How CMOs Can Learn More From Their Data

Every CMO (chief marketing officer) knows that data is everything—especially in account-based marketing. The right data unlocks the most effective plays, campaigns, and insights into measuring the funnel. All of which drive growth for their business.

It’s all in the details, and more often than not, their attention to data is what’s secured them a seat at the leadership table in the first place. Along with that seat comes high expectations and a whole new set of challenges. After all, with great power comes great responsibility.  But, What more can they learn from their data to continue to deliver results? How can CMOs become more data-driven and actionable leaders, especially in a market downturn?

4 Ways Marketing Leaders Can Get More from Their Data

Collecting the data is just one step in the process. To put that data to work—and earn efficient wins—CMOs must know the difference between the data that demands their full attention and the data they can afford to deprioritize.

Here are a few ways CMOs can get more from their data.

1. Use marketing technology wisely 

Running the numbers without a well-thought purpose muddies the decision-making process.

To realize the true benefits of ABM—prioritizing accounts with the highest chance of closing—CMOs need a plan. That means putting data in context, not taking it at face value. It also means thinking about how you’ll:

  • Judge the success of programs via conversion rates and KPIs
  • Gauge the quality of digital marketing analytics data output
  • Determine the success of marketing analytics
  • Analyze marketing campaigns

For marketing teams with big tech stacks, this will also mean making sure your systems can talk to each other enough to make data collection count. Seven out of 10 marketing leaders plan to invest more in marketing technology to help reach their revenue goals, per a June 2022 report by CMO Council and KPMG.

Marketing technology (MarTech) is the most crucial and major purchasing decision for CMOs. They need MaTech to justify investments and prove revenue growth. Not only that, but realizing the full potential of your MarTech (including fostering alignment with sales) isn’t sustainable unless all your systems play nice. Plus, running through the same platform makes budget allocation and reporting a lot less time-consuming.

But integrations can’t do all the work. To make effective data-driven decisions, consider how you’ll manage data from the start. If you create and stick to a specific approach, you can leverage your data over time to measure which programs are the most successful.

The key is to always have a plan for how you’ll use your data before you request it or pull it from your platform. With the end goal in mind, it’s easier to know how and when to invest your resources and turn data into wins. 

2. Track data by funnel stage

Tracking data by funnel stage is another way to prevent data overload. Beyond that, it’s also an effective way to sort through and prioritize accounts in your pipeline.

How does this actually happen? Through a combination of static and dynamic data.

Static data: Are these accounts a good fit?

Static data refers to information gathered at a fixed point in time, typically related to the profile of accounts. It includes key elements such as firmographics or technographics—the core data that drives the backbone of your ABM strategy, ideal customer profile (ICP), and target account list (TAL) building.

Static data drives key strategic decisions around which accounts you should target (based on firmographic and technographic factors) and ultimately informs the long-term marketing strategy as you begin to layer in dynamic data.

Dynamic data: Are these accounts engaged or ready to buy?

Dynamic data refers to a dataset that continually changes over time-based on behavior—and it’s crucial for understanding how accounts move through a buyer’s journey. For instance, dynamic engagement data for an account constantly updates to reflect changes in on-site engagement or off-site intent. 

From there, dynamic data continually funnels into key decisions, influencing who you target, when you target, and what offers you target them with.

It provides insight into account activity that helps you prioritize which accounts are the most ready to buy versus which accounts need extra nurturing.

Mapping journey stages with fit, intent, and engagement data

Here’s how the typical ABM funnel breaks down:

  • Unaware
  • Aware
  • Engaged
  • Open Opportunity
  • Won Opportunity
  • Post-Won Opportunity

These stages map where an account or customer is in their buying journey and they’re better defined by the dynamic and static data you’ve collected—namely fit, intent, and engagement signals. 

Customizing these journey stages will benefit from as many channels as possible, including:

  • Advertising data
  • Website data 
  • Email engagement
  • Content engagement
  • Sales activity (such as Salesforce, HubSpot, etc.)

With a robust ABM platform, you’ll have access to an overview of your accounts and their distribution throughout the funnel, which will enable you to:

  • Identify in-market behaviors
  • Find and engage high intent accounts
  • Prioritize accounts based on buying stage

Segmenting these accounts will pave the way for new account-based strategies you can tailor to multiple customers in similar stages of the buying journey. Ideally, this type of automation will save both time and money while providing the insight needed to move the most valuable targets down the funnel.

3. Embrace machine learning

Machine learning isn’t just a buzzword....

If you want to make smart investments and find customers who are a perfect fit for your company at scale, machine learning (ML) opens a slew of new opportunities by leveraging your data into a predictive model that scores and prioritizes accounts. 

Here’s how that might look in practice:

  • Build a custom training model based on data from your best closed-won customers. 
  • Grade your target account list based on those parameters, scoring the accounts using fit data and factors like company size, revenue, tech stack, and industry.
  • Score your TAL and assign grades to accounts to tier them based on “most likely to close” versus “less likely to close.”
  • Work hand-in-hand with sales to prioritize your highest-scoring, data-validated target accounts.


But don’t expect machine learning to handle everything. Leveraging account-based data collection means continually refining your ICP and TAL based on dynamic, cross-channel insights. 

The Road Ahead for CMOs

Now more than ever CMOs are being pulled in multiple directions at once. According to eMarketer B2B CMO and Leadership Balancing Act report, the number of marketing projects have increased by 81%, while 43% of marketers say their budgets have not. The pressure to do more with less is increasing and CMOs need to narrow their focus. Here are a few considerations to help CMOs do just that. 

Know your value to the organization as CMO

It’s critical that there is alignment between key executives on the organization's needs and what exactly the value is that the CMO is to provide. The attention of a CMO is being stretched across branding, demand gen, revenue and more. Setting clear expectations from the start around your GTM strategy will avoid any general confusion among leadership. 

Geek out on your market

Successful CMOs know their audience and their needs when it comes to market trends. They are knowledgeable about their market and are the go-to resource for updates and more. This helps them to also anticipate future market shifts, disruptions and keep a close eye on the competition. 

Understand the Customer Journey

CMOs should spend more time with customers.  If they have a good understanding of their customer experience, it will only make it easier for them to address new prospects. To connect on a more impactful level, try to avoid routine questions about common challenges. If you ask a predictable question, you will only get a predictable answer leaving you with vague customer data.

Bottom Line, Understand the Data

It's one to have control over data and another to truly understand it to show ROI. CMO should know the KPIs that illustrate the health of all marketing efforts and how they relate to wider business initiatives. Strengths in analytics are almost a standard for CMOs to understand data intuitively in order to stay ahead of ( and predict) potential hurdles. 

Through integrated systems, embracing data, and a thorough understanding of how your customers make their way through the funnel, CMOs can use data to do what ABM helps marketing teams do best: prioritize the accounts with the highest chance of closing and become better leaders.

 Book a demo with our team today to elevate your ABM strategy. 

About the Author

Alysha Parker, Content Marketing Manager

Alysha is a Content Marketer at RollWorks

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