovation Hotel in Sarasota. This exclusive event brings together C-suite executives from media, events, and marketplace industries to explore how data and AI-driven strategies can fuel enterprise growth. Tasca's experience in implementing data transformation at Northstar Travel Group will provide valuable perspectives for attendees looking to leverage data for business success in their own organizations. Learn more here.
While AI is a hot topic, Northstar's approach is pragmatic and focused on tangible results. Tasca notes, "We're experimenting with different products that can be data and AI first, more generative... integrating AI into these tools to create a better and new experience.”
Some key areas where AI is making an impact include:1. Content optimization: AI-powered tools suggest headlines and topics based on current trends and user engagement data.
2. Personalization: Tailoring content and recommendations for individual users across Northstar's digital platforms.
3. Event planning: Using AI to match attendees with relevant sessions and networking opportunities.
However, Tasca cautions against getting caught up in AI hype. "It's not about getting a model that performs 0.5 percent better in certain use cases. It's actually about using data and AI to help our core fundamentals," he emphasizes.
One of the most significant challenges—and opportunities—in B2B media is proving the value of advertising to clients. Northstar is tackling this head-on with innovative approaches to measurement and ROI tracking.
Tasca highlights the disparity in marketing spend: "Travel professionals influence as much as 45 percent of the spend of a 3 trillion market... but the marketing dollars that go into travel professionals budgets is a fraction, like 2 percent." This discrepancy underscores the potential for growth if B2B media companies can effectively demonstrate their value.
Northstar is developing multi-faceted measurement strategies:1. Transactional data partnerships: Working with industry partners to track actual bookings resulting from advertising exposure.
2. Survey-based approaches: Similar to Brand Lift studies used in consumer advertising.
3. RFP tracking platforms: Creating tools for meeting planners to submit RFPs, allowing for direct attribution of business generated through Northstar's events and content.
"The mandate of proving the measurement as low to the bottom of the funnel as we can get remains to be true," Tasca states. This focus on concrete, revenue-based metrics is crucial for demonstrating the true value of B2B media advertising.
Tasca's experience at Google has provided valuable insights for his role at Northstar, but he emphasizes the need for a different approach in B2B media:
1. Faster execution: Unlike Google, who can take their time on execution given their massive revenue, B2B media companies like Northstar need to move quickly and get products to market faster. Tasca admits, "If I could start my time again at Northstar, I'd be more aggressive and try to get things done faster."
2. Focused investments: While Google can afford to make multiple bets, B2B media companies must be more strategic in their investments, focusing on core business needs. Tasca explains, "At Northstar, we don't have the ability to do that. So we have to be more mindful about how we're making investments."
3. Revenue focus: As a private equity-owned company, Northstar prioritizes revenue growth, meeting quarterly and annual objectives. This contrasts with Google's ability to prioritize getting things right over getting them fast due to its substantial revenue cushion.
As Northstar continues its data transformation journey, Tasca identifies key roles and skills needed:
1. Data scientists: To build models and derive insights from collected data.
2. UX professionals: To ensure data-driven products are user-friendly and intuitive.
3. Sales team evolution: Training existing sales teams and bringing in new talent with digital, data, and AI selling skills.
Tasca's approach, blending Silicon Valley innovation with B2B media expertise, offers valuable insights for other companies navigating similar transformations. By focusing on core business needs, embracing AI judiciously, and developing robust measurement strategies, B2B media companies can unlock new value for their clients and audiences alike.
As the industry continues to evolve, events like RevvedUP and initiatives like Revenue Room Connect provide platforms for knowledge sharing and networking among industry leaders. Tasca's involvement in these initiatives underscores the importance of collaboration and continuous learning in driving innovation in B2B media.
Northstar Travel Group's data transformation journey, led by Nino Tasca, exemplifies the potential for B2B media companies to leverage data and AI in meaningful ways. By focusing on core business needs, developing innovative measurement strategies, and adapting lessons from tech giants to the B2B context, Northstar is positioning itself at the forefront of the industry's digital evolution.
"Hollowing out the ecosystem is not going to work in the long-term."
Lucky Gunasekara, CEO of Miso.ai, is leading the charge in transforming how media companies leverage artificial intelligence. Miso.ai is an AI media lab that focuses on news media, publishing, and online education.
I recently spoke with Lucky on The Revenue Room ™ podcast, and he shared his vision for Miso, and how AI can be effectively used by publishers.
"We're pretty narrowly focused these days on news media, publishing and online education," Lucky explains. "We have these AI building block models that publishers can unlock very quickly, often overnight for like personalized search or AI search or real-time recommendations or discovery that's personalized or first party data or native advertising."
With a presence on about 100 sites globally and billions of API calls processed, Miso’s AI's mission is clear: to put more money into media than they take out, recognizing the critical role of journalism in society.
Miso's partnerships with notable clients such as Foundry and O'Reilly Media showcase the practical applications of their technology. Their flagship product, "Answers," offers AI-powered search capabilities for websites like Macworld.com and CIO.com. What sets Miso apart is their unique approach to user engagement.
Lucky elaborates, "We embed in every article questions that are based on the context of the article and further commentary in the adjacent articles. What we have found is that these questions, which we call “explore questions”, they are just extremely effective at driving engagement."
This innovative approach not only enhances user experience but also opens up new avenues for revenue generation. Miso integrates native affiliate ads and relevant white papers into their answers, creating a seamless blend of information and monetization opportunities.
"If the answer on macworld.com is talking about the Apple Watch Ultra 2, the lowest price to get the Apple Watch Ultra 2 is right there, through different affiliate partners. On CIO.com, you might ask a question about generative AI and cybersecurity, and we'll present the answer, again, strictly from the title and the network of sibling sites that you're on, but we'll also show a white paper from a partner discussing cybersecurity and gen AI."
The implementation of Miso’s solutions has led to significant improvements in key performance indicators for their clients, such as site registrations. Lucky reports, "We've seen 2X registrations through this funnel. And then the direct attribution subs lift that we've seen is about 10 percent right now". The engagement with native advertising has been particularly remarkable, with Lucky stating, "We've seen 10 to 25 times higher click through rates than display."
These impressive metrics underscore the potential of AI-powered solutions to not only enhance user engagement but also drive tangible business results for publishers. The impact extends beyond just click-through rates, as Miso's solutions are driving registrations and subscriptions for their clients.
Given the significant revenue impact of AI solutions in the media industry, Lucky will be sharing more insights on this topic at our upcoming RevvedUP conference. RevvedUP, focusing on revenue generation and enterprise growth, is an exclusive event for C-suite executives in media, events, and marketplace industries. RevvedUP will be held from February 25-27 at the Art Ovation Hotel in Sarasota, providing an ideal platform for industry leaders to explore innovative strategies for leveraging AI to boost revenue and drive business growth. Learn more here.
As AI continues to reshape the media landscape, Lucky strongly emphasizes the importance of fairly compensating publishers for their content used in AI systems. He criticizes the current approach of many AI companies, stating, "Hollowing out the ecosystem is not going to work in the long-term."
This stance reflects a growing concern in the industry about the sustainability of current AI practices and their impact on content creators. Lucky advocates for a more balanced relationship between tech companies and media publishers, suggesting the need for an "iTunes-like" solution for AI and publishing, with fair revenue sharing.
In response to these challenges, Miso has collaborated with O'Reilly Media to develop a groundbreaking model where creators receive royalties for AI-generated answers using their content. Lucky explains, "We built out a forensic model because of the way that we're set up, you know, we're by default able to, when we take in a question, have a data trail of which titles do we consider, which snippets did we look at?"
This innovative approach not only ensures fair compensation for content creators but also sets a new standard for ethical AI practices in the publishing industry. It demonstrates that it's possible to harness the power of AI while maintaining a sustainable ecosystem for content creation.
Looking ahead, Lucky envisions a more symbiotic relationship between AI companies and publishers. He suggests,
"The market and the world just needs a more transparent and equitable framework for getting AI answers out to the public at scale from trustworthy sources and in a way that drives high rev share, and credit and attribution to sources."
This vision extends beyond mere financial considerations, touching on the broader role of media in society. Lucky emphasizes the importance of maintaining a robust and diverse media landscape, capable of driving social progress and cultural change.
The current landscape of media, AI, and tech is at a critical juncture. Lucky expresses concern about the present state of AI and publishing relationships, highlighting the need for a more equitable and sustainable model. The rapid advancement of AI technology has created both opportunities and challenges for the publishing industry.
Currently, there's a significant imbalance in how AI companies are utilizing content from publishers without adequate compensation or attribution. This situation echoes past disruptions in the media industry, such as the early days of search engines and digital music distribution.
The media and publishing sectors are facing a crucial moment where they need to assert their value and negotiate fair terms with tech companies. There's a growing recognition that quality content is essential for AI systems to function effectively, yet the current models often fail to reflect this in terms of revenue sharing or proper attribution.
As the industry moves forward, there's an urgent need for innovative solutions that can bridge the gap between AI capabilities and fair compensation for content creators. The current "deal, no deal, or deal with it" approach is unsustainable in the long term and risks eroding the quality and diversity of content available to consumers.
The challenge ahead lies in creating a more balanced ecosystem where both tech companies and media publishers can thrive, ensuring that the value of quality journalism and content creation is properly recognized and rewarded in the AI-driven future.
"The ability to understand not just who the audience is but also what they care about—and, just as importantly, what they don’t care about—allows us to deliver content that is both timely and impactful.” - Jane Qin Medeiros, SVP/GM, Industry Dive
In the rapidly evolving landscape of B2B media, staying ahead requires more than just producing great content; it demands a sophisticated understanding of audience behavior, the strategic use of data, and the cautious integration of emerging technologies like AI. Industry Dive, a leading B2B digital media company, has successfully positioned itself at the forefront of this transformation by combining niche audience insights with cutting-edge content marketing strategies. I spoke with Jane Qin Medeiros, General Manager at Industry Dive and studioID, to explore the strategies and innovations that have propelled her company to significant industry success.
Industry Dive’s core strategy centers on building and nurturing niche B2B audiences. By focusing on specific verticals such as construction, banking, and healthcare, the company has cultivated a loyal readership that trusts its high-quality journalism. These niche audiences are not just passive consumers; they are actively engaged professionals seeking valuable insights to help them make informed decisions in their respective industries.
What sets Industry Dive apart is its deep understanding of these audiences. The company doesn’t just collect basic demographic data; it gathers detailed information on content preferences, engagement patterns, and even the topics that no longer resonate with readers. This real-time, first-party data allows Industry Dive to continuously refine its content strategies, ensuring they stay relevant and valuable to their audience.
"The ability to understand not just who the audience is but also what they care about—and, just as importantly, what they don’t care about—allows us to deliver content that is both timely and impactful," Jane explained. "This data-driven approach helps in tailoring content to meet the specific needs of our audience, which in turn drives higher engagement and more meaningful interactions."
At the heart of Industry Dive’s content marketing success is studioID, its global content marketing services group. StudioID’s role is to create custom content for B2B marketers, leveraging Industry Dive’s deep audience insights to craft campaigns that align with the broader marketing journey—from brand awareness to lead conversion.
The genesis of studioID lies in the acquisition of NewsCred’s content studio, a move that perfectly aligned with Industry Dive’s strengths. On one hand, Industry Dive had the audience but lacked advanced content studio capabilities. On the other hand, NewsCred’s content studio had the expertise but lacked a substantial audience. The merger of these strengths has allowed studioID to thrive, creating a powerful synergy between audience data and content creation.
This synergy is evident in how studioID approaches content marketing. Rather than just producing content for the sake of it, studioID focuses on creating highly targeted campaigns that are designed to meet specific marketing goals. By integrating deep audience insights with content expertise, studioID ensures that every piece of content serves a strategic purpose, whether it’s building brand awareness, establishing thought leadership, or driving lead generation.
StudioID’s contribution to Industry Dive’s revenue is significant, accounting for 40% of the company’s total revenue. This success is largely due to a dual business model that balances scalable content campaigns with long-term, customized enterprise partnerships.
On one side, studioID runs thousands of content campaigns annually, producing assets like white papers and webinars that drive lead generation for clients. These campaigns are often the first touchpoint for clients, allowing studioID to demonstrate its capabilities and earn the trust needed to expand the relationship.
On the other side, studioID engages in deep, long-term partnerships with enterprise clients. These relationships are highly customized, involving strategic development, comprehensive content programs, and continuous optimization based on performance metrics. These partnerships are not just about delivering content; they involve working closely with clients to develop a full marketing strategy, build a measurement framework, and align all activities with the client’s business goals.
"Our approach is very much a 'land and expand' strategy," Jane said. "Initial content campaigns serve as a gateway to deeper engagement, allowing us to gradually scale up the relationship, offer more comprehensive services, and ultimately increase revenue."
This strategy also helps in building multi-threaded relationships within client organizations, ensuring that studioID becomes an integral part of their marketing strategy.
In today’s digital landscape, AI is often seen as a game-changer, but Industry Dive and studioID approach it with a balanced perspective. Rather than rushing to integrate AI across all content creation processes, they are carefully testing and evaluating its potential.
StudioID’s current focus is on using AI for tasks like content atomization—breaking down larger pieces of content into smaller, more digestible formats for various channels—and refining content through short-form copywriting and translation. However, the company remains cautious about using AI for original content creation, as current technology still lacks the nuance and depth that human expertise provides.
For Industry Dive, the real value of AI lies in its ability to process large amounts of data and generate insights that can inform business decisions. This includes optimizing operational processes, improving content distribution, and enhancing audience engagement strategies. By using AI to support these secondary tasks, studioID can increase efficiency without compromising the quality of the content.
"We don’t have to be first to market with every new technology," Jane noted, "but we do want to ensure that any technology we adopt supports our core values of quality, credibility, and audience engagement."
One of the biggest challenges in content marketing is proving ROI, especially when it comes to linking content efforts directly to revenue. StudioID addresses this challenge by establishing a clear measurement framework at the outset of each client partnership. This framework aligns content activities with specific business goals, such as brand building, content engagement, and lead generation.
The measurement framework includes a range of metrics tailored to the client’s objectives. For example, if the goal is to build brand awareness, the framework might include proxy metrics like content impressions and engagement rates. If the goal is lead generation, the focus might be on the number of marketing-qualified leads (MQLs) generated and their progression through the sales funnel.
However, studioID’s approach goes beyond just tracking metrics. The company’s sales and client services teams take a consultative approach, working closely with clients to interpret the data and optimize strategies. This might involve adjusting tactics, launching new initiatives, or refining the content strategy to better meet the client’s goals.
"By taking a holistic approach to ROI," Jane said, "we ensure that our content marketing efforts are not only effective but also clearly linked to the client’s broader business objectives. This transparency and alignment help build trust and pave the way for long-term partnerships."
As Industry Dive looks to the future, its core strategy remains focused on serving niche B2B audiences with high-quality, independent journalism. However, the tools and technologies used to achieve this goal are constantly evolving. The company’s emphasis on first-party data and opt-in audiences positions it well in an era of increasing privacy concerns and data regulations.
At the same time, Industry Dive is exploring new ways to integrate AI into its content creation and audience engagement strategies. The goal is not to replace human expertise but to enhance it, using AI to increase efficiency, optimize content distribution, and generate deeper insights into audience behavior.
The company’s partnership with its owner since 2022, Informa, further strengthens its position, providing additional resources and opportunities to scale its operations and expand its offerings. As Industry Dive continues to grow, its commitment to innovation, data-driven insights, and quality content will remain at the heart of its strategy.
In an industry where change is the only constant, Industry Dive and studioID offer a compelling model for success. By combining deep audience insights with strategic content marketing and a cautious approach to AI, they have built a business that not only drives revenue but also delivers real value to clients. As the digital media landscape continues to evolve, companies that can effectively leverage data, digital tools, and AI while maintaining a focus on quality and audience engagement will be best positioned to thrive.
In the competitive landscape of the B2B sector, having a well-structured Revenue Operating Plan (ROP) is not just beneficial; it is essential. A Revenue Operating Plan serves as the blueprint for systematic and efficient revenue generation, ensuring that every aspect of your business is aligned towards achieving financial success. This comprehensive guide will walk you through the critical steps of building a Revenue Operating Plan, focusing on the key elements of building, engaging, executing, delivering, expanding, and the continuous improvement cycle of rinse, lather, repeat. By the end of this blog, you will have a clear understanding of how to implement these strategies to enhance your business operations and drive sustainable growth.
The foundation of any successful Revenue Operating Plan lies in the ability to align your products with customer needs and market demands. This step is crucial as it ensures that your offerings are relevant and valuable to your target audience. To achieve this alignment, it is essential to conduct thorough market research and gather insights into customer preferences, pain points, and emerging trends. By understanding what your customers truly need, you can tailor your products to meet those demands effectively. Additionally, it is important to continuously monitor the market and adapt your offerings to stay ahead of the competition. This proactive approach will not only help you retain existing customers but also attract new ones by demonstrating your commitment to meeting their evolving needs.
Generating demand within your target segments is the next critical step in your Revenue Operating Plan. This involves creating awareness and interest in your products or services among potential customers. To achieve this, it is essential to have a well-coordinated effort across marketing, business development, sales, and product teams. Each team plays a vital role in driving demand and ensuring that your message resonates with the target audience. Marketing efforts should focus on creating compelling content, running targeted campaigns, and leveraging digital channels to reach potential customers. Business development teams should work on identifying and nurturing leads, while sales teams should be equipped with the right tools and training to convert those leads into customers. Product teams, on the other hand, should ensure that the offerings are aligned with the market needs and provide the necessary support to the sales and marketing teams. This cross-functional alignment is crucial for pipeline development and acceleration, ultimately leading to increased revenue generation.
Optimizing pipeline management is essential for ensuring predictable sales closures and achieving your revenue targets. This involves having a clear and efficient process for managing leads, opportunities, and deals throughout the sales cycle. One of the key aspects of pipeline management is the use of data analytics to identify risks and seize opportunities. By analyzing data from various sources, you can gain valuable insights into the performance of your sales pipeline and make informed decisions to improve it. Additionally, enabling sales leaders to provide real-time coaching and deal guidance is crucial for maximizing the effectiveness of your sales team. This can be achieved through regular training sessions, performance reviews, and the use of advanced sales tools and technologies. By optimizing your pipeline management, you can ensure that your sales efforts are focused on the right opportunities, leading to higher conversion rates and increased revenue.
Delivering value that exceeds customer expectations is a key component of a successful Revenue Operating Plan. This involves not only meeting the needs of your customers but also going above and beyond to provide exceptional value. To achieve this, it is important to use data to pinpoint product opportunities and address unmet needs. By analyzing customer feedback, usage patterns, and market trends, you can identify areas where your products can be improved or new features can be added to enhance the customer experience. Additionally, it is important to have a customer-centric approach in all aspects of your business, from product development to customer support. By consistently delivering value and exceeding customer expectations, you can build strong relationships with your customers, leading to increased loyalty and long-term revenue growth.
Retaining and enlarging your client base is essential for sustained revenue growth. This involves focusing on upselling and cross-selling within existing accounts to maximize the value of each customer. To achieve this, it is important to have a deep understanding of your customers' needs and preferences, as well as their usage patterns and buying behavior. By leveraging this information, you can identify opportunities to offer additional products or services that complement their existing purchases. Additionally, it is important to have a proactive approach to customer retention, which involves regularly engaging with your customers, addressing their concerns, and providing exceptional support. By focusing on retaining and expanding your client base, you can ensure a steady stream of revenue and drive long-term growth for your business.
The final step in building a successful Revenue Operating Plan is to continually refine and scale your processes using data-driven insights. This involves regularly reviewing and analyzing your performance metrics, identifying areas for improvement, and making necessary adjustments to your strategies and processes. By adopting a culture of continuous improvement and adaptation, you can ensure that your business remains agile and responsive to changing market conditions. This proactive approach will not only help you stay ahead of the competition but also drive sustained revenue growth. Additionally, it is important to leverage advanced technologies and tools to streamline your processes and enhance your decision-making capabilities. By continually refining and scaling your processes, you can ensure that your Revenue Operating Plan remains effective and aligned with your business goals.
In conclusion, building a robust Revenue Operating Plan is essential for achieving success in the B2B sector. By following the key steps of building, engaging, executing, delivering, expanding, and continuously refining your processes, you can create a systematic and efficient approach to revenue generation. Each of these steps plays a crucial role in ensuring that your business is aligned towards achieving its financial goals and driving sustainable growth. By implementing these strategies, you can enhance your business operations, exceed customer expectations, and achieve long-term success. So, take the first step today and start building your Revenue Operating Plan to unlock the full potential of your business.
Artificial Intelligence (AI) is no longer a futuristic concept confined to science fiction. It has permeated various industries, bringing about significant transformations. One such industry experiencing a paradigm shift due to AI is event management. From planning and execution to post-event analysis, AI technologies are revolutionizing how events are organized and managed. This blog delves into the myriad ways AI is changing the event management landscape, offering insights into its applications, benefits, and challenges.
One of the most immediate and impactful applications of AI in event management is providing real-time support to attendees. AI chatbots and virtual assistants are increasingly being deployed to handle a variety of tasks that traditionally required human intervention. These AI-powered tools can answer frequently asked questions, provide directions, and even offer personalized recommendations based on attendees' interests and behaviors.
Imagine attending a large conference and needing to find a specific session or locate the nearest restroom. Instead of searching through a map or asking a staff member, you could simply ask an AI chatbot on your smartphone. The chatbot, equipped with natural language processing capabilities, can understand your query and provide an accurate response in seconds. This not only enhances the attendee experience but also frees up human staff to focus on more complex tasks.
Moreover, AI can offer personalized recommendations by analyzing attendees' past behaviors and preferences. For instance, if an attendee has shown interest in certain topics or speakers in previous events, the AI can suggest similar sessions or networking opportunities. This level of personalization can significantly enhance attendee satisfaction and engagement.
Another groundbreaking application of AI in event management is real-time speech summarization. Conferences and seminars often feature multiple sessions running simultaneously, making it challenging for attendees to catch all the content they are interested in. AI can bridge this gap by providing real-time summaries and highlights of speeches or sessions.
Using technologies like natural language processing and speech recognition, AI can transcribe and summarize speeches in real-time. Attendees can receive concise summaries of sessions they missed or review key points from speeches they attended. This not only makes the content more accessible but also enhances knowledge retention and engagement.
For example, an AI-powered tool could analyze a keynote speech and generate a summary highlighting the main points, key statistics, and actionable insights. Attendees can access these summaries through a mobile app or event website, ensuring they stay informed and engaged throughout the event.
Security is a paramount concern for any event, and AI is playing a crucial role in enhancing safety measures. AI technologies like facial recognition and anomaly detection are being used to ensure secure environments for attendees.
Facial recognition technology can be employed at entry points to verify the identity of attendees, ensuring that only authorized individuals gain access. This not only speeds up the check-in process but also enhances security by preventing unauthorized entry. Additionally, AI-powered anomaly detection systems can monitor surveillance footage in real-time to identify suspicious activities or behaviors. These systems can alert security personnel to potential threats, enabling swift and effective responses.
For instance, an AI system could analyze video feeds from multiple cameras and detect unusual patterns, such as unattended bags or individuals loitering in restricted areas. By identifying these anomalies in real-time, security teams can take proactive measures to mitigate risks and ensure the safety of all attendees.
AI-driven analytics are transforming the way events are planned and executed. By leveraging predictive modeling and data analysis, AI can optimize various aspects of event planning, from layout design to schedule management and resource allocation.
Predictive modeling allows event organizers to anticipate attendee behaviors and preferences, enabling them to make data-driven decisions. For example, AI can analyze historical data from previous events to predict attendance patterns, helping organizers allocate resources more efficiently. This can include optimizing the placement of booths, scheduling sessions to avoid conflicts, and ensuring adequate staffing levels.
Moreover, AI can assist in designing event layouts that maximize attendee engagement and flow. By analyzing data on attendee movements and interactions, AI can suggest optimal booth placements, seating arrangements, and traffic flow patterns. This not only enhances the overall attendee experience but also increases the effectiveness of exhibitors and sponsors.
For instance, an AI-powered tool could analyze data from past events to identify high-traffic areas and suggest strategic booth placements for maximum visibility. This level of optimization can lead to more successful events, with higher attendee satisfaction and better ROI for exhibitors and sponsors.
The integration of AI in event management offers numerous benefits, including increased efficiency, enhanced security, and personalized attendee experiences. AI-powered tools can automate routine tasks, freeing up human staff to focus on more complex and strategic activities. This not only improves operational efficiency but also reduces costs and enhances the overall quality of events.
Personalization is another significant benefit of AI in event management. By analyzing attendee data, AI can offer tailored recommendations and experiences, increasing engagement and satisfaction. For example, AI can suggest sessions, networking opportunities, and even dining options based on attendees' preferences and behaviors.
However, the adoption of AI in event management also presents challenges. Privacy concerns are a major issue, as the use of AI often involves collecting and analyzing large amounts of personal data. Event organizers must ensure they have robust data handling protocols in place to protect attendees' privacy and comply with relevant regulations.
Additionally, the implementation of AI technologies requires significant investment in terms of time, money, and expertise. Event organizers must be prepared to invest in the necessary infrastructure and training to effectively integrate AI into their operations. There is also the challenge of ensuring that AI systems are reliable and accurate, as any errors or malfunctions could negatively impact the attendee experience.
AI is undoubtedly transforming the event management industry, offering innovative solutions that enhance efficiency, security, and attendee experiences. From AI-powered support and speech summarization to enhanced security and event planning optimization, the applications of AI in event management are vast and varied.
As AI technologies continue to evolve, we can expect even more groundbreaking innovations in the event management sector. Event organizers who embrace AI will be well-positioned to deliver exceptional experiences, drive engagement, and achieve their strategic objectives.
In conclusion, the integration of AI in event management is not just a trend but a significant shift that is reshaping the industry. By leveraging the power of AI, event organizers can create more efficient, secure, and personalized events that meet the evolving needs and expectations of attendees. The future of event management is undoubtedly bright, with AI leading the way.
Data has emerged as the new currency in today's rapidly evolving B2B media landscape, driving valuations and shaping acquisition strategies. As traditional revenue streams face increasing pressure, savvy companies leverage their data assets to create new value propositions and enhance their market position.
The days of relying solely on print advertising are long gone. And now, even digital-first strategies are seemingly “legacy” if they don’t come with a corresponding data strategy. Forward-thinking B2B information and marketing service companies (events, media, data/information, marketplaces) are pivoting towards data-first strategies that prioritize data collection, curation, analysis, and monetization.
This shift isn't just about survival; it's about thriving in a marketplace that demands more targeted, measurable, and actionable insights and where customers are increasingly expecting robust, personalized and relevant experiences that help them make data-driven decisions and execute smarter, faster, and better.
While subscriber numbers and event attendance figures remain important, they're no longer enough to drive premium valuations. Today's most valuable B2B media companies are those that have invested in robust first-party data strategies. This includes:
By combining these data points, companies can offer advertisers and sponsors much more than just eyeballs – they can provide access to highly qualified leads and predictive insights about purchasing decisions.
The landscape of B2B media is undergoing a dramatic transformation. The most successful companies in this space are moving beyond traditional display advertising to embrace performance-based models. This shift is not just a trend; it's a strategic imperative driven by advertisers' demand for measurable results and media companies' need for more predictable revenue streams.
In the evolving landscape of B2B media, data has emerged as a powerful standalone product, offering new revenue streams and strategic advantages. Forward-thinking companies are no longer viewing data as just a byproduct of their operations (or the dreaded word “exhaust”) but as a valuable asset that can be packaged, marketed, and sold independently.
FreightWaves has become a standout example of data monetization in the transportation and logistics sector.
FreightWaves has transformed from a media company into a data and analytics powerhouse. Their SONAR platform has become an essential tool for many logistics professionals, providing critical insights for decision-making in a volatile market.
By combining their industry expertise with cutting-edge data analytics, FreightWaves created a product that addresses a critical need in the logistics industry for real-time, actionable data.
GovTribe has successfully monetized government contracting data, filling a crucial information gap in the public sector marketplace.
GovTribe has become an essential resource for companies looking to navigate the complex world of government contracting. Their data products help businesses identify opportunities, assess competition, and make strategic decisions about pursuing government contracts.
By aggregating, cleaning, and analyzing publicly available government data, GovTribe created a high-value product that simplifies the government contracting process for businesses of all sizes.
Dodge Construction Network (formerly Dodge Data & Analytics) has long been a leader in construction industry intelligence.
Dodge's data products have become indispensable tools for construction companies, suppliers, and service providers. They help businesses identify opportunities, plan resources, and make strategic decisions based on market trends.
Dodge leveraged its long-standing industry presence and vast data collection to create products that provide actionable insights across the construction lifecycle, from planning to bidding to project execution.
As the market evolves, buyers and investors are placing an increasing premium on companies with strong data strategies. Key factors influencing valuations now include:
Companies that can demonstrate a clear data strategy and proven execution are likely to see significantly higher multiples compared to their less data-savvy peers.
For B2B media and event companies looking to maximize their enterprise value, investing in data capabilities is no longer optional – it's essential. This means:
As we enter 2025, the divide between data-rich and data-poor companies continues to widen. With AI taking center stage, those failing to adopt a sound data strategy will fall behind and in some cases, become obsolete. Certainly, their valuations will command nowhere near what their data-rich counterparts will. And, in some cases, many won’t ever make it to market. Embracing data's potential to fuel enterprise value is no longer optional to excel in an intensifying and intricate market landscape.
H2K Labs is a tech-enabled value creation specialist, the producer of The Revenue Room™ Podcast, curator of Revenue Room™ Connect, and producer of RevvedUP 2025 We help media, data/information, event, and marketplace businesses accelerate revenue, drive profitability, and fuel enterprise value using data, digital, and AI. We are an added-value reseller of data and AI solutions that are purpose-built for the industries we serve including Insightify and Channel Metrics.
In today's complex business landscape, understanding and leveraging enterprise value is crucial for sustainable growth.As I recently discussed in our new rapid learning format for C-Suite executives, LunchLab NYC, enterprise value goes far beyond just revenue and profitability. It encompasses customer retention, market positioning, operational efficiency, innovation, financial management, scalability, strategic partnerships, and risk management.
However, two critical elements underpin all these components: customer-centricity and data activation.
The statistics below underscore the significant impact of a customer-centric approach on a business's bottom line. This approach can drive enhanced profitability, increased customer lifetime value, and improved retention rates. It is evident that prioritizing customer experience and catering to customer needs can yield substantial business advantages.
When analyzing businesses that derive revenue from diverse sectors like media, events, and data/information, these statistics make a very compelling business case for investing in cultivating a customer-centric business model.
Profitability
Customer Lifetime Value (CLV):
Retention
Customer-centricity is not just a buzzword; it's a comprehensive approach that touches every aspect of your business. Here are key elements to consider:
Mindset
Deliver value in every customer interaction. This element is about adopting a customer-first mentality across your entire organization. It means viewing every touchpoint - from marketing emails to customer service calls - as an opportunity to provide value to the customer. For example, in marketing, aim for a 75/25 split: 75% of your communications should deliver valuable content to customers, while only 25% should be promotional. This approach builds trust and demonstrates your commitment to the customer's success, not just your bottom line.
Personalization and Relevance
Use data to understand and meet customer needs. True personalization goes beyond simply addressing a customer by name. It's about leveraging data to understand customer behaviors, preferences, and needs, then tailoring your offerings and communications accordingly. This could involve using predictive analytics to anticipate customer needs, or segmenting your audience for more targeted messaging. The key is relevance - providing customers with what they need, when they need it, based on data-driven insights.
Empathy
Provide holistic solutions by understanding customers' ultimate goals. Empathy in business means looking beyond your product or service to understand the broader context of your customer's challenges and objectives. It involves developing a deep understanding of your customer's industry, business model, and long-term goals. With this knowledge, you can position your offerings as part of a holistic solution that addresses their underlying needs, not just as a standalone product or service.
Relationship Focus
Prioritize customer retention over constant acquisition. While acquiring new customers is important, retaining and growing relationships with existing customers often provides a better return on investment. This approach involves viewing each customer relationship as a long-term partnership. Focus on customer lifecycle management, proactively addressing issues, and finding new ways to add value. This can increase customer loyalty, higher lifetime value, and more stable, predictable revenue.
Organizational Alignment
Ensure clear roles and responsibilities internally. internally Customer centricity requires every department to work in harmony towards the common goal of customer success. This means clearly defining roles and responsibilities, ensuring smooth handoffs between departments, and breaking down silos that might impede the customer experience. For instance, sales, marketing, and customer success teams should have aligned goals and regular communication to ensure a seamless customer journey.
Holistic Approach
Involve leadership in customer engagement. Customer centricity must be championed from the top down. When C-suite executives regularly engage with customers - through site visits, feedback sessions, or even tracking key customer metrics - it sends a powerful message about the company's priorities. This high-level engagement also provides valuable insights that can shape company strategy and ensure that customer needs remain at the forefront of decision-making.
Multi-sided businesses such as media, events, data/information, and marketplaces have unique challenges and addressing them requires a strategic approach anda clear understanding of all the unique dynamics. It often involves investing in robust technology solutions and complex tech and data stacks, fostering a culture of customer-centricity across the organization, and continuously refining processes based on stakeholder feedback and data insights.
Diverse Stakeholders: Balancing the needs of different customer groups
Multi-sided business models often serve multiple distinct customer groups simultaneously. For example, a trade show organizer must cater to exhibitors, attendees, and sponsors. Each group has different needs and expectations, which can sometimes conflict. The challenge lies in creating value for all parties without significantly compromising the experience of any one group. This requires careful planning, clear communication, and often creative solutions to ensure all stakeholders feel their needs are being met.
Competing Interests: Managing various programs and initiatives simultaneously
In multi-sided models, different initiatives often compete for resources and attention. For instance, at a conference, you might have booth exhibitions, conference sessions, and hosted buyer programs all running concurrently. Each of these needs to succeed for different stakeholders, but they may compete for attendee time and attention. The challenge is to structure these programs in a way that maximizes value for all parties, perhaps by careful scheduling, creating synergies between programs, or using data to optimize the overall experience.
Data Integration: Consolidating customer data from multiple systems and acquisitions
Multi-sided businesses often use numerous systems to manage different aspects of their operations - CRM systems, event management platforms, marketing automation tools, CDPs, ad management systems etc. Additionally, they may accumulate multiple systems serving similar functions through acquisitions or organic growth. The challenge is integrating data from all these sources to create a unified view of each customer. This is crucial for delivering personalized experiences and making informed business decisions, but it requires significant technical expertise and often substantial investment.
Internal Priorities: Aligning incentives and KPIs across departments
Different departments within a multi-sided business may have misaligned incentives that can undermine customer-centricity. For example, a marketing team might be incentivized to maximize event registrations, while sales teams are focused on sponsor satisfaction which is directly connected to attendee quality and engagement. This can lead to situations where quantitative goals are met (high attendance) but qualitative goals suffer (sponsor ROI). The challenge is to create a balanced scorecard of KPIs that encourages all departments to work towards overall customer satisfaction and business success.
Channel Diversification: Managing diverse revenue streams and contracts
Multi-sided businesses often have complex revenue models with multiple streams - subscriptions, advertising, sponsorships, ticket sales, etc. These may have different contract structures, revenue recognition rules, and customer success metrics. The challenge is to manage this complexity while still providing a cohesive and satisfying customer experience. This often requires sophisticated financial management and customer success strategies tailored to each revenue stream.
Compliance: Ensuring data governance and hygiene
The growing significance of data in advancing customer-centricity necessitates that multi-sided businesses navigate intricate data governance terrains. This involves adhering to regulations such as GDPR or CCPA, upholding data quality across diverse systems, and enforcing robust data security protocols. The complexity is amplified in multi-sided models due to the varied data types gathered from distinct stakeholder groups. Ensuring meticulous data hygiene and governance is imperative not just for regulatory adherence but also for upholding customer trust and facilitating efficient data-driven strategies. The intricacy is heightened in multi-sided models due to the diverse data collected from various stakeholder groups. Upholding meticulous data hygiene and governance is essential not only for regulatory conformity but also for fostering customer trust and empowering effective data-driven decision-making. Hygiene and governance play a pivotal role in generating the necessary insights to steer successful customer-centric approaches.
While the benefits of customer centricity are clear, implementing and maintaining this approach comes with its own set of challenges. Understanding and addressing these obstacles is crucial for organizations aiming to truly put the customer at the center of their operations.
Avoid "boiling the ocean" - focus on manageable, impactful initiatives
One common pitfall is trying to transform everything at once. This approach can lead to overwhelm and ineffective implementation. Instead, organizations should identify key touch points in the customer journey where improvements can have the most significant impact. Start with pilot projects that can demonstrate quick wins and build momentum. For example, focus on enhancing sponsor onboarding and post event engagement and upsell processes or improving response times in customer support before tackling larger, more complex initiatives.
Ensure consistency between claims and actions, starting from top leadership
Customer centricity must be more than just a slogan - it needs to be embedded in the company's culture and actions. This alignment starts at the top. Leadership must not only advocate for customer-centric practices but also embody them in their decision-making and interactions. Regular training and communication can help ensure that all employees understand and embrace the customer-centric approach. Customer-centric KPIs need to be part of dashboards and management meeting discussions. Consider implementing reward systems that recognize and incentivize customer-centric behaviors across all levels of the organization.
Balance customer focus with business profitability
While putting customers first is important, it shouldn't come at the expense of business sustainability. The challenge lies in finding the sweet spot where customer needs are met while maintaining profitability. This might involve making tough decisions, such as discontinuing unprofitable products or services that some customers love. The key is to communicate transparently with customers about such decisions and always strive to offer alternatives or solutions that still meet their needs.
Implement proper processes to support customer-centric initiatives
Customer centricity requires more than just good intentions - it needs to be supported by robust processes and systems. This includes:
Overcome data silos and privacy concerns:
In the age of data-driven decision making, breaking down data silos is crucial for gaining a 360-degree view of the customer. However, this must be balanced with increasing privacy concerns and regulations. Invest in secure, integrated data systems and ensure compliance with data protection laws. Be transparent with customers about how their data is used and give them control over their information.
By addressing these challenges head-on, organizations can create a truly customer-centric culture that not only meets customer needs but also drives business growth and success.
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H2K Labs is a tech-enabled value creation specialist, the host of The Revenue Room™ Podcast, curator of Revenue Room™ Connect, and producer of RevvedUP 2025 We help media, data/information, event, and marketplace businesses accelerate revenue, drive profitability, and fuel enterprise value using data, digital, and AI. We are an added-value reseller of data and AI solutions that are purpose-built for the industries we serve including Insightify and Channel Metrics.
In a recent episode of The Revenue Room™ Podcast, H2K Labs’ CEO, Heather Holst-Knudsen, interviewed Kate Spellman, Chief Commercial Officer at Questex, about the evolving landscape of B2B media and events. With her extensive experience in the industry, Kate shared valuable insights on how Questex is adapting to industry changes and driving growth.
Kate emphasized the critical role of data in Questex's operations, particularly in empowering their commercial team. By centralizing customer data in Salesforce, Questex has gained real-time visibility into their business performance. This shift has enabled more informed decision-making and faster responses to market changes.
“All of our customer data is now in Salesforce. That has made a huge difference because we are actually able to look at it, which we were not able to do when we wouldn't know what that month's rollup was until two months later.” Kate said.
Questex has also adopted Gong, an AI-powered conversation intelligence platform. Kate shared her surprise at Gong's effectiveness: "It will give you a probability of close, which I think is so interesting and such great learnings for someone like me, but it also helps us train new salespeople.
This AI-driven approach not only improves sales forecasting accuracy but also enhances the onboarding and training process for new sales team members.
Questex is also focusing on empowering their customers with data-driven insights. They're partnering with Channel Metrics to launch a unified end-to-end campaign and lead generation reporting tool that will provide customers with a unified dashboard of their marketing and event performance metrics. And, smartly, they are piloting Channel Metrics with their Telecom division before rolling out enterprise wide.
"The customer will actually have a dashboard that includes lead reporting, Google analytics, event reporting all in one dashboard. So it's not product by product, which is how we report today," Kate explained. This initiative aims to demonstrate clear ROI to clients while also opening up opportunities for upselling through audience scoring.
Kate didn't shy away from discussing the threats facing the B2B media and events industry. She highlighted concerns about the impact of AI on traditional search and advertising models, as well as the challenges of data sprawl and rapidly changing attendee expectations for events.
Despite these challenges, Kate remains optimistic about Questex's ability to adapt: "I think we just also have to stay very true to who we are... without getting distracted by the next big shiny penny."
Questex has successfully launched new events and products by leveraging data insights. For example, they launched The Hospitality Show based on observed audience interests. The Hospitality Show was one of Questex’s most successful launches across all KPIs bringing together over 3,800 attendees, 320 exhibitors, 100 industry-leading speakers, and revenues in the seven figure range in its first year (2023).
Kate was very excited about what she was able to take back to the office from participating in the inaugural Lunch Lab NYC event, a rapid learning program for C-suite executives produced by Revenue Room™ Connect, a new solution by H2K Labs. As a Revenue Room™ Connect Executive Advisory Board Member, Kate’s looking forward to the upcoming RevvedUP 2025 event, which will focus on fueling enterprise value by leveraging data, digital, and AI. RevvedUP 2025 takes place February 25-27 at The Art Ovation Hotel in Sarasota, FL.
Kate expressed her excitement about the event, stating, "What you're doing is truly imperative. I think to not only Questex, but to the industry ahead." (Thank you, Kate!)
Throughout the interview, Kate emphasized the need for B2B media companies to be agile, data-driven, and customer-centric. She highlighted Questex's success in beating revenue and EBITDA targets through double-digit growth while acknowledging the need for continuous adaptation to maintain this momentum.
As the B2B media landscape continues to evolve, leaders like Kate Spellman are at the forefront, navigating challenges and seizing opportunities. Her insights provide a valuable roadmap for others in the industry looking to drive growth and innovation in an increasingly complex and technology-driven environment.
Interested in hearing the full podcast? You can listen to the podcast on the channels listed below:
Apple:
https://podcasts.apple.com/us/podcast/the-revenue-room-with-kate-spellman-chief-customer/id1690675143?i=1000663015076
Spotify:
https://open.spotify.com/episode/4zKnXKmIhcKSfXG5km50F8?si=Uju357LpRuyGrk79VVVEHQ
YouTube:
https://www.youtube.com/watch?v=OvKztUvuIJQ
Other important links:
H2K Labs is a tech-enabled value creation specialist, the host of The Revenue Room™ Podcast, curator of Revenue Room™ Connect, and producer of RevvedUP 2025 We help media, data/information, and marketplace businesses accelerate revenue, drive profitability, and fuel enterprise value using data, digital, and AI. We are an added-value reseller of data and AI solutions that are purpose-built for the industries we serve including Insightify and Channel Metrics.
Many times, the gaps in revenue are not a function of the sales teams.
That’s a bold statement, so let it sink in for a minute.
However, we find that it's often a function of the process and data they have to go to market for acquiring, retaining, and expanding customers. That’s why we believe a data-driven revenue growth strategy is essential.
We call it The Revenue RoomTM.
The revenue room integrates the functions within an organization that are critical to revenue development, from sales to marketing to finance and more, to develop a comprehensive, targeted approach to aligning data, product, and revenue strategy. Data intelligence and alignment are keys to refining your sales process.
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Often, revenue intelligence data is collected, but it’s not being utilized for better decision-making. For example, there’s a misconception that everything useful about clients exists in the CRM. That’s simply not true, especially when you are doing sales forecasting and empowering your sales team. There’s a lot of data that sits outside your CRM that is crucial to how you sell.
Often, there is a disconnect with the data collected. The average company has 17 petabytes of data, and nearly 60% of that data is no longer being actively used or managed. It’s often scattered across different platforms, cloud providers, and third-party applications. It may be siloed in different departments or only exist in individual salespeople’s notes. Curating and blending the data into a single source of revenue truth are the keys to delivering on the most important KPIs.
Instead of churn, for example, a company might have strong retention, but they see their wallet share is not moving. That’s often an upsell expansion issue. It might be that sales teams aren’t focusing on upsell opportunities, or you may not have the right products to grow your share of business.
Regardless, understanding your most important KPIs and then tracking them consistently will help everyone stay focused on the key revenue drivers. However, this only works if you can capture all the data from your CRM and different sources with an easy way to visualize it.
Real-time reporting with a single source of revenue truth can empower you to:
A Forbes Insight analysis showed the power of this data in a unified view that impacts customer experience and sales success. Those surveyed reported these benefits:
Despite the obvious benefits, 87% of marketers say data is their most under-utilized asset. Seth Marrs, principal analyst at Forrester, put it this way: “Data visibility has been a missing link, preventing sales and marketing teams from aligning.”
First-party data is information you gather directly from your customers or prospects. The most common is tracking behavior on your website. When you see prospects who are reading articles, looking at products or services, or doing deep dives into solutions briefs or product specs, they are sending intent signals.
Leveraging first-party data is powerful. Let’s say someone keeps coming back to articles about supply chain optimization. You have newsletters focused on the supply chain, an event coming up about optimization, and an active supply chain community. You will want to get that prospect engaged with each of these touch points and provide relevant messaging for this prospect.
With the right data in hand, you can personalize messaging, and it’s critical to do so. A McKinsey study shows that 71% of consumers expect personalization, and 76% are frustrated when it doesn’t happen.
However, personalization is just part of the equation. Success comes from personalization plus relevancy. If the content is relevant, no amount of personalization will matter.
One of the biggest reasons for customer churn is what we call “Your Own Dang Fault” — failing to control program performance that is within your ability to do so. A salesperson might sign a broad-ranging deal with multiple layers. The client is happy, and the salesperson has done their job. But… when it gets to the service delivery team, they struggle to figure out exactly what was sold.
So, they try to deploy programs that deliver on expectations — but may fall short.
If you are using data to assess your programs, you can diagnose when you have an over exuberant salesperson who is selling products that lead to customer dissatisfaction or programs that aren’t meeting client objectives. You can then coach up that salesperson to help them sell the right product mix that meets customer goals.
The digital information you have is important to prove the case to the salesperson, who may need persuading to change their approach.
On the other hand, maybe the salesperson did sell the exact right product mix. You have the data to back it up, so you can go to the customer success team and ensure they deliver on the promises. Tracking these metrics against the goals will show whether you are hitting the targets. If not, you need to pivot and re-assess. This improves the overall customer experience.
In sales, you need every possible edge to build sustainable growth. McKinsey research shows that the top performers generate about 2.6 times the sales ROI of poor performers, driving profitability. Equipping your team with the right tools and the comprehensive data they need can help you join the ranks of top performers to scale your revenue.
H2K Labs empowers midsize B2B companies to scale and excel through data. We focus on data strategy, revenue strategy, and product strategy — leveraging cutting-edge data intelligence cloud designed to fuel top and bottom-line growth.
Contact H2K Labs today to discuss how a comprehensive data, revenue, and product strategy can deliver on your revenue goals.
“You find your target, you find your niche, and that's what you obsess with. And that's what we do. We are obsessed with people who want to spend money on their home.”
Thomas Bohn, President and COO, THM Media
In the rapidly changing landscape of media and advertising, TheHomeMag™ stands out as a pioneer in transforming traditional print media into a dynamic, multi-platform powerhouse. Under the leadership of Thomas Bohn, President and COO, TheHomeMag™ has undergone significant rebranding and restructuring, now operating under Advanced Home Improvement Media. This transformation reflects the company’s broader vision to encompass a variety of brands and expand its influence beyond traditional print.
Founded over two decades ago by Sean and Debbie Campbell, TheHomeMag™ began as a modest publication in Fort Myers and Cape Coral, Florida. Inspired by a similar business in South Africa, the Campbells sailed to the U.S. and started what would become a media sensation in the home improvement industry. Their vision was clear: to create a lasting and profitable business. Today, TheHomeMag™ operates in 68 markets, with a balanced mix of franchise and corporate-owned entities, demonstrating the resilience and scalability of their business model.
Under Tom’s leadership, TheHomeMag™ has undergone a significant transformation, evolving from a primarily print-focused publication to a cutting-edge, multimedia, tech-enabled powerhouse in the home improvement industry. His leadership philosophy at TheHomeMag™ is profoundly captured in a statement from his biography: "Tom envisions what he wants to accomplish and then finds the means to attain it." This approach is evident in how he has steered the company through significant transformations. Upon joining the company, Tom embraced the foundational visions of founder Sean Campbell and immediately set about crafting a detailed and actionable roadmap for the future. He set a new narrative focusing on expansive capabilities beyond traditional print, emphasizing the critical role of data and artificial intelligence. These tools not only enhance the company's offerings but also redefine how they engage with customers and advertisers.
Tom’s strategy centers on mobilizing a talented team, empowering them with the autonomy and tools necessary to innovate and execute effectively. This commitment to vision and practical implementation has led to impressive results, including a dramatic transition to a robust multimedia enterprise. Under his visionary yet pragmatic approach, TheHomeMag™ has not only enhanced its market position but also fostered a positive corporate culture, significantly boosting employee motivation and satisfaction. This was recently highlighted when TheHomeMag™ scored exceptionally high in an Inc 500 survey, ranking it among the best places to work—a direct reflection of Tom’s ethos of "clearing the path" —a philosophy rooted in making the connection between homeowners and service providers seamless and effective, leveraging both quality content and innovative technology. This strategy has enabled TheHomeMag™ to leapfrog competitors and position itself as a leader in a highly competitive market.
TheHomeMag’s™ data-centric approach is reshaping the way it connects with its audience and drives business innovation. By leveraging comprehensive data analysis and partnerships with market research firms like MRI, TheHomeMag™ has gained profound insights into its readership’s behavior and preferences. This strategic emphasis on data not only enhances content relevancy but also boosts reader engagement significantly, as evidenced by the fact that their readers are far more likely to undertake home improvement projects shortly after engaging with the magazine.
This deep understanding of their audience enables TheHomeMag™ to tailor its offerings precisely to meet their needs while also creating targeted advertising opportunities that benefit advertisers. By maintaining a firm commitment to ethical data use, TheHomeMag™ builds trust and reliability among its customers, distinguishing itself in a market where consumer data handling is often a contentious issue.
Moreover, this data-driven strategy supports Tom’s exploration of new business avenues, such as fintech solutions that facilitate easier project financing for homeowners. Initiatives like the proposed HomeMag DreamCard illustrate how TheHomeMag™ uses data not only to inform content and marketing strategies but also to enhance the practical aspects of customer project implementation, enriching the overall customer experience and ensuring that TheHomeMag™ remains at the forefront of the home improvement media industry.
At TheHomeMag™, the strategic vision for an integrated media portfolio that caters effectively to both audiences and advertisers has led to the development of innovative digital solutions, notably the introduction of a robust email marketing platform. Under Tom’s leadership, the company has achieved impressive penetration and open rates for its email campaigns, significantly outperforming industry averages. This success is a testament to the quality and efficacy of their digital strategies, which focus on delivering premium content directly relevant to their users' interests.
Building on this success, TheHomeMag™ is pushing the boundaries further by integrating artificial intelligence into their services. A prime example is "Ask Home-y™," an AI-driven platform designed to enhance the home improvement experience for homeowners. Unlike conventional directories, Ask Home-y™ offers a dynamic, interactive experience, allowing users to engage in conversations about their home improvement needs and receive personalized suggestions. This AI initiative is not just about technological innovation; it’s about creating meaningful connections without compromising customer privacy, ensuring that interactions remain beneficial to both homeowners and advertisers alike. By focusing on connectivity over commodification, TheHomeMag™ is setting new standards in how media companies engage with their constituencies.
Before taking the helm at TheHomeMag™, Thomas amassed a rich history of leadership across various sectors, particularly in association and media management. His early career highlights include revitalizing the Oldsmar Chamber of Commerce, where he dramatically increased its scale and impact as its CEO right out of business school. Thomas’s adeptness at strategic disruption and transformation continued as he led multiple organizations through significant growth phases, skillfully navigating mergers and acquisitions and pioneering digital transitions. Notably, his tenure at the North American Veterinary Community (NAVC) saw him transforming the organization by expanding its media properties and digital training platforms, significantly increasing its reach and revenue. This blend of experiences crafted a solid foundation for his visionary work at TheHomeMag™, where he continues to drive innovation and growth.
TheHomeMag’s™ evolution from a traditional print publication to a leading multimedia company in the home improvement sector illustrates the power of visionary leadership combined with strategic innovation. As the company continues to grow and adapt, it remains committed to its roots of quality, community, and service, setting a benchmark for the industry and offering valuable insights into the future of media and home improvement.
In today’s digital age, the role of a Chief Financial Officer (CFO) extends far beyond traditional financial management. Data, often referred to as the new oil, has become a critical asset for organizations. As a CFO, understanding and leveraging data effectively can drive strategic decision-making, enhance operational efficiency, and create a competitive edge. Here’s a closer look at the pivotal role data plays in an organization from this CFO’s perspective.
Data-driven decision-making is at the core of modern business strategy. Accurate, timely, and relevant data allows CFOs to:
Optimizing operational processes is essential for sustaining growth and profitability. Data plays a crucial role in:
Maintaining accurate financial records and adhering to regulatory requirements is a fundamental responsibility of CFOs. Data supports these functions by:
Understanding customer behavior and preferences is key to driving revenue growth. Data analytics enable CFOs to:
In a competitive business landscape, data can provide a significant edge. CFOs can leverage data to:
I have worked in organizations that did not understand the role of data. I have seen sales, marketing and IT spend literally millions of dollars based on anecdotal evidence and not factual data. It was very frustrating to the C-suite when these projects failed and there was no return on investment (ROI).
As a CFO, harnessing the power of data is no longer optional—it’s imperative. Data drives strategic decision-making, enhances operational efficiency, ensures compliance, provides customer insights, and fosters competitive advantage. By leveraging data effectively, CFOs can not only safeguard the financial health of their organizations but also drive sustainable growth and innovation. Embracing a data-centric approach transforms the CFO role from a traditional financial steward to a strategic business leader.
Artificial Intelligence (AI) is rapidly changing the business landscape, offering new opportunities for growth, revenue generation, and customer engagement. By leveraging AI technologies, businesses can unlock the potential of their data and gain valuable insights that will drive strategic decision-making. From optimizing processes and workflows to enhancing customer experiences, AI can revolutionize business operations in today's digital age. In this blog post, we will explore the impact of AI on growth, revenue, and customer relationships and how businesses can harness the power of AI to drive success in a competitive market.
AI is pivotal in accelerating business growth by streamlining operations, improving efficiency, and identifying new revenue streams. Businesses that strategically implement AI solutions can experience significant expansion opportunities and competitive advantages. Through advanced analytics and machine learning algorithms, organizations can uncover hidden patterns in data, forecast trends, and optimize processes for increased productivity. As AI continues to evolve, businesses must adapt and innovate to stay ahead. In the next section, we will delve deeper into how AI influences revenue generation and ways to capitalize on AI to foster customer relationships for sustainable business growth.
According to PWC, AI tech can increase revenue by over $15 trillion in the next decade Some estimates suggest that AI technology could generate $15.7 trillion in revenue by 2030, boosting the GDP of local economies by an additional 26% (Tractica).
Implementing AI-driven strategies can profoundly impact a company's revenue generation capabilities. By leveraging AI technologies such as chatbots for customer service, personalized recommendations based on machine-learning algorithms, and predictive analytics for accurate demand forecasting, businesses can maximize sales opportunities and drive revenue growth. Utilizing AI to understand customer behaviors and preferences allows for targeted marketing campaigns and improved customer retention. Furthermore, AI-powered automation can streamline sales processes, enhance lead generation, and optimize pricing strategies for higher profit margins. The integration of AI into revenue-generating activities positions businesses for sustainable growth in today's competitive landscape.
In addition to boosting revenue and driving growth, AI technology plays a pivotal role in enhancing customer experiences. Forbes Advisor reports that “64% of business owners believe AI has the potential to improve customer relationships,” indicating a positive outlook on the role of AI in enhancing client interactions.
By analyzing vast amounts of data, AI can provide valuable insights into customer preferences, behavior patterns, and expectations. This enables businesses to offer personalized recommendations, tailored marketing campaigns, and seamless interactions through chatbots and virtual assistants. By leveraging AI-powered tools, companies can effectively engage with customers, address their needs promptly, and foster long-lasting relationships. The ability to deliver exceptional customer experiences through AI not only increases loyalty and satisfaction, but also differentiates a brand in a competitive market environment.
To fully leverage AI for sustainable growth, companies must meticulously develop and implement customized strategies. Implementing AI-driven solutions across various touch points can optimize operational efficiencies, enhance decision-making processes, and streamline customer interactions. As previously mentioned, integrating AI technologies into sales, marketing, and customer service functions allows organizations to further scale their operations, boost revenue streams, and nurture customer relationships effectively. Moreover, continuous monitoring and adaptation of AI strategies based on real-time insights are crucial for staying competitive and meeting evolving customer demands. In the upcoming sections, we will delve deeper into the practical steps and best practices for implementing AI strategies to drive sustainable business growth.
As companies embrace AI to drive growth and enhance the customers’ experiences, it's essential to navigate the potential challenges and risks that come with AI integration. From data privacy concerns to ethical considerations and algorithm bias, businesses must proactively address these issues to mitigate future concerns regarding AI, maintain their clientele’s trust, and ensure compliance. Implementing robust cybersecurity measures, fostering transparency in AI algorithms, and prioritizing data ethics are imperative steps towards attenuating risks and building a solid foundation for sustainable AI adoption.
The strategic integration of AI presents an unparalleled opportunity for companies to drive growth, boost revenue, and enhance customer experiences. By taking charge in addressing challenges such as data privacy, ethics, and bias, businesses can create a solid foundation for sustainable AI adoption. Prioritizing cybersecurity, fostering transparency, and upholding stringent data ethics are crucial steps towards maximizing the benefits of AI integration. As we navigate the evolving landscape of technology, embracing AI in your business strategy is key to staying competitive and meeting the increasing demands of the market.
On The Revenue Room ™ podcast, I spent some time with Amy Roman, CEO of AmplifyGTM, to learn her secrets to successfully building a customer centric organization.
Amy’s career in business and marketing has been both long and varied, giving her a unique perspective on the topic. She started in large consumer packaged goods companies, working in various sales and marketing roles. About ten years ago, she transitioned to the technology sector, running a branding and design agency and then taking over sales and marketing for an IT managed services provider, significantly growing the company and increasing its valuation by 50%. This success led her to found AmplifyGTM, where she now helps companies identify and implement the fastest paths to sustained revenue growth.
One of the most interesting aspects of our conversation was Amy’s perspective on the role of the Chief Revenue Officer (CRO). In her view, a CRO is critical because they oversee the entire front end of the business, including outside sales, inside sales, and marketing. This role is about delivering results and being responsible for revenue, ensuring that all elements work together seamlessly to drive growth.
There is some controversy surrounding the CRO role, often viewed as a glorified VP of Sales. However, a true CRO integrates sales, marketing, and customer success to optimize the entire value chain of acquiring, retaining, and growing customers. Amy views having direct sales experience crucial for a CRO, as understanding the challenges of sales is fundamental to leading a revenue-driven organization.
Multi-sided business models involve serving multiple distinct user groups and creating value by connecting them. For instance, an IT-managed service provider connects vendors' technology with customers' needs, managing relationships and value propositions on both sides. Today, most businesses, especially those with significant channel strategies, operate on multi-sided models, even if they don’t explicitly recognize it.
Aligning revenue-critical roles within such organizations starts with an overall assessment. Amy looks for hidden strengths and opportunities within the organization, identifying strategic rather than just tactical issues. For example, if sales and marketing are not aligned on the ideal customer profile, it leads to inefficiencies. Defining and agreeing on the strategy, such as the target customer, is crucial. This clarity helps in focusing efforts and resources effectively.
Data is essential for fueling revenue growth, but it needs to be actionable. The process begins with setting up robust feedback loops and scorecards to continuously monitor and evolve the go-to-market strategy. Here’s a deeper dive into how organizations can effectively utilize data to drive revenue growth:
The challenge often lies in gathering and ensuring the accuracy of data, but the real value comes from interpreting and acting on it. When done correctly, data-driven strategies can significantly enhance your revenue growth by enabling more informed decision-making, improving customer experiences, and optimizing operational efficiencies.
Customer centricity is more than just a business strategy; it is a philosophy that places the customer at the core of every decision and action taken by an organization. In today's rapidly changing business environment, being customer-obsessed is not just beneficial but essential for sustained success. Here’s why:
Implementing customer centricity requires a holistic approach. It involves rethinking business processes, aligning organizational structures, and fostering a culture that prioritizes the customer. It also means integrating customer feedback into decision-making processes and continuously striving to improve the customer journey.
In the fast-paced world of business, the C-suite is often seen as the pinnacle of success.: yet, behind closed doors, many CEOs are grappling with a common enemy: bad data. From decreased earnings per share to a loss of investor trust, the consequences of poor data management ripple through every level of the organization.
According to Gartner:
Poor data quality costs organizations an average of $15 million per year in losses. IBM found that 33% of business leaders do not trust the information they use to make decisions. Inaccurate data can damage a company's reputation, leading to loss of customer trust and loyalty. According to Oracle, 89% of customers will switch to a competitor due to poor data experiences.
These statistics highlight the significant impact bad data can have on organizations, impacts such as financial losses and diminished customer trust. Ensuring data accuracy and quality is crucial for informed decision-making and maintaining competitive advantage in today's business landscape.
Bad data can take many different forms. It might be outdated, incomplete, inaccurate, inconsistent, or irrelevant. Regardless of the form it takes, bad data can be devastating for a company's operations. The consequences of bad data include:
Bad decisions: Bad data can cause decision-makers to make poor choices or miss opportunities, which can have serious consequences for a business, leading to lost revenue, wasted resources, or missed opportunities.
Increased risk: Bad data can increase the risk of financial loss, reputational damage, or legal exposure. For example, if a company relies on inaccurate data to make financial decisions, it could face serious financial consequences.
Loss of credibility: If a company's data is consistently inaccurate or incomplete, it can damage the company's reputation and credibility in the marketplace.
Companies have a wealth of information at their disposal; however, not all data is created equal. Bad data can have serious consequences for a business, especially for those in the C-suite. Poor-quality data can directly impact the decision-making process, ultimately costing companies time, resources, and money.
The C-suite is responsible for the strategic direction of a company. They rely on data to make informed decisions and drive the company forward. When bad data is introduced into the decision-making process, it can create significant challenges for leaders in the C-suite.
Specifically, bad data can:
No one in the C-Suite is immune. Each executive has their own struggle.
The Chief Executive Officer (CEO) feels the pain of decreased earnings per share, lower valuation, and the loss of investor/shareholder trust. The cause? Profit erosion, missed forecasts, and delayed or lowered financial events. Without accurate data to guide decision-making, the CEO is left navigating turbulent waters blindfolded.
For the Chief Financial Officer (CFO), the pain of profit erosion and missed forecasts runs deep. Without visibility into critical metrics like customer acquisition cost (CAC) and unit-level margins, the CFO struggles to accelerate value creation and drive sustainable growth.
The Chief Revenue Officer (CRO) faces the agony of unhealthy revenue, missed quotas, and inconsistent go-to-market solutions. The root cause? A lack of visibility into critical data outside the CRM, missed customer signals, and poorly performing programs.
The Chief Technology Officer (CTO) wrestles with faulty technology solutions, inefficient resource allocation, security risks, and reduced innovation. With this adversity, the CTO cannot properly support the organization.
The Chief Marketing Officer (CMO) grapples with the pain of poor-performing marketing campaigns and missed audience targets. Without proper journey mapping and audience engagement, the CMO struggles to allocate resources efficiently and drive meaningful results.
The Chief Product Officer (CPO) feels the sting of low product engagement and poor buyer-seller engagement. The cause being... Customer needs going unmet, content failing to address demand, and user experiences lacking relevance and personalization.
To alleviate the pain felt across the C-suite, organizations must prioritize data quality and management. By investing in robust data analytics tools, implementing data-driven strategies, and fostering a culture of data literacy, businesses can empower their leaders to make informed decisions and drive meaningful outcomes. The road to success begins with good data—and the journey is well worth the effort.
There is exciting news for businesses looking to revolutionize their data management and analytics. Introducing a modern end-to-end data management & analytics platform that seamlessly integrates with your workflows: Insightify by H2K Labs. Empower your business users to tackle their most pressing data challenges with ease and efficiency. Say goodbye to data silos and hello to streamlined insights!
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In today's data-driven era, predictive analytics is leveraged to steer decision-making, enhance operational efficiencies, and unlock new revenue opportunities. By integrating historical data, statistical algorithms, and machine learning, companies can forecast future trends and predict behaviors with impressive precision. This ability is particularly transformative in multisided business platforms where data is constantly being generated across multiple customer segments and channels.
In data monetization and predictive analytics, it is important to understand which business models are most predisposed to success. Industries with multisided business models often exhibit high levels of data liquidity due to several intrinsic factors related to the nature and dynamics of their operations. A multisided business model involves platforms or companies that facilitate interactions between two or more distinct but interdependent groups of customers or users. Examples include online marketplaces, social media platforms, and payment processing companies. Here’s why these industries typically have high data liquidity:
Multisided platforms facilitate a variety of interactions among different user groups. For example, a marketplace connects buyers and sellers, a payment platform links merchants and consumers, and a social media site interacts with individuals, advertisers, and content creators. Each interaction generates data, often in large volumes, such as transaction histories, user behavior analytics, content preferences, and engagement metrics.
The ongoing interactions on these platforms ensure a continuous stream of data. Each transaction or engagement on the platform adds new data points, enriching the existing datasets. This continuous data flow helps maintain high data liquidity, making it readily available for analysis and monetization.
Multisided platforms often benefit from network effects, where the platform's value increases as more users join and interact. This increase in users and interactions boosts the volume and variety of data collected, enhancing data liquidity. As data accumulates, these platforms can leverage more detailed insights to improve user experiences, tailor services, and attract even more users, further reinforcing the network effect.
Data from one group of users can often be leveraged to enhance the services or products offered to another group. For instance, consumer behavior data on an e-commerce platform can be analyzed to help sellers optimize their offerings or marketing strategies. This cross-utilization of data increases its value and liquidity, as it is actively being used and exchanged across the platform.
Multisided platforms are typically scalable, expanding rapidly into new markets or user segments. This scalability leads to more data generation and a broader base from which data can be harvested. As platforms scale, they also diversify the types of data collected, encompassing a wider array of behaviors, preferences, and interactions.
The impact of using diverse revenue recognition models in a business is significant and multifaceted, affecting both financial reporting and data management. Different models can lead to variations in how revenue is recognized and reported, altering the apparent financial health of a company and influencing stakeholder decisions and investment strategies. Additionally, these models affect data accuracy and the complexity of data management, as each model requires specific data tracking and analysis to ensure compliance with regulatory standards.
In summary, the high levels of data liquidity found in industries with multisided business models are driven by the continuous, diverse, and expansive nature of the data generated through their platform interactions. This liquidity supports robust analytics and operational agility and enhances the platform’s ability to innovate and maintain a competitive edge.
Predictive analytics offers several strategic advantages for multisided business models, crucial for thriving in competitive environments:
Incorporating predictive analytics into a multisided platform can transform data into a strategic asset, driving growth and competitive advantage by aligning business operations closely with market demands and user expectations.
With their rich datasets and dynamic content landscapes, media companies are ideally placed to leverage predictive analytics. Here are several impactful applications:
Advertiser Churn: By analyzing historical data, such as frequency and volume of ad buys, campaign success rates, and client feedback, predictive models can flag advertisers at risk of reducing their spend or leaving altogether.
For example, if a model detects that advertisers with decreasing engagement rates tend to churn within three months, media companies can initiate targeted retention strategies tailored to these advertisers. These strategies might include personalized offers, improved ad placement options, or custom campaign analytics reports designed to demonstrate the platform's value.
Subscriber Churn: Media businesses utilize predictive models to identify which subscribers might soon cancel their subscriptions. Insights into why subscribers leave—be it content dissatisfaction or competitive pricing—enable targeted interventions to retain them.
Ad Campaign Performance: By leveraging data from past campaigns, including viewer engagement metrics, conversion rates, and demographic information, predictive models can forecast the performance of future campaigns under various scenarios. For instance, a media company might use predictive analytics to determine the optimal mix of content, audience targeting, and ad timing to enhance viewer engagement and conversion rates. Additionally, predictive models can identify which content themes or formats resonate most with specific audience segments, allowing for the customization of ads to audience preferences.
Leveraging First-Party Data: With third-party cookies phasing out, media companies increasingly rely on first-party data to fuel their predictive models. This data provides deeper insights into consumer behaviors on their platforms, enabling more accurate predictions about content preferences and advertisement placements.
Enhancing Lead Generation Campaigns: Predictive analytics can significantly improve the effectiveness of lead generation campaigns by identifying characteristics of leads that are more likely to convert. Media companies can use these insights to tailor their messaging and targeting strategies, thereby increasing their campaigns' conversion rates and ROI.
Optimizing Event Outcomes: For media companies that host webinars, conferences, or other events, predictive analytics can forecast attendee interests and engagement levels. This intelligence allows for customizing event content to match audience preferences, enhancing participant satisfaction and engagement.
Content Optimization: Predictive analytics guides media entities in crafting content strategies aligned with viewer preferences, ensuring resource allocation towards content with higher engagement potential. Preferences can include time, format, length, channel, and style mapped to specific themes and audience segments.
Informing Editorial Decisions: Editorial teams can benefit from predictive analytics by identifying trending topics and predicting reader interest in various subjects. This can guide content creation efforts, ensuring that resources are invested in articles and features more likely to resonate with their audience. For example, by analyzing reader reactions to different themes or writers, editorial teams can adjust their content strategies to better align with emerging trends, increasing readership and engagement.
While predictive analytics can provide substantial benefits, several challenges may impede its successful implementation:
Data Quality and Depth: The precision of predictive analytics hinges on high-quality, comprehensive data. Inaccuracies or data gaps can lead to faulty conclusions, which might result in costly missteps.
Model Overfitting: Creating models overly tailored to historical data can fail in generalizing future conditions, leading to unexpected outcomes when applied in different contexts.
Organizational Resistance: The disruptive nature of predictive analytics might meet resistance internally, as stakeholders may prefer traditional methods over data-driven strategies.
End-to-End Workflows: Merely observing data falls short. Automated workflows are critical to act on insights effectively. These workflows ensure actions are taken, measured, and held accountable.
Regulatory Compliance: With stringent data privacy laws, companies must ensure that their predictive analytics practices comply with all regulations to avoid legal and reputational risks.
Predictive analytics offers businesses a powerful tool to navigate the complexities of modern markets. By turning vast data into actionable insights, companies across various sectors can remain competitive and pioneer new growth and efficiency strategies. For media companies, in particular, integrating predictive analytics into their operational and strategic frameworks is not just an option but a necessity to thrive in an increasingly digital world.
Set up a complimentary assessment call to see if predictive analytics are right for your company.
In our world of data dependency, businesses rely heavily on the integrity and accessibility of their data to make informed decisions, drive growth, and maintain a competitive edge. However, as data volumes continue to skyrocket and technologies evolve, ensuring the security and proper management of data has become increasingly complex. The question every organization must ask themselves is: Do you really know where your data is?
Data is the lifeblood of modern business operations, flowing through various systems, applications, and platforms. From customer information to financial records and intellectual property, data comes in many forms and resides in numerous locations. Yet, despite its critical importance, many businesses struggle to maintain a comprehensive understanding of where their data is stored and how it is being used.
One of the primary challenges organizations face is data sprawl, the proliferation of data across disparate systems and environments. According to a study by Varonis, the average company has 17 petabytes (a petabyte is a million gigabytes) of data, with 58% of that data being "stale," or no longer actively managed or used. With the rise of cloud computing, mobile devices, and remote work, data can easily become scattered across multiple cloud providers, on-premises servers, employee devices, and third-party applications. This decentralized approach to data management not only increases the risk of data breaches and compliance violations but also makes it difficult for businesses to enforce consistent data governance policies.
Another factor contributing to the complexity of data management is the lack of visibility into data usage and access permissions. A survey conducted by IBM found that 61% of organizations struggle with maintaining visibility into who is accessing their data and how it's being used. Without clear visibility into who is accessing data, when they are accessing it, and for what purposes, businesses are vulnerable to insider threats, unauthorized access, and data misuse.
Additionally, as data privacy regulations such as GDPR and CCPA continue to evolve, organizations must ensure they have the necessary controls to protect sensitive data and comply with regulatory requirements. The International Association of Privacy Professionals (IAPP) reports that the average cost of non-compliance with data protection regulations, such as GDPR and CCPA, is $14.82 million.
To address these challenges, businesses must adopt a proactive approach to data management that prioritizes visibility, control, and security. This begins with conducting a comprehensive data audit to identify all data sources, repositories, and access points within the organization. By gaining a clear understanding of where data is located and how it is being used, businesses can implement appropriate security measures and access controls to safeguard sensitive information.
Furthermore, organizations should leverage data management tools and technologies that provide real-time visibility into data usage, access patterns, and security incidents. From data loss prevention (DLP) solutions to identity and access management (IAM) platforms, investing in the right tools can help businesses monitor and manage their data more effectively, reducing the risk of data breaches and compliance violations.
The question of whether you really know where your data is cannot be taken lightly. In an era of increasing data complexity and regulatory scrutiny, businesses must take proactive steps to gain visibility into their data landscape and implement robust security controls to protect sensitive information. By prioritizing data governance, security, and compliance, organizations can mitigate the risks associated with bad data management and ensure their data remains a strategic asset rather than a liability.
Traditional business intelligence (BI) tools are often ill-equipped to meet the demands of today's rapidly evolving business landscape. Built primarily for analyzing historical data, these tools lack the agility and functionality required to generate actionable insights that drive future value. Additionally, traditional BI solutions are not optimized for business users or multi-sided business models, requiring extensive technical expertise and hindering collaboration across organizations.
To overcome these limitations, businesses must embrace modern data management and analytics platforms. These platforms offer intuitive interfaces, self-service capabilities, and advanced analytics features that empower business users to derive actionable insights from data without relying on IT or data science teams. By leveraging real-time data analysis and predictive capabilities, businesses can stay ahead of the competition, adapt quickly to market changes, and seize new opportunities for growth and innovation. In today's data-driven world, making the switch to modern analytics solutions is essential for unlocking the full potential of data and driving long-term success.
In today's data-driven world, the importance of data management and predictive analytics cannot be overstated. However, many businesses overlook the costly consequences of bad data on their bottom line. From inaccurate forecasting to poor decision-making, the impact of flawed data can be detrimental to a company's success.
At H2K Labs, we specialize in providing cutting-edge solutions such as The Revenue Room™ and Insightify to help businesses harness the power of their data for optimal performance. In this blog, we will delve into the hidden truth behind the costly consequences of bad data and how it can be mitigated through effective data management strategies.
What is bad data, and how does it impact your business? Bad data refers to inaccurate, incomplete, or outdated information that can lead to misinformed decisions, lost opportunities, and ultimately impact your bottom line. It can result in flawed reports, inefficient processes, and damage to your business reputation.
Understanding the implications of bad data is vital for improving data quality and making informed decisions for sustainable growth. In this post, we will uncover the different forms of bad data and explore strategies to identify and rectify them to safeguard your business from the costly consequences of inaccurate information.
The financial impact of bad data on your business cannot be understated. Harvard Business Review (HBR) estimated that companies in the U.S. experience a $3.1 trillion annual cost related to bad data and that knowledge workers spend about 50% of their time addressing data issues. Also, at an aggregate level, 30% of annual revenue is lost to bad data (Entrepreneur.com). And that’s just the tip of the iceberg. When businesses rely on inaccurate or incomplete information to drive their strategies, they are flying blind. Inaccurate information leads to misguided decision-making.
Some symptoms are increased operational costs, missed revenue opportunities, and poor resource allocation. Imagine the costs associated with targeting the wrong audience due to outdated customer information, losing business because you were unaware of program performance issues, or making pricing decisions based on flawed market data. These mistakes affect your bottom line directly and have long-term consequences on your business's sustainability and growth. Let’s delve deeper into the specific monetary implications of bad data and discuss strategies to mitigate these risks effectively.
Aside from financial impacts, bad data can also create significant operational hurdles for your business. Inaccurate information can lead to inefficiencies in processes, decision-making delays, and decreased productivity among your teams. It can also impact customer service. According to research by Forbes Insights, 66% of executives believe that inaccurate data undermines their ability to provide an excellent customer experience. Operational challenges arising from bad data can include difficulties in personalizing customer interactions and addressing customer inquiries effectively.
Picture the complications of trying to streamline your supply chain with unreliable inventory data or trying to execute marketing campaigns without a clear understanding of your target audience. These operational challenges not only disrupt the flow of your business operations but can also damage your reputation and customer relationships. In the next section, we will explore how bad data affects your day-to-day operations and offer solutions to overcome these obstacles effectively.
Maintaining data integrity is crucial for the success of any business. Implementing robust data quality control measures can significantly mitigate the risks associated with bad data. From regular data audits to investing in data cleaning tools, there are various strategies you can adopt to ensure the accuracy and reliability of your information. By prioritizing data quality control, you not only safeguard your operations against costly errors but also enhance decision-making processes and boost overall business efficiency. The upcoming section will explore best practices for implementing data quality control measures and how they can positively impact your bottom line.
Identifying bad data is the first step towards rectifying its detrimental effects on your bottom line. Start by conducting thorough data profiling to uncover inconsistencies and anomalies. Utilize data quality software to flag erroneous entries and duplicates automatically. Establish clear data validation rules to catch errors at the point of entry. Regularly monitor key performance indicators affected by data quality issues. For rectification, involve all stakeholders in data cleansing efforts and implement a data governance framework to maintain data accuracy over time.
Maintaining data integrity is not just a nicety but an absolute necessity for any organization looking to thrive in today's data-driven landscape. The hidden cost of bad data extends far beyond mere numbers on a balance sheet. It undermines decision-making, incurs significant financial losses, and erodes trust—a trifecta of detrimental effects that can spell disaster for businesses.
By prioritizing data integrity, you are not only safeguarding your bottom line but also laying a solid foundation for informed decision-making and sustainable growth. Embrace advanced data validation techniques, invest in robust data quality tools, and foster a culture of data governance within your organization. Remember, the true value of your data lies in its accuracy and reliability - make it a priority to protect and nurture this invaluable asset.
In a thought-provoking piece by Jacob Donnelly, Founder of A Media Operator, in his recent article, Why Media & Events Go Hand in Hand, the spotlight is turned on an increasingly relevant topic in the business landscape: the intersection of events and digital transformation. A few of the points made that resonated with me and that I recap below with additional context include:
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If you are a leader in media and events and not a member of Jacob’s AMO Community, you are missing out. Jacob has one of the best, most active, highly engaged, and exciting communities in the media and event spaces. Here’s a link to join. Full disclosure, there is no affiliate relationship at all, I am just a huge fan and love what he is doing. You will too.
The separation of media and events businesses is not due to what customers want but rather what investors want. Investors want high-margin, easy-to-assign valuation businesses. When you combine media and events that have different valuation multiples and cost infrastructures, this sometimes makes things messy. While this worked in the past, it’s my opinion that the tide has shifted and businesses that do not offer a Vision-to-Decision approach for buyers and a “Start the Conversation Early and Stay There” for sellers may miss out on desired valuation and buyer attractiveness, especially with strategics.
Most US-based media companies offer events (think Forbes, Wall Street Journal, Crains’s Business), and it is a critical component of value for customers, improving annual contract size, lifetime value, audience engagement metrics, and overall revenue growth. The media plus events combination offers revenue diversification, which as we saw during Covid, was a lifeline for many.
Additional structural changes are making this intersection more vital and critical. Data monetization, 1st party data, AI, and the radically changing landscape of audience acquisition and retention channels, and changing customer preferences and demands are just a few of those factors.
Informa's decision to shed its traditional media assets might have seemed radical at the time. While I wonder if they knew this when they sold over 20 B2B media titles to Endeavor Business Media in 2019, it underscored a forward-thinking approach to digital transformation. By offloading legacy media operations entrenched in outdated practices and data environments, Informa opened the door to fuel its lucrative event business with modern, 365/24/7 media businesses that are profitable on their own but also add strategic value to events and add significant value to a new revenue stream through data monetization.
Informa now boasts two modern media entities - Industry Dive and TechTarget - that started out as pure digital plays with zero legacy print, that offer incredible scale, in terms of market reach, data solutions, and SaaS subscription offerings. This strategic realignment is perfectly in sync with their GAP2 objectives in the area of data and digital.
One of the most compelling aspects of Informa's transformation is its emphasis on first-party data. In an era where data is king, Informa's ability to collect, analyze, and monetize this information in a SaaS-like model is not just innovative; it's a game-changer. This approach not only diversifies revenue streams but also enriches the value they offer to their clients and the broader market.
Simply reading TechTarget’s homepage content is all you need.
But then scroll down a bit further…
And finally, voila!
Imagine:
Another critical point Jacob raises is the evolution of the buyer/seller journey in the context of a media + events + data ecosystem. The traditional pathways to purchase – reading articles, downloading white papers, attending webinars, or participating in events – are no longer standalone touchpoints. Instead, they are part of a broader, more intricate journey that requires a nuanced understanding of the buyer's needs and behaviors.
For example, in sectors like manufacturing MRO supplies or enterprise software, the route to purchase is far from linear. Buyers seek comprehensive solutions to their needs, making product discovery a pivotal phase in their journey. Here, media and event companies have a unique opportunity to enhance the customer experience. By curating deep repositories of products organized by category and searchable by various criteria (features, integrations, price points, industry focus, etc.), these companies can significantly impact the decision-making process. Facilitating actions such as saving, sharing, comparing, and responding to RFPs/RFIs not only aids in the discovery phase but also propels buyers closer to the crucial mid-to-end of the funnel stages.
From the convergence standpoint, the deeper you embed yourself into the buyer journey, the more purchase intent data you will acquire which in turn allows you to produce better demand generation campaign results, provide highly relevant curated journeys for audience members, and if you offer matchmaking services, you can accelerate and improve the match rate quantitatively and qualitatively.
I naturally delve into the realm of AI in our conversation. By crafting a captivating "Vision to Decision" path for buyers and offering sellers the "Start the Conversation Early and Stay There" initiative, which merges media, events, and decision-making tools, the prospect of leveraging AI in a profitable manner—be it for internal enhancements, product enhancements, or standalone commercial solutions—is truly exciting.
The wealth of data generated through interactions on these platforms offers unprecedented opportunities for highly curated and relevant experiences that both buyers and sellers will be willing to pay for. More on that in a follow-up blog.
As we reflect on the insights from Jacob's article, it's evident that the intersection of events, digital, and data is not just reshaping the media landscape; it's setting a new benchmark for how businesses engage with their audiences. Informa's strategic pivot serves as a compelling case study for the potential that lies in embracing digital transformation, leveraging data, and rethinking the customer journey. For media companies and event organizers, the message is clear: the future belongs to those who can integrate these elements to deliver a more nuanced, personalized, and valuable experience to both buyers and sellers.
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H2K Labs partners with businesses of all sizes, from startups to large corporations, to leverage data for scalable financial gain and comprehensive value creation. We specialize in tech-enabled strategies, utilizing advanced analytics to uncover new revenue opportunities, enhance existing revenue streams, and optimize margins, thereby increasing sustainable long-term growth and enterprise value. Our services are powered by H2K's analytic platform, Insightify, and include AI-driven predictive analytics, comprehensive revenue management, and strategic M&A support services.
This is a special edition of A Media Operator, sponsored by H2K Labs by Jacob Donnelly. In these sponsored deep dives, we dig into a specific topic and go into much more detail. I hope you enjoy it!
Revenue predictability is a critical business process that has become increasingly challenging. The combination of economic uncertainty, the increasing pace of technological change and disruption, the explosion of data, and rapidly changing demands and preferences of buy-side and sell-side customer segments has made the traditional “same time last year” method of forecasting obsolete.
Businesses generate an immense amount of data, but many operators don’t know how to use it properly. Every interaction with a client—prospective and current—is information that can better inform how your business is performing. Every campaign that runs is information that can give you hints to how your advertising partners will think about renewal conversations. How your audience is engaging with your clients’ campaigns is even more telling. Even payment terms can lend insight into whether your financial forecast is as clean as you expect.
The reality is that bad—or no—data is costing you more than you think. Not only can it impact your immediate cash flow or next quarter’s financial forecasts, but if your data isn’t clean, it could impact your company valuation when it comes time to either raise money or sell the business. The reality is that prospective buyers can only make decisions with the data that you provide to them. And so, the quality of the data you have about your business will determine what they can offer you.
Businesses seek revenue predictability, yet traditional forecasting relies on subjective, often outdated CRM data lacking crucial insights. To achieve this predictability, revenue and finance teams must shift focus from solely focusing on what’s in the CRM to primary data stored in external systems such as client delivery platforms, ad management systems, lead management platforms, invoicing and collections, and unstructured data such as email and messaging content.
And yet, so many businesses ignore this information. They look at their current year’s revenue and make assumptions on what next year’s financial forecasts will look like. It’s like sticking their finger in the air and making a decision based on how the wind is blowing. I had a boss once say to me, “let’s hit $10m in ad revenue in 24 months.” We were barely pushing $1m, we didn’t know anything about our audience, and yet we were going to somehow hit this magical and made-up number.
It doesn’t work that way. The only way to make better decisions about your business is to have the proper data. And not only do you need the proper data, you need to operationalize that data. Data that lives in a silo, or data that doesn’t have an owner, is like an iceberg in the ocean. It’s there, but its impact on the business is unknown until your ship crashes into it.
Now, we could turn this piece into an entire book about all the different ways to use data to help make your business stronger. But what I want to focus on is the types of advertising data that you have control of that can have an immediate impact on your business forecast—both in mitigating churn and growing your client’s spend.
H2K Labs helps clients unleash the power of real-time data to transform how they acquire, retain, and grow revenues. We know media; we know data; we know revenue because we have been publishers before.
We break the barriers of traditional reporting methods, which limit clear visibility and action. Discover how real-time reporting in your Revenue Room can empower you to:
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To leverage these insights effectively, establish uniform data standards across your organization to create a unified revenue stream. By implementing predictive analytics using machine learning and AI, you can further amplify the impact of these data points on your business outcomes. This approach goes beyond merely observing past events; it forecasts future occurrences, uncovers the underlying causes, and provides actionable insights to alter the outcomes.
It is crucial to know in real-time how well you are meeting customer expectations and fulfilling contractual obligations when selling advertising, demand generation, trade show space, or guaranteed appointments. Knowing past and present results isn’t sufficient.
Instead, a dependable predictive analysis is crucial. It forecasts the potential outcome at the campaign’s end if no action is taken, aligning it with the commitments made to your client. These insights not only have to be presented to sales and customer success in a way that allows them to take action, but they must also be a critical part of the forecasting process to ensure accuracy and allow the business to respond effectively.
Advertising
Demand Generation
The days of sending campaign and demand generation reporting in disparate Excel spreadsheets weeks after the end of the campaign are over. If reporting happens after the campaign ends, it is too late. Providing your clients with unified real-time campaign reporting is a great way to keep your clients engaged and excited about performance. Also, it makes your sales and customer success teams data-fueled value creators for your clients. But there’s also another important benefit: client engagement with those dashboards.
As media and event organizers, we invest in developing first-party data and purchase intent signals for our clients. However, we fail to look at what our prospects and clients are doing on our website and in other applications that provide us with these same intent signals within our domain. By tracking them across our owned & operated, we can make smart decisions.
Enhancing the oversight of sales team activity levels demands a comprehensive approach that extends beyond merely tracking interactions within the CRM. Without a robust data architecture, stringent CRM governance, and standard operating procedures, the true extent of a salesperson’s activity—both inside and outside the CRM—can often go unnoticed. Since CRM data is largely a function of what the salesperson chooses to enter, connecting that to structured and unstructured data sitting outside the CRM is required to gain a holistic view of sales activities.
Most clients have purchasing and payment patterns, and deviations from both these patterns are often overlooked as significant risk signals.
This is a lot to digest, but the benefit of thinking each one of these critical data levers through and coming up with a modern predictive forecasting strategy are clear:
In my last blog, Uncovering the Hidden Gold: How Marketing Can Secure a Seat at the Revenue Table, I talked about how I realized we needed to be using our data in the best way to move the business forward. Marketing had it's set of KPIs and reported against those KPIs but they were not earth-shattering. Today, I want to talk about identifying critical gaps in the data, my aha moment, and how to use the gaps in planning. We (marketing) need to get deeper into the data to drive a stronger marketing strategy to show results to the business that matters - to earn a seat at the revenue table.
Over my time in media and events, we reported on the typical results but these numbers are superficial and only sometimes essential. Don't get me wrong, the marketing numbers are essential - to marketing. Did it really matter to the rest of the business how paid social media was performing? Did it matter how much traffic the website was getting? Not really - but these numbers are where I still see event and media companies' focus.
Don't believe me?
A few years back, I talked with the CMO of a large medical device manufacturing company about his media buying experience. During the discussion, he expressed that the media sales reps didn't have the skills and/or data when faced with a knowledgeable buyer. He was presented with options for an ad package and the standard details: email open rate, email click-through rate, website impressions, etc. Then he started asking more questions. He wanted to know information about the programs that went more profound, like:
You see, he didn't care as much about the standard metrics that are reported, like total impressions, subscribers, and website traffic. He wanted to understand his return on investment. The sale rep he was working with couldn't answer those questions - if they could, it took longer to get the information because they had to go request the data.
I recently attended Event Tech Live in Las Vegas, one of the sessions was about using event data to create a data-driven strategy to improve the event and deliver value to the stakeholders. Overall the session was great, I was sitting there thinking - I sure wish I had something like this in my prior life. It would have helped get me out of the weeds and really allow me to focus better and understand what was happening with the marketing efforts. However, what needed to be added for me was using the data to improve revenue and increase the value of the business beyond delivering attendees to the event.
When it hit me that marketing was looking at the data all wrong and reporting on marketing numbers that didn't really matter outside of marketing, I started pulling post-show data from each event into two workbooks; one focused on marketing channels and event data in the other; things like square foot sold, number of exhibitors, number of attendees, attendee areas of interest, attendee companies, number of attendees from key companies, exhibitor product categories, etc.
This took a great deal of time and effort - because it was pulling data from 16 different spreadsheets, pulling reports from 16 different events in our sales database, and compiling it all into something that made sense. Oh, and not to mention, I had to engage the data team multiple times because I kept finding discrepancies in the data.
I will not spend any time (right now) talking about the marketing channel data, but you never know when that might surface. On the event data - I discovered some really interesting things.
I could go on, but there was a lot of information uncovered once someone took the time to dig into the data to really understand. What it did teach me was there were fundamental gaps in our strategic planning, not just at the marketing level but at the brand level.
As a marketing leader, it can sometimes be hard to accept the way you have been developing the strategy needs improvement, and especially hard telling the business the way they have been doing it could be significantly improved. However, the reward is definitely worth the effort.
The best way to approach the challenge is to break it into parts. It is easier make small improvements with lasting results rather than try and change everything all at once, disrupting the business. Here at H2K Labs, we have a flywheel approach to help our customers tackle challenges.
As an example, before I worked in events I was in the restaurant industry for many years. At one point, I was in the role of a “restaurant troubleshooter” where I would be sent into an underperforming store to “fix it”. In effect, I was sent in as the general manager where they had removed the prior manager and given marching orders to make things run better - from service to quality. It was all over the place. My approach was simple, I went in day one and just worked. I did this for a week. The next week, I started working with people directly to help. In one instance, I noticed the food was not being prepared properly, so on one of the busiest nights, I scheduled myself to work the line with the rest of the kitchen. I slowly started implementing the correct way to do things and all the while explaining what I was doing to the person next to me. Then after a couple of hours, we switched places and they took over. After a day or two of this, the food preparation drastically improved. I repeated this over and over with all of the “problem” areas and guess what? In a matter of three weeks, we were a fully performing team and the store was improved. All it took was a little coaching.
That approach stuck with me to this day. Using this knowledge, I approached the issue of strategic planning to improve the way we as a business approached our planning. For example, we took the mismatch of the attendee interests and exhibitor product categories and worked those into the strategy. We focused on developing a plan to offset the gap and put it into action. We identified the companies needed to satisfy the other to improve not only the event but improve relationships with our exhibitors. Then we picked another area to improve - key attendee companies and developed a plan to ramp up efforts to attract more of the right people from those companies to the event.
The end results were fantastic. The different teams started working closer together to make the products a win-win. Trust in other departments deepened. Goals were being met and as a result we saw better collaboration, more internal communication, and a lot less finger pointing when there was a problem.
However, it took a lot of time and effort to get that data because of the complexity of the business model. It wasn't really sustainable to put in the hours of manual work to keep things moving along. There were just too many platforms with different pieces of data to make things manageable. Platforms in the market were not able to help do these things as they were not created for our business. Sure, we could piece together the data sets in a spreadsheet - but someone always had to spend hours doing the work when their time could have been better spent doing more impactful things.
In my next blog, I will focus on using this data to advance your team and align them with sales.
Until next time!
As a marketer, have you ever found yourself stuck in a cycle of sending more emails, spending more on paid digital campaigns, and trying to build even more partnerships? It's easy to get lost in the data, assuming that driving more traffic and leads will ultimately lead to revenue growth. However, what I learned through my years in event and media marketing is that the traditional approach isn't always the best one. In this blog series, I'll share my journey to discovering a better way to align marketing with revenue goals and secure a seat at the revenue table.
I started my career in event and media with a large event and media company working in event sales marketing. During this time, I used to sit in on calls with potential exhibitors to learn how to sell better. I created collateral for sales reps but often found that what we created was not used. Despite the challenges, I continued to help create fantastic-looking event prospectuses that would contain stats from the attendees of the prior year. Afterward, I transitioned to working with the company's media business, where I repeated many of the same things we did on the events side. The most significant piece of work every year was the media kit, where we tried all sorts of ideas, from creating packages that combined events and media to building out directories and channels on websites. A few years later, I moved back to managing attendee marketing. Here, we employed all sorts of innovative ideas to drive registration, from giveaways to flash sales, all to ensure that we'd have enough attendees at the event and hit our attendance goal.
Marketing reported on our KPIs: lead generated, traffic to the website, paid digital performance, number of registrations, number of actual attendees, saturation of attendees to exhibitor, and more. Sales reported on their KPIs: pipeline, new business, renewals, square foot sold, sponsorships purchased, and more. Then we rinsed, lathered, and repeated the same thing - year after year, event after event.
But there was always a common dialogue: attendee quality is not strong, more event attendees, more registrations for this webinar, more clicks on these ads, more subscribers for newsletters, more leads for this white paper, etc. So, marketing did what marketing did - send more emails, spend more on paid digital campaigns, rent lists, and try to build even more partnerships.
Then, one day sitting at my computer while reconciling the forecast it hit me…we are doing it wrong.
But what was uncovered was gold!
While H2K Labs isn't focused on typical marketing dashboards and audience performance, I learned some valuable lessons that apply to the work we are doing today. Over the next few weeks, I will share more about what I learned and how it applies to securing marketing a seat at the revenue table.
Are you tired of focusing on attendee quantity instead of revenue quality? Join me on this journey to uncover a better approach to marketing that will empower your team to work with sales account reps, deliver quality leads, and report on metrics that matter.
In our preceding blogs, we've shed light on The Revenue Room™ and Revenue Kaizen, presenting pivotal operating principles to elevate revenue into a center of excellence in B2B enterprises. Our focus now shifts to the intricate components that make revenue an essential business process, exploring how to implement and manage these elements effectively.
Following the steps of the Revenue Operating Plan is crucial, especially in the B2B sector, as it lays the groundwork for a systematic and efficient approach to revenue generation. By aligning products with customer needs and demands, and engaging effectively with target segments, businesses ensure that their offerings are both relevant and compelling. The execution phase, which focuses on managing the sales pipeline, leverages data-driven strategies to optimize sales processes and reduce revenue risks. The delivery stage is key to fulfilling customer expectations and building long-term value, fostering customer loyalty and retention. Finally, the expansion phase concentrates on growing business within the existing customer base, through upselling and cross-selling, which is essential for sustainable growth. The iterative nature of the 'Rinse, Lather, Repeat' step, using data to continuously refine and scale operations, ensures that the business stays agile and responsive to market changes. Implementing these steps effectively results in a robust, customer-centric revenue model that drives business success and resilience.
Implementing a phased approach to align revenue-critical roles is vital. Starting with the most obvious alignments, the process evolves through four distinct phases, each adding more departments into the alignment, from Sales and Customer Success to including Marketing, Operations, and Product teams. Data is pivotal in this alignment, fostering collaborative, data-driven decision-making.
"Revenue critical roles'' refer to key organizational functions that directly influence and drive revenue generation. These roles are pivotal in ensuring the financial success of a company. In the B2B information sector, the roles are more expansive than in other B2B businesses. They span across various departments, each contributing uniquely to the revenue stream. Here's a breakdown of some of these roles and their primary functions:
Function: Responsible for directly selling products or services to customers. They play a crucial role in meeting sales targets, developing sales strategies, managing the sales team, and building relationships with key clients.
Function: Focus on creating and implementing marketing strategies that enhance brand recognition and generate leads for the sales team. Their role involves market research, campaign creation, digital marketing, and tracking the effectiveness of marketing efforts in terms of ROI and lead generation.
Function: Tasked with identifying new business opportunities, partnerships, and markets. They are crucial in expanding the company’s client base and finding new revenue streams. Their role often overlaps with sales and marketing and while common in most B2B businesses, not as common in B2B information sectors.
Function: Ensure customer satisfaction and retention, which is critical for recurring revenue and upselling opportunities. They work to understand customer needs, address issues, and provide solutions that enhance the customer experience. In B2B information, customer operations includes:
Function: Oversee the integration and alignment of sales, marketing, and customer success operations. They are crucial for streamlining processes, optimizing the sales funnel, and ensuring that the different departments work cohesively towards revenue goals.
Function: Oversee the development and lifecycle of a product. Product teams ensure that products meet market demands and customer needs, directly influencing the sales potential of the product. In the world of business information - eg. media, events, price reporting, marketplaces - the product eco-system includes but is not limited to:
Function: Play a key role in revenue forecasting, budgeting, and financial analysis. They provide insights into financial performance, cost control, and investment opportunities, aiding in strategic decision-making.
Each role contributes to the revenue pipeline in different but interconnected ways. Their functions are crucial in driving sales, optimizing marketing efforts, maintaining customer relationships, and ultimately, ensuring the financial health and growth of the organization.
Creating revenue-impacting KPIs for the aligned organization is a crucial step. These KPIs span across different departments - Sales, Marketing, Customer Success, Operations, Product, and Finance - each with its specific set of metrics that align with overall revenue goals. We will do a deep-dive into the specific KPIs in an upcoming blog. Make sure to sign up for blog alerts so you can be notified when we post.
Standardization plays a crucial role in data-driven revenue organizations for several key reasons:
1. Enhances Data Quality and Integrity: Standardization ensures that data across the organization is consistent and uniform. When data is standardized, it reduces errors and discrepancies, improving the overall quality and reliability of the data. This is especially important in data-driven businesses where decisions are based on data analysis. Poor data quality can lead to incorrect conclusions and poor decision-making.
2. Facilitates Data Integration: In today’s business environment, data often comes from various sources, including internal systems, social media, IoT devices/event tech, and third-party sources. Standardization allows for easier integration of these diverse data sets. It ensures that data from different sources can be combined and used together effectively, which is essential for comprehensive analysis and insights.
3. Improves Efficiency: Standardized data streamlines processes and saves time and resources. It reduces the need for manual data cleaning and transformation, allowing data scientists and analysts to focus on higher-value tasks such as analysis and interpretation. This can lead to faster insights and more agile decision-making.
4. Enables Scalability: As businesses grow, so does the volume and complexity of their data. Standardization creates a framework that can easily scale, accommodating increasing amounts of data without sacrificing quality or performance. This scalability is vital for data-driven businesses that need to adapt to changing market conditions and business needs quickly.
5. Supports Compliance and Data Governance: With the increasing importance of data privacy and security regulations (like GDPR, CCPA, etc.), standardization aids in compliance. It ensures that data handling across the organization meets legal and regulatory requirements. Moreover, standardized data supports robust data governance, allowing organizations to manage their data more effectively and securely.
6. Facilitates Better Analytics and Machine Learning: Standardized data is critical for accurate analytics and machine learning models. If you need predictive analytics, they won’t happen without standardization. There is no way to create the model accurately. Inconsistent or poor-quality data can lead to biased or invalid model results. Standardization ensures that the data fed into these models is accurate and consistent, leading to more reliable and actionable insights.
7. Enhances Data Sharing and Collaboration: In large organizations and across different departments, data sharing and collaboration are essential. Standardization ensures that everyone is on the same page, allowing different teams to understand and use the data similarly. This uniform understanding is crucial for collaborative projects and cross-functional teams.
Transforming revenue into a critical business process is not just about adopting new strategies or technologies; it’s about a holistic transformation of your business’s approach to revenue generation. It requires continuous improvement, standardization, and alignment across all departments. By following the outlined components and phases, businesses can effectively make revenue a center of excellence, paving the way for sustained growth and success in the competitive B2B landscape.
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In our previous blog, we delved into The Revenue Room™ and Revenue Kaizen, highlighting the immense financial returns of centering revenue as a focal point of excellence in B2B businesses. Now, let's explore why revenue is your most critical business process and the guiding principles of The Revenue Room™ Operating Framework.
For many businesses, sales are often seen as an immediate outcome rather than a process that needs careful management. This perspective is particularly prevalent in companies formed through acquisitions, owned by private equity, or that are very decentralized. These companies often suffer from fragmented and siloed sales organizations and processes. This fragmentation leads to challenges in controlling, measuring, scaling, and optimizing revenue goals, resulting in lost revenue, wallet share, and market share. Therefore, transforming these outdated, siloed sales practices into a modern, data-driven center of revenue excellence is crucial.
1. Leadership-Driven Transformation
Transformation starts with leadership. Leaders must define and communicate a clear vision and mission for driving transformation and articulate how it will benefit individuals, teams, and the business. This communication needs to be consistent and ongoing.
“A key foundation for change success lies in data-driven leadership. The report finds that leaders who explain the benefits of data use and lead by example can increase the likelihood of change success by 23 percent and have been shown to increase employees’ willingness to work in a data-driven manner.” - Cap Gemini, Data-Driven Change Management is Crucial for Successful Transformation, January 2023
2. Data-Driven Decisions
The journey must be fueled by data. Utilizing a single source of revenue truth coupled with advanced business intelligence enables the activation of analytics, predictive insights, risk and opportunity identification, and embedding data-driven decision-making into daily workflows.
3. Defining Success: Transparent Metrics & KPIs
Smart KPIs are critical to data transformation for a few compelling reasons: focused direction, improved decision-making, enhanced accountability, performance tracking, improved employee engagement and alignment, continuous improvement and risk management.
Establish clear, transparent, measurable objectives and performance metrics to evaluate the success of revenue initiatives. This helps in tracking progress and making necessary adjustments.
4. Effective Revenue Governance
It’s essential to exercise control over all customer-facing, revenue-generating activities. This includes establishing clear metrics, definitions, functional accountability and responsibility, and processes.
Revenue governance in a business context refers to the policies, procedures, and standards to manage and oversee all aspects of revenue generation, recognition, and reporting within an organization. It is a comprehensive approach that ensures accuracy, consistency, and compliance in revenue-related processes.
Revenue governance includes: revenue recognition, pricing and discounting, sales and contract management, internal controls and audits, pipeline management, GTM motions, data management and reporting standards, risk management, cross-functional collaboration, technology and systems, compliance and regulatory requirements, technology and systems, training and development and performance monitoring.
5. Collaboration Across Functions
Align every revenue-critical employee across various departments such as sales, marketing, finance, customer success, product, and operations. This ensures a unified focus on goals and collaborative efforts in opportunity identification, acquisition, retention, and expansion.
In B2B information environments, collaboration cuts across sales marketing, audience marketing, sales, customer success, content, operations and finance.Yes, even content and operations need to connect to revenue directly.
6. Embracing Evolutionary Transformation
Transformation is not instantaneous; it's an evolutionary process that unfolds over time. It requires continuous learning, experimentation, risk-taking, and a collaborative team spirit. And again, this must start from the top and permeate every facet of the revenue organization.
Think Revenue Kaizen.
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7. Forecasting as a Core Competency
Covid proved that Mike Tyson was right when he said, “Everyone has a plan until they get punched in the mouth.”
Customer behaviors and demands are in a constant state of flux, rendering prior assumptions inadequate for future predictions. To adapt to these changes, forecasting must become a fundamental skill, placing significant emphasis on analyzing data from diverse and even unconventional sources. This analysis not only allows us to discern the intentions of our customers but also to anticipate shifts in their demographics and how we can deliver value to them.
Predictive and prescriptive forecasting should be a core competency across all areas, including sales, revenue lifecycle, and operational performance. Forecasting should be in lockstep with pipeline motions.
8. Customer-Centricity
“Customer-centric businesses are 60% more profitable than their counterparts.” - Deloitte The value of experience: How the C-suite values customer experience in the digital age
Customer-centricity is a common theme among market leaders and includes keeping the customer at the center of all revenue initiatives. This involves understanding their needs, pain points, and buying behaviors.
Impact on revenue includes:
9. Transparency and Accountability
Maintain transparency in revenue performance throughout the organization. This should include metrics that reflect actual performance and the impact of transformational changes. Reporting, analytics, and data visualization should be made available through governed business intelligence dashboards to all.
10. Focusing on People
Recognize the need for upskilling or reskilling in certain roles and skills, while others may require new talent acquisition. Training and upskilling, especially in the area of data fluency, needs to be uniform within the context of functional roles as well as from a business-wide perspective.
Understanding and implementing The Revenue Room™ Operating Principles is crucial for any business that aims to excel in revenue generation. By focusing on these principles, companies can transform their revenue processes, making them more efficient, data-driven, and customer-centric. This approach not only revitalizes outdated practices but also positions the company for sustainable growth and profitability in an increasingly competitive and complex business landscape.
Heather Holst-Knudsen has deep roots in the B2B world, growing up in the renowned Thomas Publishing Company. With years of experience and a passion for the industry, she has significantly contributed to digital innovation and monetizing audience engagement. Holst-Knudsen's expertise led her to found H2K Labs, specializing in generating financial returns from data and driving revenue and profitability.
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In today's marketplace, data is more valuable than ever before. Businesses that use data analytics and AI to inform and support their decisions often outperform their competitors who rely on gut instincts alone. A recent HBR Pulse survey on transforming data into business value through analytics and AI found that 75% of respondents say having a data-driven culture is critical to their organization's overall success. But, where is your go-to-market source of truth? How can you ensure that the data you are using is accurate and up-to-date? In this post, we'll explore the survey results and discuss some effective strategies for transforming data into business value.
The survey found that organizations already highly data-driven before the pandemic doubled down and became even more data-driven while struggling organizations fell further behind. Leaders in the survey invested in and accelerated data, analytics, and AI initiatives at higher levels than their counterparts. The reason for this is obvious: with COVID-19 completely transforming how businesses operate in weeks, executives were more inclined to adopt data-driven cultures and accelerate industry-specific solutions, including AI.
In addition, it was discovered that having a unified data cloud is important for organizations that desire significant value from their approach. A Unified Cloud approach enables businesses to share data more efficiently and effectively, increasing collaboration and reducing redundancy, resulting in the ability to identify opportunities for innovation, market entry, competition, scale efficiency and agility, reduce risk, and improve operating margins.
“While it appears that many companies have their data management acts together, in fact, many don’t,” says Doug Levin, executive in residence at Harvard Business School and lecturer at the Harvard Business Analytics Program.
However, the survey found that organizations still struggling to keep up often face challenges in analyzing data across multiple sources and data quality issues. In the past, data silos have been creating barriers to analyzing data across the whole corporation and restricting access to real-time data. Sourcing data from various places remains challenging, including complexities in integrating/consolidating data from several systems/sources. Additionally, data quality issues often arise from poor data governance practices.
Multicloud adoption is emerging as a popular solution, but it presents challenges in data governance/management and service integration and management. However, democratizing access to data and analytics tools and AI capabilities is key to remaining competitive.
Organizations with data complexity due to high levels of daily transactions, mergers and acquisitions, diverse customer segments, and revenue streams have even greater challenges.
CRM and data warehouses are used for data management, but they are not well-suited for most B2B organizations. For instance, a CRM cannot handle detailed digital data such as product analytics, payment/booking/subscription information, call intelligence data, among other areas. Moreover, data warehouses limit you to high-level dashboards that provide minimal insights, or you have to hire a data science and engineering team that can translate the data into valuable insights. Organizations in highly transactional environments with multiple revenue sources and customer segments such as business information, media, events, and marketing platforms require more innovative approaches to data management and reporting.
Now organizations can use end-to-end data management and advanced analytic solutions such as Insightify. Insightify sits on top of core systems such as CRM, Marketing Automation, Finance, Operations, CDP, and even existing business intelligence tools and seamlessly aggregates data from decentralized sources, unifying it into a Single Source of Truth (SSOT) at the platform level. Insightify preserves data in its original format at its source so that businesses can avoid the high costs and risk levels associated with waterfall-level data transformation projects.
Using this unique approach, users are empowered with high-level dashboards and visualization tools coupled with in-depth drill-down capabilities to diagnose, interpret, and prescribe actions and decisions.
Finally, the survey highlights the importance of measuring and reporting data and analytics investments, business value, or outcomes. Investing in data and analytics is only useful if it can deliver concrete business outcomes, such as new product/service introduction, operational efficiency, customer satisfaction, revenue, and market share. Leaders' organizations reported improved performance in each of these key areas. Maximizing business value from data requires leadership support and enterprise-wide strategies for data and analytics.
In conclusion, organizations that prioritize their data analytics initiatives can expect significant returns. With data-driven cultures becoming must-have requirements for modern-day business, businesses must ensure they have a significant head start over their competitors. Leaders who invest in data, analytics, and AI initiatives position themselves to address the effects of disruptions while driving innovation effectively. The right approach, using the correct data from the right platform, can create significant business power. Organizations that utilize effective strategies for transforming data into business value can improve their operational efficiency, customer satisfaction, revenue, and market share while also 21differentiating themselves from their competitors.
The Revenue Room™ empowers mid-market B2B businesses to architect modern revenue organizations using innovative thinking and data-driven strategies. Developed by H2K Labs, this exclusive framework is specifically designed for midsized companies encountering data complexities, such as diverse revenue streams, multi-sided business models, and integrated offerings encompassing services and products. Businesses grappling with data complexity include media, events, buyer-seller marketplaces, business information, and marketing technology and service providers.
In an environment marked by inflation, achieving revenue growth has become a top priority for companies. However, to ensure lasting impact, businesses must focus on retaining and growing their existing customer base, emphasizing high-quality revenue, and investing in capability building across all revenue-critical functions. This requires adopting an approach where capabilities build upon each other, gaining strength over time.
The Compelling Financial Returns of Data-Driven Selling
The transition to data-driven selling is not just a trend but a necessity. According to the Gartner Future of Sales 2025 Report, 60% of B2B sales organizations will shift from intuition-based to data-driven selling by 2025. This shift promises substantial financial returns, as evidenced by data from Boston Consulting Group. Companies with data-driven revenue organizations can expect a 10–20% increase in sales productivity, a 15–20% increase in customer satisfaction, a 30% reduction in GTM expenses, 19% faster growth, 15% more profits. Data from Forrester Consulting shows that public companies enjoy 71% improvement in stock performance.
Several factors underscore the imperative for modernization in the revenue organization. As the business landscape continues to evolve at a rapid pace, new and previously unknown competitors continuously emerge, and radical changes reshape your customer’s preferences and the way they consume information and purchase. Economic challenges and evolving customer demands further intensify the pressure felt by businesses while investors and boards increasingly demand results.
Data assumes a crucial role, transcending its status as a mere tool and becoming a pivotal driver of operational efficiency, margin improvement, value creation, revenue generation, and competitive advantage.
There are clear metrics you can track to see if your revenue organization requires modernization. Some easy ones to monitor include consistently missed forecasts (especially those presented to the board), decreasing quota attainment levels, increasing churn rates, maverick discounting, decreased net revenue retention, low NPS and CSAT scores, and higher-than-expected attrition rates on the revenue team.
In addition to the readily noticeable signals, some are more elusive or recognized but deliberately unacknowledged by the business due to the overwhelming magnitude of the anticipated change.
Inefficiency in Data Management: The extensive time, personnel, and effort required to aggregate, cleanse, organize, and analyze data can be daunting and inefficient. This process, though necessary for deriving insights, is often overwhelming and takes valuable time away from strategic activities that could drive the business forward. Reports are inconsistent, unreliable, and incredibly frustrating to employees.
Missed Revenue Opportunities: Often, there's a persistent concern about potential revenue slipping through the cracks due to inadequate data insights. For example, the finance team might struggle to identify the reasons for customer attrition or to effectively track how well a media business is offsetting print decline with digital growth. Understanding lifetime value is also another challenge.
Challenges in Key Data Metrics Extraction: Investors and boards demand more frequent and more complicated data insights such as gross and net revenue retention, ARPC (average revenue per customer), and audience engagement metrics over a rolling 12-month period. Finance teams and/or CROs cannot produce these reports and data quickly and effectively.
“I know no one apparently gets fired for choosing IBM, but I do know a few CEOs who did get fired for providing imprecise forecasts to the board four times in a row.” - Me at a recent breakfast with a private equity investor. The Revenue Room™ is here to help.
To be successful in making revenue a center of excellence, businesses must embrace Revenue Kaizen.
Revenue Kaizen is an incremental method for enhancing revenue outcomes and is essential for continuous improvement in revenue strategies. It involves making small but significant improvements, decreasing waste, gaining buy-in, iterating processes, and encouraging embedded learning and skills development. The importance of revenue kaizen lies in its focus on continuous process improvement, risk-taking, change management, and constant evaluation and iteration.
The journey to revenue excellence is complex and challenging but crucial for business success. Identifying and understanding the red flags, embracing the principles of revenue kaizen, and investing in data transformation and advanced business intelligence help B2B midsized businesses navigate the complexities of the modern economy and move towards becoming data-driven, efficient and profitable organizations. Request a Complimentary Strategy Call
In our first podcast, the CEO of H2K Labs, Heather Holst-Knudsen, talked about data and revenue with Chad Rose, the Managing Partner of Treehouse Technology Group, one of our technology partners. Chad started as a data engineer at S&P, where he learned how to build predictive models and manage data efficiently. With Phil West and Darton Rose, they founded Treehouse Technology Group in 2014 to serve the middle market's demand for better data and analytics. They identified a gap in the BI landscape and developed InsightOut to deliver enterprise-level analytics at an affordable cost. Heather noticed the same issues within the media, events, and business information industry. No data platform truly understood the complex business environment.
While Chad’s experience has been focused on traditional business models, also known as one-sided businesses, there are some similar issues to the event, media, and business information industry. For example, if a SaaS business is focused on recurring revenue you need to monitor, you need to have your head around the metrics impacting that renewal churn, renewals, and AR. Those metrics are in and of themselves often very difficult to report on as so much of the data around that revenue stream sits in different sources. Another example is events, which really are little independent companies. The sales cycle depends on when the event is happening and works like an individual fiscal year you're managing. Finally, mergers and acquisitions are pretty common within the InsighOut customer base, and it's also common in media and events.
According to Chad, these businesses (media, events, and business information) “with so much in terms of data complexity, trying to meet the targets that they're trying to achieve, and with different business units each acting differently, make it harder to get a full picture of the entire business and just to get an ongoing pulse through an analytics implementation.” The data that's being generated is very much outside the CRM in many cases because of customer behaviors or all the people that are connecting with an event or a media customer.
In fact, each of the business units and the brands in those business units really operates like a mini business, with its own P&L, unique fiscal requirements, etc. The data that's being generated holds a lot of value which is being underutilized. It is very overwhelming in terms of figuring out where to start activating the data on the revenue side.
A common misnomer is a lot of businesses feel they can't start an analytics initiative or think they can get anything out of the data. It is often viewed as a linear process where you have to get the data in shape and then be able to start reporting on it or be able to start getting value out of it. You can often do the two in parallel, and they actually reinforce each other if done properly.
Generally, the types of issues in creating an SSOT are not specific to media, events, and business information but are more around the data cleanliness and the data management practices within the organizations, or lack thereof. A lot of organizations are trying to get a better handle on how to input data and get the team, sales team, to input data consistently within the CRM.
However, revenue recognition is a big challenge unique to media, events, and business information. You have these products you're selling, and you have to deliver on what has been sold to recognize the revenue. Businesses need to have a handle on what has been delivered against what's been sold, booked but not yet delivered, those types of scenarios are within any business, but particularly in media, events, and business information; seem to be a pretty big challenge. You have to reconcile what's being done on the operational side against what's been done on the sales side and the financial side. Further, a recurring revenue business model can be pretty challenging, especially if you don't have good systems. Many media and events companies, want people to subscribe to a data product which adds even more complexity to revenue recognition. There hasn’t been a platform developed, until now, that can manage that data complexity.
Another challenge in the industry is product customization, for example, industry sectors they serve, like manufacturing, retail, food and beverage, or life sciences, and how their products are structured. Normalizing the data becomes more complex. These industries also have more systems than most where data might be stored; registration, lead scanning, and ad operations, just to name a few. So there are quite a few potential data sets, and those exist across a variety of systems and business units. It isn't critical to start with capturing all of the data when you're developing a single source of truth. But, "I think that within this space is pretty unique in that there's a lot of untapped potential within all those different data sets that if you can establish, it could be quite beneficial," according to Chad.
The data landscape has changed dramatically, both in toolsets and organizational operations. It's gotten more complex as a business can have hundreds of tools being used for different needs, marketing systems, CRM, sales systems, and finance systems, but you might also have different systems managing your websites or different systems managing your customer engagement, and customer success. And so there are just more and more of those that each company is signing up for and using and leveraging.
From a user perspective, it is great as these tools are highly specialized, from a data perspective, it means data is siloed in many different systems and, therefore, highly unusable. Older business intelligence platforms are not designed to be flexible, you need to have a team of engineers to do the implementation and configuration. However, today, there are many more self-service platforms that are much easier to manage and use. Many of them have integrations using APIs or ways to automatically integrate, and many organizations do not leverage the connections.
Today business intelligence platforms are AI-enabled or becoming increasingly AI-enabled, and they are much faster to get to value and actual successful implementation. Additionally, some elements are even newer in terms of things like reverse ETL or write-backs, which enables businesses to push updates from the single source of truth, from your reporting system back into your source systems.
For the end user, you have aggregated all the data, and for example, you've highlighted some churn risks within the dataset, it is pushed back into the CRM, and the sales team gets notified and can action the issue. Until very recently, this was not possible, or you wouldn't be able to do it without having a big engineering team. As the systems have become open with their APIs, as the technology has become more AI-enabled, the result is organizations can achieve better results much faster, and far cheaper. And you can do so with the modern stack that exists today, versus trying to implement the tools designed in prior ecosystems or prior technology stacks.
In reality, older business intelligence platforms are expensive for mid-market companies. Especially in media and events where the data is complex and lives in multiple layers of platforms. Large organizations can afford to invest in business intelligence solutions, whereas smaller companies cannot. However, that has changed in recent years, in part due to SaaS companies and the availability of products in the market.
The decision of which tools to use is where we see many companies go wrong. They are more likely to purchase or hire the well-known name used by enterprises without understanding the implications and the level of support required to implement those tools. As a result, many companies get stuck and end up with failed implementations of powerful tools that are simply not the right fit.
One of the biggest pillars of successful data monetization is democratizing data. It has to be operationalized and part of the daily flow of work.
One of the assumptions when InsightOut, and now Insightify, was developed is users are not data scientists, not technically trained, and not experts in determining the right key performance indicators (KPIs), or what to do with the data presented to them. Users want the same user-friendly experience in their business tools as they have in their personal tools.
InsightOut was built to simplify the presentation of data and make it less like a dashboard and more like an application. We wanted to strike a balance between flexibility and simplicity. The platform needed to give end users the data they need, when needed, and in a format, they can easily understand and use.
Many analytics solutions have failed because they simply provide a few charts and graphs without solving the automation problem or giving users the necessary answers.
When we built Insightify, we focused on a handful of visualizations business users and executives commonly use: , , and intelligence. These visualizations are highly customizable, allowing users to slice, dice, and display the data in a way that automates data preparation and report generation while providing all the necessary data points.
The level of adoption of InsightOut has been extremely high within the companies that have implemented it, and it has become one of their most popular tools for day-to-day use. The need for exporting data to Excel has significantly decreased compared to other tools that fall short of meeting customer needs.
Over many discussions with clients, Chad has discovered that the role of data science will change. The change is in part due to advances within AI, or the capabilities to interpret data and decipher what's happening within the datasets, which are becoming very powerful. This will inevitably lead to a situation where a business user should be able to log into a system that has pulled in these different datasets automatically, interpreted the data, and is giving you the outliers or the trends or the specific data points you should be paying attention to today, or for this week, or for this month.
There will always be data scientists at the very edge of the development of analytics where they're looking at coming up with brand new ways of determining what's happening or investigating brand new datasets. A lot of companies who share similar business models should and will have the predictive models automated to a certain degree ten years down the road. In the past, if a middle-market company looking to become an enterprise-level company, they would go out and hire engineers to stitch together a bunch of data. Chad doesn’t believe that will happen going forward. He feels the applications will become exceedingly powerful to help enable business users as they intend to make use of this data.
A shared problem across all businesses doesn't matter what type, is that becoming data-driven is a critical imperative if you're going to succeed and thrive in the future. However, it requires financial capital, time commitment, leadership commitment, persistence, and in most cases, significant culture and organizational change. Many times businesses are unable (or unwilling) to justify this level of investment. One of the areas H2K Labs does is help customers define success, identify the business value, and ensure it's measured across the journey. According to Chad, businesses need to start small to become a data-driven organization.
The problem with these types of transformations will only happen and often only start from the executive level. The CFO, CEO, and that level of the executives within the business have to lead change, and they are typically the ones who push transformation, although they are also the ones who might not know or may know the least in terms of technically what's available and what's possible for them to do within their business as it relates to data.
The view is I want to become data-driven. I wanna aggregate this data, or I want to get to some sort of single source of truth. The reality is there are thousand different systems, the team is telling them the data is a mess and not clean. So the perception becomes this is going to be a giant lift, which has to be a giant lift, but it really doesn't. If you approach the goal with that mindset, then you're most likely going to fail.
The solution is simple, start small. Identify the key things which need to take place within the business on a monthly, quarterly basis. If you don't have the technology in place, you're probably doing that manually today. If you're doing that manually, there's a clear ROI to automate that. If you're not automating that, you will be behind very quickly.
You start very small, and you automate what you can within the existing reports. Even within those, you must have a certain eye toward what's worth automating. Then you've alleviated work from your team so they can see the value. You have a working solution that's answering some of the questions you are otherwise getting from manual exercises, and you start to generate some buy-in.
Once you've accomplished the first goal, the team can see a little bit more about what's possible, and they will start asking other questions as to what could come next. And if you take those iterative steps, one-month, two-month types of projects that should get a result at the end of those and you deliver those, then you build that internal support, you clear the ROI threshold, and you can continue to build on each win.
As a senior finance executive, you’re being tasked with finding ways to accelerate growth and increase profits, and a better understanding of data points like cost efficiency and customer acquisition costs are integral to that goal. This is particularly true in information, media, and event businesses - and at marketing service providers that serve them - because data is the lifeblood of your business.
However, in our recent survey of over 100 leaders in the industry, we found that less than ½ of all senior executives have high confidence in the trustworthiness of their company’s data. ⅔ of these executives included CEOs and CFOS. If you and your CEO do not have high confidence in your data, then there is a fundamental issue to tackle.
It begins with a Single Source of Truth for your data (SSOT).
According to Accenture, 76% of CFOs agree that their organization will struggle to meet objectives without one version of the truth across business units.
What is an SSOT, exactly? It is a trusted, unified data architecture and system of management that supports comprehensive, automated financial reporting. It gives finance leaders a place to manage pro forma analysis. Through it, users can clearly see what data has changed, how it was changed, and who made it. Having an SSOT means no longer needing multiple parties to review and validate data sets each time a report needs to be published or shared. Instead, users can feel confident about the integrity of their data, with the information automatically pre-verified.
The Benefits of SSOT for CFOs and Other leaders
One example of data-driven decisions from an SSOT is improving your unit economics to improve profitability. Over 8 in 10 leaders at Information, Media and Event companies believe that challenges with improving unit economics based on analytics will have a significant or very significant impact on growth. The inability to get the data house in order is affecting your growth. You need to synthesize customer data, program data, financial data and other info from disparate sources to do it effectively. Again, it is challenging but very doable, with the right data strategy and platforms. Naturally, we’d be remiss if we didn’t mention Insightify, a data platform specifically designed to meet these and other needs for executives in our industry.
CFOs are Leading the way and Our Roadmap Can Help
In order to minimize the challenges of data management and give CFOs and finance teams access to reliable intelligence, many organizations are moving toward a single source of truth. Increasingly, CFOs are becoming more influential in getting there.
What’s the best path?
Download our E-Book: Achieving a Single Source of Truth: A New Standard for CFOs and Finance Teams.
We’ll take you through what’s involved in the process, drawing from our 30 years of experience with data strategy and data-driven growth in the industry.
Need help?
H2K Labs has developed a data-first, modular, continuous improvement framework to help customers make revenue a core business process and a center of operational excellence.
If you are a CEO, CFO, CRO, or other senior-level executive leading a media, events, and digital information business, you are wrestling with how to meet company goals in an uncertain economic climate alongside a rapidly changing business landscape.
Inflation, market downturn, increasing pressure to transform and evolve business models, growing a team amid talent shortages, and ensuring operational efficiency and effectiveness are all hot topics on the leadership team's agenda.
Even sales behemoths like Salesforce are facing new economic realities where top-line growth is no longer enough. Marc Benioff is now focused on delivering and excelling at delivering "profitable, efficient growth" in response to pressure from activist investors.
In this series, we'll explore recession-proof strategies that will help you maximize profits while reducing risks. No one likes surprises in the boardroom, and we’re here to help you avoid them, no matter what the economic environment. Each strategy should be part of your operating plan and will have short and long-term benefits — as long as the words "sustainable and scalable" are embedded into the discussion.
10 topics we will cover in this series:
Retention is one of the most significant bell-weathers of business health and value creation. While some customer loss is inevitable due to budget cuts, employee turnover, and acquisitions, high levels of churn are clear indicators of possible issues. Customer churn wreaks havoc on the business and costs substantially more than just the lost revenue. The consequences of churn:
Everyone hates churn, but in our business, let's be honest, some of it is inevitable. In addition, media, events, and digital information organizations suffer from being the first on the chopping block when the economy turns sour and marketing budgets get cut.
I like to break causes of churn into 3 categories:
I don't know about you, but I like to spend my time focusing on things I can control, which means I am going to focus on Controllable and Our Own Dang Fault columns.
Controlling churn and retention outcomes is tied to a few common threads:Predictive Data & Analytics > Preemptive Action > Measurement and Accountability > Revenue-Critical Functional Alignment > Leadership & Skills
You should measure your closed/lost deals on the retention side this way. Why? Because knowing what percent falls into what's controllable and what’s not will be very revealing and could give you a clear sense of what you could add to the bottom line if you improved those outcomes.
PS: Don't forget, it's not just enough to retain the logo, you need to also retain and grow the revenue.
I could spend days and weeks talking about how to fix customer churn and boost retention. High levels of customer retention not only indicate robust business health, it also is an indicator that the business is able to support the development of new revenue streams.
Here are some proven approaches to boost your customer retention.
Tip #1: Identify the root causes and leading indicators of customer churn. Sometimes these are intuitive but just not very visible due to lack of real-time data transparency. Outside of the things you cannot control, the usual suspects include underperforming products or contracts, price sensitivity, the level of customer service, and ongoing sales engagement.
Tip #2: Create a Retention Working Group. Define retention broadly, assemble a cross functional team with people at different levels of your organization and give them a clear mandate. Areas to focus on can include:
Tip #3: Using predictive analytics and , connect contract performance data with your renewal, upsell and expansion pipeline. When contract obligations are not being met (whether it is quantity and quality of impressions, leads, meetings, and other curated engagements) your team will get alerts to take action.
Tip #4: Create metrics and compensation incentives for all revenue critical teams tied to retention and account expansion.
Tip #5: Hire and train a ninja Customer Success Team. Customer Success is not to be confused with Customer Service which is really a subset of Customer Success. Develop customer journey plans that include onboarding, training, ongoing value creation and upsell/cross-sell action plans.
Tip #6: Measure, measure, and measure again. Using data analytics, benchmarking and scorecards, track what’s working and what’s not. Iterate and pivot and share best practices across your organization: all brand portfolios and regions. Break out and roll-up results in meaningful ways, e.g. by division, brand, channel and sector etc.
In this economy in particular, reducing customer churn is critical. It is the number one concern among C-suite executives surveyed in our study, 2023 Data-Driven Revenue Growth in the Media, Digital Information and Events Industry. The report from our study will be available in May, request a copy here.
Do you need to improve retention and reduce churn? Request a meeting with me today.
Improving the likelihood of deals closing is critical to getting more output from your sales team(s). Doing it effectively is one part process and one part technology…and data is at the center of both.
By fine-tuning your approach and tailoring your communications for each prospect, you can effectively boost your deal conversion rates to grow your revenue. Most importantly, put predictive and prescriptive data analytics powered by AI and machine-learning into the hands of all your revenue-critical employees so you can identify deal risk and opportunities in time to make an impact.
According to our study of over 100 CEOs, CROs and other executives, 8 in 10 companies are not effectively using predictive analytics to mitigate risks with pipeline traction and velocity. 34% of companies are not doing it at all. Ironically, data is one of the biggest assets of all companies who participated in this study: digital information, media and events organizations, in addition to marketing service providers.
If your competitors are using these methods and you’re not, your company is at a disadvantage. The tools exist to make it happen.
Here are some other important considerations to close more deals:
Tip #1: Adopt conversational intelligence tools to understand customer intent and interests at different stages of the sales process. Connect to predictive analytics and dashboards to identify opportunity and risk.
Tip #2: Dissect objections from prospects, and ensure they are well documented for each account in your CRM. Standardize and carefully manage objection responses, with solid training for your team. Using your data platform, when objections are identified, immediately deal-storm with revenue-critical members of the team to craft the next step of the deal plan. Put metrics in place to measure impact on that deal.
Tip #3: Closely examine wins and losses, and debrief with your sales teams and take action on what’s working and what’s not. Using predictive analytics, create algorithms that identify the potential loss ahead of time to help mitigate and turn into a win.
Tip #4: Personalize communications to each account and, when efficient, every stakeholder. In partnership with marketing and using a unified view of the customer, develop a continuous improvement strategy where prospect and customer communication is constantly tailored using what’s working and getting rid of what’s not.
Our Revenue Acceleration solutions will help you extract more value from current operations while planning for the future. We’ll help you get set up to use predictive and prescriptive analytics to identify deal risk before it happens, with our platform, Insightify. We deliver a rapid time to value, with quick wins and a continuous cycle of improvement – a Flywheel effect.
Each topic should be part of your operating plan and will have short and long-term benefits — as long as the words "sustainable and scalable growth" are embedded into the discussion.
Picture a scenario where you're trying to generate an accurate forecast for your CFO, CEO, and board. Imagine coordinating across multiple divisions, utilizing countless spreadsheets, and investing hundreds of hours from your senior team members. The process is exhausting, frustrating, and ineffective. This situation is unfortunately all too common, and we need to address it.
And unfortunately, once all that time is spent generating a forecast that only looks back, it is no longer a forecast; it’s a “backcast.” It’s truly dead on arrival.
When considering the costs to generate a forecast that is dead on arrival, it gets worse.
Let's consider an average organization with ten divisions. If each division requires 100 hours per month to generate a forecast, at an average rate of $80 per hour, that's a whopping $960,000 spent annually.
And what's the outcome of this massive annual investment? You're left with forecasts that are dead on arrival, missed quotas, unhappy board members, a lack of confidence in leadership, and reduced company valuation.
But there's a solution to this challenging problem. The key is to make data the heart of your revenue center of excellence. The journey to this state of revenue enlightenment may seem daunting, but it's achievable with the right framework.
Before the power of data could be harnessed, forecasting was defined as a method of making informed predictions by using historical data to determine future trends.
With the ability to harness data, train machine learning models, and use AI to forecast upcoming events, forecasting now involves a combination of historical data and real-time changes and trends. Salesperson behavior, customer service behavior, pipeline traction, post-sale engagement, customer behavior, product performance, finance data, and macroeconomic trends all play a crucial role in making accurate predictions.
By integrating these factors, forecasting becomes a robust and reliable tool. It not only predicts future outcomes but also uncovers root causes and provides prescriptive insights to address them effectively.
This approach minimizes risk and empowers data-driven decisions to grow more substantially . It enhances the quality and efficacy of the forecasting process and has a direct impact on the top line.
The world has changed. Customer behaviors have changed. Employee behaviors have changed. What you sell has changed or will be changing. What worked a few months ago is no longer working today. We also have two years of complete abnormality. Using Same Time Last Year and historical data is simply not viable and is getting revenue organizations into trouble.
And frankly, when faced with uncertain economic conditions, not having an accurate forward-looking view into your revenue future could be a mistake hard to overcome.
Predictive forecasting impacts the board, the CEO, CRO, COO, CRO, CMO, and functional heads. It affects revenue teams and individual sellers. It’s critical that predictive forecasting is put at the top of the strategy agenda.
My first piece of advice is to understand two things:
Once that is established, knowing where to start is easy, and we have developed a framework to help you along the journey.
The Revenue Room™ Framework serves as the guiding North Star that encompasses predictive forecasting and simplifies the transition from outdated, ineffective forecasting practices to highly effective predictive forecasting. The four phases of the journey include standardizing and governing revenue functions, reviewing and consolidating data and platforms, and, ultimately, modernizing products. Let's break it down:
The first step is to standardize processes and develop governance across your revenue functions. This involves streamlining your sales processes, standardizing your pipeline stages, and establishing common terminology across divisions. You'll also need to ensure that everyone is using the same CRM and sales tech stack and that you're all measuring success using the same KPIs.
Next, you need to review your systems and the data flowing through them. This involves strategizing and governing data, managing and analyzing it, and improving data visualization and reporting. It's crucial to consolidate your data platforms, democratize access to them, and improve your team's data literacy and skills.
Now, with standards, governance, and a data and platform strategy in place, you're ready to activate data analytics to drive revenue excellence. This means aligning your organization, establishing revenue operations, implementing measurements and insights, and identifying risks and opportunities.. It also means your revenue teams can use leading indicators to improve quota performance, identify deal risk and, immediately activate “deal storming” activities, get alerts to as well as customer expansion opportunities. Revenue-critical teams can collaborate, making winning a team sport.
Finally, as your revenue organization gains momentum and your understanding of customer demands increases, your product team can collaborate with your revenue, marketing, and operations teams to improve product performance and innovate around data. Products can be standardized so data and reporting is meaningful and accessible with a push of a button, unprofitable or loss leaders can be managed or discontinued, and new solutions with high margins and customer value can be optimized.
Putting data at the center of your revenue universe allows you to generate predictive and prescriptive forecasts. This approach allows you to avoid 'Category 5' disasters, make your customers, CEOs, CFOs, board members, and investors happier, and increase your company's valuation.
The most significant benefit, however, is the cultural shift that occurs within your organization. You'll notice an increase in data literacy, shared accountability, and decision-making backed by data rather than gut instincts. As a result, your business becomes more customer-centric.
So, what's your take on predictive and prescriptive forecasting and making revenue a center of excellence? Are you ready to implement the recommended framework and steps to get there? Email me with your thoughts.
I regularly speak with the CEOs of Media and Event companies about their pain points with revenue growth. Inevitably, quota attainment, forecasting, and managing revenue waterfall come up. The wild world of revenue data strategy is even harder when you have to navigate a labyrinth of acquisitions, diverse brand portfolios, and enterprise-wide data asset roadblocks.
Here are some observations about the challenges and steps to overcome them.
1. Embrace CRM Compliance. Let's eradicate CRM sandbagging once and for all. Encourage your sales team to enter all deals, not just the ones they deem "likely to close." This will prevent valuable data from slipping through the cracks and paves the way for more accurate forecasting. Fundamentals like this also forge an easier path for predictive analytics – anticipating revenue risks and opportunities and acting on them proactively. In order to do that, however, you need to follow the Golden Rule of Data: what you put in is what you get out.
2. Look Beyond the CRM. When most leaders think about “revenue data”, CRM comes to mind, but leading indicators that truly move businesses forward also come from other data sources. When aggregating data across the enterprise, expand your data sources to include customer emails, conversational intelligence, audience engagement, input from customer success teams, and product performance. By leveraging this data, you can move towards the 3Ps of forecasting: Precise, Predictive, and Prescriptive.
3. Ditch Excel and Level Up. Excel is a time-wasting vortex that is holding back your organization. Hours, days, and weeks are spent pulling data from it, and much of this work consists of one-off efforts to chase down data for lagging indicators. What’s worse, it doesn’t add value to the enterprise or scale well. There are alternatives to break free from Excel…more efficient, scalable solutions to manage your data across the enterprise and empower your teams to add more value (with surprisingly fast ramp up times). If you’re at a private equity backed company, pay particular attention because value creation drives the PE world.
4. Assemble A Revenue Team. In a world where revenue drivers are hidden in marketing data, customer success data, product data, and beyond, think about how to bring your people in these functions together so they have a seat at the revenue table. And give them a voice. Create a cross-functional revenue team, consisting of business development representatives, account executives, customer service managers, account managers, marketers, content creators, audience specialists, and operations experts. This team should work together to achieve unified company-wide revenue goals. That’s when the magic happens: true alignment. What a concept.
The concept of a revenue team is very nascent, but I am seeing some movement with more progressive revenue leaders.
5. Recognize that Revenue Data Requires Strategy. Most information and event companies have made major investments in audience data: the lifeblood of the business. But more leaders are starting to connect the dots with a broader view of business drivers from their data, and how they tie together. A solid revenue data strategy can improve pricing, reduce “rogue discounting” of sales teams, understand audience value and ROI, and understand the profitability of products, customers, contracts, and sales representatives.
Enterprise data strategy has caught the attention of leaders, particularly CFOs. A true data-fueled revenue strategy can improve customer acquisition, retention, expansion, pricing, and unit-level profitability. Not to mention fewer surprises with forecasts. When that happens, your investors will thank you.
Bottom line, these five steps are fundamental to unlocking the true power of data-driven revenue growth. We’re here to help, no matter where you are in the journey.
H2K Labs will be the new flagship brand focusing on accelerating profitable revenue growth for media, event, and digital information businesses. The focus will lean on the industry experience of the leadership team to help these businesses use data to create lasting value for their company and drive growth on the bottom line.
“When revenue growth is efficient, profitable, and scalable, businesses benefit from adding more percentage points to the profit line. However, data complexities in these industries prevent process improvement, deep customer understanding, risk mitigation, value creation, forecasting accuracy, and ultimately hurt your EBITDA (and valuation),” says Heather Holst-Knudsen, CEO at H2K Labs.
The company also introduced Insightify, the first SaaS data solution purpose built for the media, event, and digital information industries. Unlike other platforms, Insightify was built specifically to help leaders in the industry reduce churn, gain pricing power, identify and manage risks, increase forecasting accuracy and more with predictive analytics.
“Having been an operator myself in the industries we serve, I know very well the pain our customers face when managing revenue data and trying to improve processes and find efficiencies. I am also acutely aware of the challenges our customers face when buying technology, many times having to spend hundreds of thousands of dollars and 9+ months customizing only to be somewhat satisfied with the outcome upon launch. Our goal with the combination of focused advisory and Insightify is to accelerate profitable and scalable revenue growth, increase speed to value, and ensure user adoption and ROI,” says Heather Holst-Knudsen, CEO at H2K Labs.
To develop Insightify, H2K Labs partnered with InsightOut, a data management & analytics solution that fully integrates with modern workflows to empower business users to solve their acute data problems. InsightOut was chosen as the platform offering due to its variety of core features, ease of use for business professionals, and speed to market. This partnership expands H2K Labs' capabilities to accelerate revenue for companies in the industry with a cutting edge, proven platform used by Bain Capital, Sentrics and many other leading organizations.
“Partnering with H2K allows us to accelerate our mission of enabling organizations to realize the full potential of data in a very specific, actionable ways. With H2K Labs extremely deep industry knowledge within the media, events and digital information space combined with InsightOut's technology, they are able to deliver industry leading analytics at an incredibly fast pace. We are extremely excited about this partnership and what we are bringing to this underserved market,” says Chad Rose, CEO at InsightOut.
H2K clients now have access to a broader suite of solutions:
The benefits for our customers include:
About H2K Partners: H2K Partners empowers media, events, and digital information companies to thrive in a rapidly evolving market. With over 30 years of experience, we understand the challenges faced by businesses in these sectors and have developed a data-first approach to help overcome them. Using a blend of AI-powered revenue intelligence, analytics and visualization and real-world expertise, we unlock new opportunities for growth, scalability, and future-proofing revenues. Our team of experts works closely with revenue, finance, marketing, and product leaders to design winning data strategies, modernize revenue operations, and identify high-growth monetization opportunities.
About InsightOut, by Treehouse Technology Group: InsightOut is a unified data analytics platform from Treehouse Technology Group that enables business teams to unlock the power of their data. Business users can extract insights and value from their data at scale, with self-service simplicity. Our end-to-end data solution aggregates, cleans, and blends fragmented data across departments — no matter the data source or volume — within a visual command center. With purpose-built dashboards and intuitive visualizations, users have a 360° view of the business and can independently manage and analyze data at the speed of thought, without reliance on IT. Our valued customers include Envision Healthcare, Dick’s Sporting Goods, Fidelity, Teleflex, Bain Capital, Sentrics, and more.
FOR IMMEDIATE RELEASE:
April 24, 2023Steven CarlisleH2K Partners(442) 274-0556marketing@h2klabs.com
According to our study on data-driven revenue growth, nearly 8 in 10 leaders find it challenging for their companies to gain pricing power. Yet, most feel that doing so will be "very” or "extremely important" to driving profitable revenue growth in the next 12 months.
Something has to give.
Commoditized products and one-size-fits-all solutions are obstacles to overcome. With events, these include square footage, branding and activations and attendee experience. In digital businesses, commodities and all-purpose approaches are found in lead generation, data subscriptions, display advertising, programmatic advertising, and in some cases, content subscriptions.
Regardless of your model, optimizing pricing to reflect the value delivered can be a valuable driver of growth and revenue without incurring additional expenses. However, perceived value depends on the customer segment and the account.
It’s important to find the right leverage points. Leverage can be gained with specific types of customers, offerings, programs and audiences.
To shed light on these leverage points, media, event and information businesses must thoroughly understand:
Let’s review a few examples of pricing power on the sell-side of the customer equation for a company that provides digital advertising and lead generation. (Most of these principles also apply to event companies driven by revenue from exhibits and sponsorships, since they are all about delivering audiences too).
Using algorithms to determine audience value and charging accordingly. Not all leads are worth the same. In fact, the same lead may be worth much more to one sponsor segment than to another.
We suggest using an algorithm that includes five core buckets of data:
These things matter because, to marketers, not all leads are created equally. Some agriculture manufacturers, for example, will pay dearly to reach farmers who are planning to grow more acres of a certain crop next year.
Enterprise software and high tech companies will pay top dollar to reach VP plus titles in critical buying roles that work within specific sectors of the business. SAP’s manufacturing industry vertical wants to find in-market buyers in Cargill’s Industrial Division across the manufacturing, finance, and operations VP functions. But guess what, so do Oracle, IBM, and Microsoft. Demand should drive up price and also provide a barrier to over engagement with a very high quality, sought after lead.
Wrapping existing products with data in the form of insights adds tremendous value for advertisers, exhibitors and sponsors. Data wraps not only allow you to command higher prices and create compelling upsell opportunities, data wraps create new customer experiences, improve satisfaction and increase lifetime value.
Reports, alerts, dashboards, visualizations to complement products and delight customers.
Performance Dashboards: For event businesses, sponsors can improve their lead generation efforts through the right mix of booth space, branding activations, and marketing programs. With real-time dashboards and reports, you can keep a finger on the pulse of performance and gain valuable insights about what works and what doesn't. Invest in timely monitoring of program stats to refine elements that make your campaigns thrive. Dashboards can provide marketers with real-time insights into highly engaged prospects that may also be attending the event they are exhibiting at. Their sales teams can then take action and schedule appointments with prospects most predisposed to meeting.
For digital businesses driven by lead generation and advertising, dashboards on campaign performance, insights on audience engagement, intent, demographic/firmographic profiles and metrics synced with internal data from clients all add value.
Real-Time Data Cleansing & Feeds: Real-time data cleansing and feeds works well for lead generation customers who require things like net new, in ICP/BP target zones, email verification and data mapping to CRM fields. Take this a step further and offer the API to send cleansed leads directly into their CRM in almost real-time. Game changer and customers will pay for it.
Data-Enhanced Lead Generation:, Enhance leads with additional data culled from purchase intent behaviors in addition to structured data fields. Additional data can include scores based on how many people from the company have also visited your website and done similar searches, engagement with competitive assets, and buyer activities such as saving, sharing, and comparing competitive products side-by-side. Think ZoomInfo data but in your owned environment. You can offer lead generation programs in two levels: basic which includes the regular data you provide and enhanced which includes the “extra.”
For event companies, value can be added by providing customers with intent data on attendee engagement and interests:
Let’s dive into the buy-side.
Keynote Speaker Meetups: Who doesn’t like some extra attention? Creating unique experiences specifically for important customers (or attendees) can make a big difference. One approach is to give exclusive access to hear high demand speakers with interactions in a more intimate setting. Content Marketing World is known for its outstanding speakers, but the real treat is the VIP experience where guests enjoy one-of-a-kind speaker interactions with people like Mark Hamill. Not only do they get information that has never before been presented by the speaker, they get to experience it in a much smaller group, offering everyone a chance to have their questions and comments addressed.
Tiered Attendance Levels: One of the best events I ever attended was a sales conference called Outbound hosted by Jeb Blount, Anthony Iannarino, and Mark Hunter. It was back in 2019 and I even wrote a LinkedIn article about it called, It’s All My Fault, which you can find here. What I loved about this event was how smart they were about attendance and getting people to not only PAY more but also how they used onsite FOMO to drive upgrades and attendance commitment for the following year - including payment - onsite.
Three attendance tiers were offered starting at $ 300 and ending at $2,750 (don’t quote me on the exact dollar amount but it was in that range.) The lowest tier gave you access to the general conference and conference networking. The mid-tier provided access to workshops. The top tier, the bomb of all tiers, took this 10X further. And of course, that’s the one I paid for.
The top tier offered me access to:
What made the FOMO so powerful is that this VIP treatment was visible to everyone and you could hear, “how do I get in?” To add some pretty flowers to this already delicious cake, here I am today, still raving about it. When that event resurfaces in 2024, I will definitely be going.
Given that hybrid and virtual events are here to stay, the same philosophy about VIP experiences applies to them too. After an online event, how about offering an extended session with a prominent speaker to marquis sponsors? Doing so can present new sponsorship opportunities and be part of premium packages.
Companies that offer tiered subscription or memberships can also squeeze more revenue from their offerings.
For example, Business insider offers a higher priced subscription that is ad-free. In the B2C world, Tinder is developing an exclusive new dating subscription service that will cost $500 a month, or $6,000 a year, according to Fast Company. The working name is called Tinder Vault, which is being planned as “amplification” of Tinder’s current technology, rather than a completely new segment.
There are many other ways to gain pricing power, and I am happy to brainstorm if you want to share 30 minutes with me over a call.
Companies that invest in understanding the intricacies of power pricing deliver the right value to the right customers. They know how to leverage existing assets to drive that value and how to ensure execution and delivery.
They tend to have higher customer satisfaction, loyalty, and long-term profitability, ultimately setting them apart from competitors who adhere to traditional cost-based pricing strategies.
Most key strategies to increase pricing power are data-driven. Leaders in the Media, Information and Events industry are responsible for creating value by monetizing data. To gain pricing power effectively, you need to know the costs, risks and benefits. However, most platforms do not empower you to do it well.
Our platform, Insightify, is purpose built to uncover insights that can inform pricing decisions and more.
Our Product Innovation solutions will help you extract more value from current operations while planning for the future.
Look out for other topics we are covering in this series.
Upcoming topics:
Dear Heather,
I'm writing from a mid-sized PE-owned B2B media company that needs to realize better margins fast. We generate revenue from traditional revenue streams such as digital advertising, print advertising, demand generation, conference sponsorship, and conference ticket sales.
We recently launched a first-party data solution called Pipeline Pal that allows customers to target prospects based on their ideal customer profile, buyer persona, and data enrichment using a combination of first-party purchase intent data that we generate through site visitor behaviors and third-party data from Bombora.
Pipeline Pal is a vital strategic investment for us. It fulfills new customer demands, boosts customer spending, and enhances our competitiveness. Moreover, it will significantly improve our company valuation upon exit.
Here’s the rub.
Our current process is the following: Lead data is generated and housed across various systems, including Swoogo, Gleanin, Brella, various lead scanning and location apps, Ad Orbit, Google Ad Manager, GoToWebinar, SailThru, CredSpark, Hubspot, Balluun and Omeda.
We manually export, clean, dedupe, and append the data using Google Sheets and BigQuery before uploading it into Looker Studio, where our clients view program results. Enriched leads are delivered via spreadsheet by our account managers. This requires significant human effort, especially the data cleansing and governance that our customers demand. One headcount can handle about 25 accounts, which is not scalable based on our growth projections and required margins and will lead to customer issues and production constraints.
What do we do?
Help!
Flummoxed With Data
Dear Flummoxed With Data,
Congratulations on launching your first-party data solution, Pipeline Pal; it's the right step in future-proofing your media business and improving your company's valuation. However, with most data monetization initiatives, new challenges arise, especially around the tech stack, internal processes, and skill sets. There is a lot to unpack, but thankfully, there are solutions to the multiple issues you describe.
On the one hand, you have the comfort of the known – your current systems, albeit with their limitations, and because you have a private equity partner, improving margins is top of mind. Investing in new technology is not high on the list of investment priorities.
However, without automating the process, improving data hygiene and governance, and handling data more securely, you are putting Pipeline Pal, your customers, your revenue, and your business at risk.
You also do not have the internal skills to develop a system, nor should you. That's high risk, expensive, and unsustainable for a company your size.
The hard truth is that you cannot scale without investing in an off-the-shelf solution. You need an off-the-shelf solution that:
As with any technology investment, there must be a quick time to pay back and a clear understanding of what success looks like. The ROI and cost-benefit analysis I recommend to justify an investment in an off-the-shelf solution combines top and bottom-line impact.
Impact on Customers & Revenue
This is the top priority when it comes to evaluating ROI. How will this investment help my business grow, gain a competitive advantage, and turn sellers and customer success managers into revenue ninjas and value creators versus report generators?
KPIs You Will Want to Consider
CSAT
Measure customer satisfaction before launch. Start measuring quarterly, particularly with customers purchasing demand generation, after launch. Customers benefit from faster ROI, reduced lead management and campaign reporting workload, and proactive campaign performance improvement.
ACV
Measure average and annual contract values to showcase increased annual spending and contract sizes. Customers who invest across various channels (website, email, newsletters, events, custom/sponsored research) achieve higher returns on investments with your company.
Unified reporting and analytics empower sales and customer delivery teams to provide real-time ROI proof to customers. It covers multi-channel and multiple brands.
Win Rate
Measure win rates and how those increase. Measure win rates in competitive selling environments as well.
A distinct competitive advantage is providing customers with real-time automated lead delivery and a unified view of integrated campaign performance.
Churn/NRR
Measure churn as well as net revenue retention. Net revenue retention is a clear leading indicator of churn risk.
Offering unified reporting with automated data cleansing, verification, appending, and enrichment in real-time enhances your contract delivery rate. Real-time leads (within 15 minutes) enable clients to act faster, increasing the likelihood of pipeline conversion, customer satisfaction, and improved retention.
Time to Revenue
Measure sales cycles or time to revenue. By empowering salespeople and custom delivery teams with real-time data, sales cycles should contract improving cash flow and quota attainment rates.
When sellers and customer success teams are empowered with real-time program performance data, they can create value for customers better and sell faster.
A second measure is cost savings and/or resource optimization. With an off-the-shelf solution, you can anticipate needing fewer resources to assemble reports, unify data, cleanse, dedupe, enrich, append, and deliver proof of performance. Those resources can be reallocated to revenue-producing activities and creating customer value.
Employee Headcount in Customer Delivery & Reporting Organizations
How many employees do you have on the customer delivery and data teams to support advertising and demand generation campaigns? How many will you need as you grow and launch Pipeline Pal?
You will need significantly fewer employees to generate and deliver campaign reports to customers by eliminating manual work effort.
Accounts per Customers Delivery FTE
The number of accounts each headcount can handle will increase by automating the full cycle customer delivery journey.
Revenue per Customer Delivery FTE
By transitioning Customer Delivery employees from report generators to value creators and increasing the number of accounts that can be handled per head, revenue per employee will increase.
Once you have considered the off-the-shelf solution, calculated time to payback, and ROI, you will need to evaluate and change internal processes and customer journey mapping and ensure your internal and external stakeholders are not only trained on how to use the platform but also how to optimize and create value through it.
Let me know if you want to discuss specific off-the-shelf solutions we have worked with. I am happy to help with the internal processes and other changes that will be required.
Here to serve,
Heather
PS - May I suggest another name other than Pipeline Pal? It makes me giggle every time I say it.
Have you ever had a “if only I had known…” moment? Of course you have. We all do. From minor details like forgetting to bring an umbrella, to more significant tragedies, like that big family vacation you planned back for March of 2020. There’s a lot of uncertainty in life, and that can lead to some unhappy surprises.
Most of us console ourselves with self-inflicted platitudes like “hindsight is 20/20,” but that doesn’t usually prevent us from wishing we could turn that hindsight into foresight. We put up with the uncertainty because we don’t have any viable, effective alternative.
But that’s not the way everyone does it. Astronauts don’t launch with their fingers’ crossed, for example (“That’s not how we deal with risk,” Chris Hadfield once put it). And the adage “No strategy survives first contact with the enemy” never stops military operations from attempting to prepare for, and manipulate, the outcome of every engagement.
Which begs a few questions. Namely, are we “guessing” more than we need to? Is there a way to anticipate future outcomes better than we currently do? And, if improved forecast accuracy is possible, how do we achieve it?
Dear reader, welcome to the wonderful world of predictive analytics.
First, an answer in brief. An overview for all you “Too Long; Didn’t Read” enthusiasts, if you will.
Your business generates a veritable dragon’s hoard of data on a daily basis. This includes data from customer interactions, market engagement, internal operations, revenue and financial metrics, and a whole lot more. And, if you operate in data complex environments such as media, events, marketing and business information sectors, multiply your data asset by three.
This data can do more than just visualize the ebb and flow of recent bookings, billings, cash flow and profitability numbers.
It can highlight historical trends, identify less obvious points of success or failure, and—most importantly—help analysts develop predictive insights. Such “leading indicators” are the ultimate goal: allowing businesses to anticipate outcomes based on past and current circumstances.
In short: predictive analytics can do for your business what a medical examination can do for a patient. By taking “vitals” and comparing them to both category averages and personal history, future diagnoses can be foreseen and prepared for. For both examples, this can lead to increased longevity, better health, and optimized performance when implemented correctly.
The key is knowing how to go from “scheduling the physical” to “clean bill of health.”
Ok, we’ve established that data can drive effective decisions that properly address risk factors and capitalize on opportunities. However, raw data doesn’t, by itself, directly translate into winning business strategies. Just because you have a spreadsheet full of revenue data doesn’t mean you’ll be hitting every target from this point forward.
Even in military contexts, hitting a target isn’t always as simple as taking aim and pulling the trigger. In fact, military terminology distinguishes the use of weapons and munitions based on what you’re firing at, and whether you can see it:
Why are we throwing around military terms in an article about predictive business analytics? Because, like poorly aimed artillery, businesses that make decisions without accurate data are effectively launching large chunks of budget and resources at the wrong targets, often overlooking crucial but unseen objectives.
Now, while militaries across the globe have been developing and refining their targeting systems for decades, businesses have only just started to benefit from the analytical equivalent of satellite imagery and laser-guided targeting. Digital technologies have made certain realities possible before professionals knew exactly how to use them for those purposes.
Business analytics implementation happens on a bit of a spectrum. At one end, teams may be so in the dark about their own data that they don’t even know where to find it all, let alone start collecting it. As organizations become more data-aware, they may seek to aggregate their information, perhaps even standardize it into a Single Source of Truth (SSOT).
Virtually every business faces issues with data integrity, though. Inaccuracies, redundancies, incompatibilities, and formatting issues all prevent the data from being properly organized and utilized. That leaves a large gap between brands that are data-aware and those that are data-driven, and crossing it can prove prohibitively difficult.
Again, this is something that militaries have dealt with for ages. The term “fog of war” refers to the obscuring uncertainty created by the inherent chaos of the battlefield. Without reliable intel, the fog of war prevents commanders from knowing where resources and threats are positioned, where they’re going, and how to properly direct efforts to turn circumstances to their advantage.
What’s true for military leaders is true for senior business management: it’s virtually impossible to manage or prepare for what you can’t see.
Gaining data awareness is the first step toward converting analytics from a diversion to a secret weapon, but it’s not the only step. You can’t simply print off a satellite photo and hand it to an artillery crew as a “firing solution.” And you likewise can’t hand a database full of yet-to-be-scrubbed information and expect your analytics team to turn it into prophetic industry forecasts.
On the other hand, processing the data by hand to normalize it is a fool’s errand, especially if your end goal is real-time insights.
To get what you want out of the data and your staff, you need something to amplify the power and impact of both. You need a force multiplier.
Here is the final caveat; “the rub,” as they say. Different organizations and different industries have different requirements for their analytics tools.
Some teams can be served perfectly well by the major players in the BI space, and more or less use the solution right out of the box. But some businesses have data environments too complex for these providers to adequately serve.
Media companies, event organizations, marketing service providers, and similar enterprises with complex data environments typically need a number of functions that standard business intelligence platforms don’t offer.
For teams that need to accommodate two-sided business models, complex client databases that require external-facing access, or even simply reporting tools that can turn 30 different marketing and sales enablement channels into a single revenue report, more specialized tools are needed.
Should you offer discounts or toss in a free value-added program to customers? In the old days, the right answer was, “Yes, customers expect it.”
Today, depending on the sophistication of the revenue organization in the business, the answer ranges from “it depends,” to “only in very select cases.” While discounts still play a role in negotiation and driving up close/win rates, it is crucial to eliminate value-add from the narrative. More on that below.
“If you have a 30% margin, and you give a 10% discount, you have to sell 50% more business to make the same profits.”
Media and event businesses must strive to grow the top-line by leveraging existing resources or, more ambitiously, by maximizing productivity while minimizing costs. Couple that with cost inflation from materials, technology, labor, travel, shipping, food & beverage, A/V, and venues, discounting and value-add are not friends of the business.
In fact, a new more urgent discussion is taking place at forward-thinking events and media companies: how to gain pricing power, not how to erode it.
The friction between commanding higher prices for what we sell and discounting so we can close a deal creates a pretty interesting conundrum.
So how do you create more value and command higher prices while also managing discounting? How do you ensure that the old strategy won’t cannibalize the new one?
In a well-governed revenue organization, discounting programs are carefully structured, documented, and transparent to both customers and sales teams. Smart sales and finance leadership teams monitor these programs closely using data. It is acknowledged that every dollar lost to discounts is a dollar that is subtracted from the margin. Moreover, the discounted amount still demands resources and cash be delivered to deliver the value promised to the customer.
"Well-governed revenue organizations understand that mismanaged discounting destroys profits more than anything else." - Every CFO on the Planet
Before I go into an example of governance and how to use data to monitor and measure, I need to make a personal plea.
Discounting can be a viable strategy if managed and monitored well. I hold an entirely different opinion about value-add. The value-add provision is a malevolence that must be expunged from all contracts as it unfailingly leads to unsatisfactory outcomes, reduces unit-level profitability and in some cases, materializes in a loss. I believe that anything given for free holds no value to the receiver of the value and as such, should not even be used to help drive demand for new products and solutions. Let’s ban value-add forever.
“Value-add is the contract nuisance of the media and events industry. It destroys value and never delivers what it promises.”
For the sake of brevity (am I ever brief?), I will give one example of discounting governance and how to use data to manage, monitor, measure and assess.
Customers could be offered discounts based on contract size.I am 50-50 on this and I imagine that it depends on the market you operate in. If value has truly been sold to me, am I really going to increase my spend because you are offering me a spend threshold discount? Not sure. But if the discounting program is offered, have strict governance around:
The word “scaled” is also important and should mean two things:
For example, if you offer discounts once a company hits 100K in spend, you would not discount the first 100K, OR the discount on the first 100K is minimal while the attractive part of the discount hits on the 101,000 spend mark. Why? Because in many cases in media and events, contracts can be canceled at any time and you wind up holding the revenue slippage.
From a data perspective, this means your CRM, order systems and financial systems need to allow for discounting types and you need to have the ability to have an historical look-back across pipeline stages and changes in dollar levels and discounting types offered throughout the selling period. In the latter case, your CRM can’t help you and most business intelligence platforms can’t either. I am inserting a shameless plug here- Insightify by H2K Labs Ping me if you want to chat about it.
Using data analytics with predictive insights, create dashboards that tell you:
I have lots of opinions about discounting and value-add. Kill value-add once and for all and create a highly governed discounting program that can be managed, evaluated, and measured using data.
Challenge the old school status quo and get rid of frequency discounts especially on digital advertising. Don’t discount lead generation programs because this is where pricing power lies. If you are not selling monthly subscriptions, don’t offer “pre-pay” discounts either. And, for the love of all things heavenly, do NOT let sales reps offer discounts “just because.” It’s killing your business.
And of course, please use data. All the time.
Recently, H2K Labs hosted the first Revenue Room™ Bootcamp focused on developing a single source of revenue truth in complex data environments. I invited Chad Rose, the CEO of Treehouse Technology Group (the developers of Insightify by H2K Labs, to join me and add more depth to technology and data-related discussion points.
The Revenue Room™ Bootcamp covered:
Many companies think of themselves as data-driven. Many have invested in business intelligence technology and have hired data science teams. Despite these investments, many are still manually creating reports, do not have a single source of truth, and have not operationalized data across the organization. Revenue is being left on the table, and unnecessary money is being spent.
In industries like marketing services, encompassing media, events, digital information, and marketing intelligence, it becomes evident that the problem runs deeper.
Today, if you're going to compete and thrive, becoming truly data-driven is a critical and vital part of your strategy. Data is the driving force behind all business decisions made today. Many organizations acknowledge that they need data. However, they don't structure their processes around using data effectively. Many companies silo their data, with each department operating with separate data and without communication. This results in massive inefficiencies and losses in revenue.
The answer to this problem is a data transformation strategy. And that has to start with developing a single source of truth.
A single source of truth (SSOT) is when all company data can be found on a centralized platform. At H2K Labs, we emphasize a subset of SSOT called a single source of revenue truth or SSORT. An SSORT strategy keeps all data connected to customers and revenue on a central platform.
The more complex your data asset is, the more key information can be lost due to a lack of communication and inefficiency. To acquire, retain, and grow revenues in a scalable and profitable fashion, revenue organizations must have an SSORT strategy at the center of their data strategy.
In industries with high data liquidity and complexity levels, as exemplified by media, events, and , developing a single source of revenue truth requires unifying, cleansing, connecting, and blending data from inside and outside the CRM. It's no small effort. However, the benefits include:
An SSORT strategy enables real-time value creation, data-driven decision-making, and waste reduction, enabling smoother operations and more efficient resource allocation.
Maximizing the effectiveness of an SSORT strategy requires balance. Organizations with large and complex data sets must be intentional with the data they utilize. Executing an SSORT strategy isn't a one-time solution. It requires continuous improvement and evaluation to ensure the right data is not only collected and normalized but blended and curated to drive the insights required to achieve results.
A few landmines discussed during the Bootcamp included:
And there are more.
The group also discussed the importance of data democratization. Empowering all functional team members to use data to make decisions as part of daily workflow not only improves business outcomes but organically develops data literacy and skills.
Studies, like the HBR 2023 Study for Google Cloud, show:
The ultimate purpose of an SSORT strategy is to increase efficiency and maximize value creation.
To achieve a successful SSORT strategy, the following platforms and tools are required:
These tools will help organizations save time, simplify the complexity of calculations, and provide support to staff.
In environments with significant data complexity, your goal should be to uncomplicate the data stack and find end-to-end solutions that offer Tesla-level capabilities and are built for business users like Insightify .
The strategy of winners is to capitalize on the data surrounding revenue, customer segments, product formats, brands, divisions, and distribution channels. An SSORT strategy will enable continuous value creation, increased profitability, and operational efficiency.
Is your business ready to transform revenue growth and improve profitability through data-driven strategies?
Please join us in The Revenue Room™ for our next Bootcamp, Using Predictive Analytics to Manage Risk and Capture Opportunity, on September 21, 2023, from 12-1 pm EST. We will discuss how predictive analytics is a valuable tool for revenue generation.
Recently I had the pleasure of moderating a panel discussion on data-driven revenue growth at the 2023 JEGI/Clarity Media and Technology Conference which took place on April 24th in New York City. Speakers on the panel included industry leaders Paul Miller, CEO of Questex, Lisa Hannant, Group CEO of Clarion Events, and Matthew Yorke, CRO of Foundry.
Here are some key takeaways from the panel, which also covered key findings of our recent study, The State of Data-Driven Revenue Growth in Digital Information, Media and Events, conducted in partnership with JEGI/Clarity.
Although these companies have different mixes of revenue streams ranging from digital media, events to lead generation and data subscription services, they all are all finding new ways to use data to drive growth. And, their private equity partners have similar expectations when it comes to business performance and health.
Our panelists’ companies are focused on reducing churn. According to our study, 71% of industry leaders feel that lowering customer churn will be a very or extremely important driver of growth for their company over the next 12 months. Yet, 8 in 10 say that doing so is challenging for their organizations.
How leaders on our panel are using data-driven approaches to improve customer retention.
91% of leaders in information, media, and event companies face challenges in identifying & mitigating revenue risk before it happens
In our study, 62% of industry leaders said that identifying and mitigating revenue risks before they happen will be very or extremely important to their company’s growth in the next year. However, 9 in 10 felt that doing so was challenging for their companies.
The leaders on our panel are finding ways to make it happen.
For example, Foundry uses a global instance of Salesforce to gather accurate data and predictive analytics, identifying upsell and cross-sell opportunities. This approach enables prescriptive advice for salespeople and insights into customer buying patterns. To be proactive, they monitor margins and KPIs, aiding in decision-making about which products to discontinue or promote based on the velocity of sales and gross retention.
Some say that “predictive analytics” is our middle name at H2K Labs (although that would be a mouthful). Our Insightify platform, purpose-built for complex data needs of two-sided business models, helps companies in our industry leverage data across CRM, financial systems, CDPs, marketing automation, customer success, inventory management, event technology AND many other systems to grow revenue and address risks before they happen.
By adopting these strategies, leaders can position their organizations for success in an increasingly competitive and data-driven business landscape.
FOR IMMEDIATE RELEASE: August 28, 2023
Sherri Windsor
H2K Labs
sherri@h2klabs.com
H2K Labs has formed a partnership with Channel Metrics, a cutting-edge data management platform designed to streamline reporting and client delivery across digital advertising, email marketing, lead generation, event marketing, and membership acquisition. The platform marks the second strategic partnership secured by H2K Labs, aimed at empowering clients to grow revenue, minimize costs, and enhance overall business value.
Many companies rely on disconnected systems to generate leads and contacts, and these systems rarely connect elegantly. This is especially true for brands with two-sided business models: membership communities, event management, marketing service providers, and business information brands. Faced with increasingly strict lead governance, and declining rates of satisfaction and retention, these teams spend an extraordinary amount of time and labor cleansing, enriching, and deduplicating the contacts they send to clients. Worse still, regulatory environments (GDPR, CCPA, etc.) force agencies to add compliance costs to their overhead or face the consequences.
Channel Metrics is a web-based unified data management system designed specifically to tackle these challenges. By blending, enriching, and deduplicating data from disparate systems and presenting it in an intuitive interface, Channel Metrics helps brands dramatically reduce the costs required to meet the demands of their clients. Users can generate comprehensive, accurate reports for customers, covering everything from digital advertising, to lead generation, to event sponsorship. The solution enables automation of lead governance, data scrubbing, and analytics, all of which can be customized to be unique to each client.
Purpose-built for the two-sided delivery model, Channel Metrics eliminates the need for manual workarounds and never-ending spreadsheets. By implementing intelligent APIs, users can automate efficiency-stifling tasks, freeing up valuable human talent for more nuanced responsibilities. And, with real-time dashboards and CRM integrations, Channel Metrics can empower brands to deliver contact and lead data faster and with fewer errors than ever before. Finally, data is encrypted both at rest and in transit, ensuring information privacy and global compliance.
"We selected Channel Metrics as our partner because it perfectly aligns with the industries we serve. Witnessing Channel Metrics in action, I instantly recognized its potential to save our customers substantial costs and data errors in creating customer reports and generating leads each year. By consolidating advertising, lead generation, email, newsletter, and event performance data into a unified interface in real-time for sales and customer success teams, it revolutionizes the game. Furthermore, its lead automation module offers functionalities such as cleansing, verification, enrichment, deduplication, and governance, along with near real-time delivery. The resulting cost savings and enhanced customer value are not only compelling but also easily quantifiable," explains Heather Holst-Knudsen, CEO at H2K Labs.
"We are thrilled to collaborate with H2K Labs on this partnership," said Channel Metrics CEO, Peter Thomas. "Heather and the H2K Labs team have a proven track record of delivering solutions that drive demonstrable ROI for their clients. We're confident that together we will build on that success.”
The benefits for our clients include:
In the battle for revenue growth, H2K Labs is the force multiplier two-sided businesses need to achieve sales increases, cost reductions, and profitability gains. We empower companies with high levels of data complexity and liquidity to thrive in a rapidly evolving market. As veterans in data-driven revenue strategy with over 30 years of experience, we understand the challenges faced by our clients and have developed a data-first approach to help overcome them. Using a blend of AI-powered revenue intelligence, analytics and visualization, and real-world expertise, we help our clients unlock new opportunities for growth, scalability, and future-proofing revenues.
Channel Metrics is a unified management platform that blends, enriches, and deduplicates data from disparate systems and presents it in an intuitive interface for event managers, marketing agencies and their clients.
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Join us as we dive into the dynamic world of home improvement, data, analytics, and revenue growth with insights from an industry leader. Listen now and stay ahead of the curve! 🎧
By leveraging data and analytics, we're not just connecting homeowners with top-notch contractors but also partnering with lending institutions to streamline the financing process. 💰
Imagine this: You upload a photo of your kitchen, and our platform not only tags products to help you envision your dream space but also offers the Home Mag Dream Card, supported by our banking partners, to finance your project seamlessly. 🏡✨
Our mission is simple – to clear the path and facilitate a smooth, enjoyable experience for our customers. We don't sell leads; we sell facilitation and connection, sparking creativity and empowering homeowners on their renovation journeys. 🌟🔧
● Data, Digital and Business Value from a Revenue SSOT Strategy
● Revenue Data and Where it Sits
● Right Data In/Right Data Out
● Platforms & Tech
● Data Operationalization, Adoption & Governance
Participants will explore six core sessions:
This LunchLab format, produced by Revenue Room Connect, a new professional network and collaborative learning platform by H2K Labs, offers a rapid learning experience architected for C-Suite leaders. Executives will gain actionable insights and strategies to immediately enhance their data-driven revenue operations.
LunchLab’s actionable insights will help you unlock:
Developed by H2K Labs for revenue-focused leaders, the playbook introduces The Revenue Room™, a pioneering framework designed to tackle high levels of data complexity and drive transformative change within revenue organizations. The playbook is particularly useful for multisided business models: media companies, event organizers, business information providers, marketplaces, and marketing agencies seeking to modernize their revenue strategies.
Information, media, and event companies spend thousands of hours managing their data annually.Data is invaluable, the lifeblood of the business. For finance teams and chief financial officers, it’s an essential component of your work. Whether it's using historical data to understand financial forecasting or compiling data points for reporting purposes, the accuracy of the data you rely upon is paramount. However, despite the power data holds, managing it can be a drain on resources. Fortunately, there are solutions.
In order to minimize the challenges of data management and give CFOs and finance teams access to reliableintelligence, many organizations are moving toward a single source of truth. Increasingly, CFOs are becomingmore influential in getting there.
Since data is the lifeblood of businesses in the media, information, and event industry and the service providers who support them, we surveyed industry leaders about their challenges and usage of data to drive profitable revenue growth. The study, conducted in April and May 2023, collected data from over 100 company executives covering all facets of B2B and B2C media, information, event, and marketing service providers. We also included in the survey a selection of investors, private equity, and venture capital firms to gain their perspectives and views on this industry.
Questions We Asked:
With AI and machine learning infiltrating their way into every aspect of business these days, it’s easy to understand why the promise of “seeing the future” is so tantalizing. If the hype is to be believed, predictive analytics can offer a level of foresight that was previously considered fanciful at best.
To be fair, not all analytics are created equal, and even supposedly “predictive” business intelligence might produce forecasts less accurate than the local weather report. But it doesn’t have to be that way. In fact, when implemented properly, predictive analytics can do more than just anticipate. It can activate.
