How to Use Data to Mitigate Advertiser Churn & Grow Revenue
This is a special edition of A Media Operator, sponsored by H2K Labs. 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Businesses seek revenue predictability, yet traditional forecasting relies on subjective, often outdated CRM data lacking crucial insights.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:
- 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.
5 Critical Data Levers To Predict Customer Churn & Improve Forecasting
- Program Performance
- Client Insights & Engagement
- Customer Interactions & Behaviors
- Sales Team Behaviors
- 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.
ONE: Program Performance
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.
TWO: Client Insights and Engagement
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.
THREE: Prospect & Client Behaviors
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.
- 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
- 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:
- 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.
FOUR: Sales Team Activity Levels
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?
- 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.
FIVE: Purchasing & Payment Patterns
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:
- Speedier, more impactful decision making
- A customer-centric approach across all revenue-critical functions
- Prioritization of deal focus for individual contributors, sales managers, and coaches
- Improved seller performance, quota attainment, and earnings
- Accelerated revenue growth and profitability
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.
