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.  

• The benefits of becoming gaining a seat at the revenue table
• Ensuring the marketing strategy is aligned with revenue goals
• Empowering sales marketing to work with account reps to improve outcomes for deals
• Delivering quality leads to the programs sales is selling
• Reporting on metrics that matter
• Identifying gaps with data

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 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.

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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.

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Don't believe me? 

Identifying Critical Gaps in Data

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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:

• On average, for a lead generation campaign, how many of the accounts were met with 90% or better-accepted leads?
• For email ads, what is the average click-through rate for advertisers vs. other content?
• For website, what is the average click-through rate for ads? Sponsored content? Etc.

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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.

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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. 

My Aha Moment

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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. 

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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. 

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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.

• Attendee product interests did not always match exhibitor product categories
• Key companies exhibitors wanted were not always there in large numbers, if at all
• Key companies attendees wanted to see were missing
• Assumptions about who the conference attendee profile were wrong
• When a person registered - it directly impacted their attendance at the event

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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. 

Shifting the Strategy

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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.  

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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. 

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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. 

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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. 

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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. 

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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. 

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In my next blog, I will focus on using this data to advance your team and align them with sales.

Until next time!

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.

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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:

• Uncover Hidden Gems: Analyze data within and outside the CRM to reveal hidden opportunities to grow revenue and potential risks tied to customer churn
• Boost Efficiency & Empower Teams: Automate reports and equip your team with self-service dashboards to free up time and produce consistent value creation for customers.
• Make Everyone a Value Creator: Empower your team to make data-driven decision-making a part of the daily flow of work. 

Want to learn more? Request a complimentary call today.

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5 Critical Data Levers To Predict Customer Churn & Improve Forecasting

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1. Program Performance
2. Client Insights & Engagement
3. Customer Interactions & Behaviors
4. Sales Team Behaviors
5. Payment Terms

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.

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ONE: Program Performance

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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

• You should know your advertising benchmarks. How are the clients’ ads performing relative to those benchmarks? How are they performing by client segment, ad format, content adjacency, and channel?
• You should also know the benchmarks for this specific advertiser. How are the ads performing relative to those benchmarks? Are you hitting quantity, engagement, and targeting expectations? If not, what prescriptive actions can you take to improve? Or are you overdelivering? And if so, at what expense to other advertisers with similar goals?
• If your client’s ad performance is tracking ahead of your benchmarks and their specific goals—that you likely committed to the advertiser when you sold them—the likelihood of them returning increases. 

Demand Generation

• Demand generation is a complex program for a few reasons. Clients have specific ICPs and Buyer Personas they want to reach. Clients also have data governance rules that impact whether or not they will accept (read: “pay for”) leads.
• Quantity counts for demand generation programs also have to occur within a specific period to correspond to the client’s top-of-funnel KPIs by month and quarter.
• If you are not hitting all cylinders, you will undoubtedly experience revenue leakage, including delayed renewal time, reduced revenue from an existing contract, and customer churn.
• If you are hitting on all cylinders, it’s a good time to talk to your client about other ways to optimize the campaign or add a new one.

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TWO: Client Insights and Engagement

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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. 

• If you offer dashboards and you have a set of clients that are not using them, that group of clients requires extra TLC to ensure they are engaged with the ROI and results of their programs consistently. 
• If your partners are not logging into the dashboard nearly as much as they used to, it could be a sign that they don’t value this particular marketing campaign nearly as much or that there may be a change in job role with one of your most important campaign influencers
• On the flip side, if there is a flurry of activity and an increase in users viewing the dashboard, that could be a signal that they are evaluating new campaign investments and need assistance in guiding them.

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THREE: Prospect & Client Behaviors

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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.

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• In the world of events, there are many signals that happen well before the prospect lets you know they are evaluating your brand as part of their event marketing strategy. Those signals include checking out who else is sponsoring, looking at last year’s event site, viewing the agenda and speakers, and conducting searches for specific event content. All those signals should be captured—for prospects and clients—to identify new business acquisition and upsell/cross-sell and expansion opportunities.
• Feedback surveys are often lost in the ether and that feedback can have a direct impact on a churn risk or expansion opportunity some text
  • You send a survey to the client asking them to rate their engagement with you from 1-5, and they give it a two. That’s a sign that the campaign isn’t working.
  • The inverse of the above bullet is that they give you a 5. That’s a sign that the campaign is working, and there may be a chance to upsell them on other things.

• For clients and prospects, engagements with sales and adjacent revenue teams contain very important signals that often do not get captured in the CRM or the forecast. A few examples include:some text
  • On a call, the client says, “our sales team is having a hard time getting any of these leads on the phone.” That’s a sign that the campaign isn’t working.
  • The client or prospects stop responding to emails that are connected to a renewal or a new deal
  • The client or prospect uses price sensitivity language often within an email exchange. Examples include: “too expensive,” “discount,” and “better deal from XYZ competitor.”
• Much of this data cannot make it back to the CRM, so you need a system that sits on top of your CRM and can easily and cost-effectively aggregate, cleanse, and make sense of the blended data sets. This requires a data intelligence and visualization platform that can do those things in real-time and also add machine learning and AI. 

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FOUR: Sales Team Activity Levels

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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. 

• There are salesperson patterns that you can identify and monitor, such as the average number of sales calls, emails, and proposals generated per week. If you see a significant deviation from those behaviors, something is up that you need to investigate
• How often is your team talking with the client? Are those engagements simply emails, or are they getting on the phone with them?
• If they are getting on the phone with them, are they helping to contextualize the data coming from that dashboard and pushing them to use it more?
• Additionally, is the sales team leaving that call with a next step? Is that next step connected to KPIs such as wallet share growth, new customer acquisition within target account segments, and expansion across brands and channels?some text
  • For some companies, that might be new products that you’ve launched.
  • For large, multiple vertical brands, there might be cross-selling capabilities that unlock tens of thousands of dollars.

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FIVE: Purchasing & Payment Patterns

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Most clients have purchasing and payment patterns, and deviations from both these patterns are often overlooked as significant risk signals. 

• Some clients take 20 days to sign a contract because of their internal processes, while other clients may take 5 days. 
• Large clients may have 60-day payment terms, and others may be excellent at paying invoices within 5 days of receiving them regardless of payment terms. Deviations from these patterns are indicators of risk that should be red-flagged and actioned. 
• Root causes of these deviations can range from cashflow problems, change in job role, or dissatisfaction with the program that is not being communicated (or is and the salesperson is not communicating internally).

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:

1. Speedier, more impactful decision making
2. A customer-centric approach across all revenue-critical functions
3. Prioritization of deal focus for individual contributors, sales managers, and coaches
4. Improved seller performance, quota attainment, and earnings
5. Accelerated revenue growth and profitability

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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:

• Uncover Hidden Gems: Analyze data within and outside the CRM to reveal hidden opportunities to grow revenue and potential risks tied to customer churn
• Boost Efficiency & Empower Teams: Automate reports and equip your team with self-service dashboards to free up time and produce consistent value creation for customers.
• Make Everyone a Value Creator: Empower your team to make data-driven decision-making a part of the daily flow of work.

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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.

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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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1. Investor-Centric versus Customer-Centric Approach
2. The Informa Paradigm
3. Defining the Correct Customer Journey
4. The AI Conversation (always there, no way out)

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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.

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Investor-Centric versus Customer-Centric Approach

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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.

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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. 

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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.

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The Informa Paradigm: A Leap into the Modern Media Ecosystem

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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. 

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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.

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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.

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Simply reading TechTarget’s homepage content is all you need.

But then scroll down a bit further…

And finally, voila!

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Imagine:

• Connecting all that purchase intent digital data to in-person event behaviors to improve customer funnel outcomes
• Identifying who are the most likely high-value attendee targets to convert and where they are most likely to convert?
• Produce rockstar-level hosted buyer programs using precise, real-time buying signals

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Defining the Correct Customer Journey

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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.

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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.

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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.

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Leveraging AI to Deepen Engagement

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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.

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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.

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The Road Ahead

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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. 

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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.

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What is bad data and how does it impact your business?

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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.

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The financial repercussions of bad data

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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.

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The operational challenges caused by bad data

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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.

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The importance of data quality control measures

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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.

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How to identify and rectify bad data in your business

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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. 

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The necessity of prioritizing data integrity in your organization

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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.

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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?

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Data: The Lifeblood of Modern Business Operations

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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.

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The Challenge of Data Sprawl

• Definition and Scope: Data sprawl refers to the proliferation of data across disparate systems and environments.
• Statistics: According to a study by Varonis, the average company manages 17 petabytes of data, with 58% classified as "stale".
• Contributing Factors: The rise of cloud computing, mobile devices, and remote work has led to data being scattered across multiple platforms, increasing the risk of data breaches and complicating data governance.

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. 

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Visibility and Compliance in Data Management

• Lack of Visibility: An IBM survey reveals that 61% of organizations struggle with maintaining visibility into who accesses their data and how it's used.
• Consequences: Poor visibility can lead to insider threats, unauthorized access, and data misuse.
• Regulatory Challenges: As data privacy regulations like GDPR and CCPA evolve, the average cost of non-compliance can reach $14.82 million (IAPP report).

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DATA: Control, Governance, & Compliance

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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.

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Strategies for Effective Data Management

• Proactive Measures: Conducting comprehensive data audits to identify all data sources, repositories, and access points is crucial.
• Technological Solutions: Investing in data management tools like DLP solutions and IAM platforms enhances real-time visibility and security.
• Importance of Data Governance: Prioritizing data governance helps mitigate risks and ensures data remains a strategic asset.

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Beyond Traditional BI: Harnessing Modern Data Management for Competitive Advantage

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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.

The Limitations of Traditional Business Intelligence

• Inadequacies: Traditional BI tools, designed for historical data analysis, lack the agility needed for today's dynamic business environment.
• Technical Barriers: These tools require extensive technical expertise, which can hinder collaboration and limit usability for business users.

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.

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Embracing Modern Data Management and Analytics Platforms

• Advantages: Modern platforms offer intuitive interfaces, self-service capabilities, and advanced analytics, empowering business users to derive actionable insights without dependency on IT.
• Benefits: Leveraging real-time data analysis and predictive capabilities allows businesses to adapt quickly to market changes and capture new opportunities.

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Modern end-to-end data management & analytics platform

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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! 

• Complete 360° view of your business
• Data Warehousing, ETL/Reverse ETL, Machine Learning/AI, Reporting, Analytics, Visualization
• Purpose-built for business users and self-service reporting and dashboard customization
•  Fast, bespoke implementation
• Architected for media, events, business information, marketing services, and adjacent SaaS solutions

Are you ready to get revved up? H2K Labs can help. We have strategies to help you drive growth, innovation, and profitability. Power your revenue growth – contact us today to learn more!

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