Data Management

The CMO Framework to Evaluating Data Actionability

The CMO Framework to Evaluating Data Actionability
“Data is the new problem. Actionable insights are the new gold.” - John Rakowski

Why CMOs need a data strategy

Data is only valuable if it provides actionable insights.

Many CMOs and PLG companies today are data-rich and information-poor. They have troves and troves of data (no one is saying I don’t have enough data) but no way to draw actionable insights. This is a problem because CMOs need their teams to move quickly. They can’t rely on CTOs and favors from engineering teams to get the insights they need. 

It is the responsibility of the CMO to make data actionable for their go-to-market teams. 

The evolution of the B2B CMO

Making sense of high volumes of data is a newer challenge for many as the role of the B2B CMO has greatly evolved over the last 50+ years

Evolution of CMO, Marketing Operations

In the 1960s (think Mad Men era), CMOs were responsible for brand awareness — slogans, commercials, and more! As time went on, priorities shifted to demand, with marketing leaders focused on scaling channels and cracking the code on multi-touch attribution. Enter 2020, and the modern CMO has a huge data responsibility. How can data be used to pilot an increasingly digitalized journey? 

While brand and demand are instrumental elements in any marketing strategy, CMOs must have a data strategy. 

So, how can CMOs build a data strategy?

A crucial first step is evaluating data actionability. 

We worked with many leading Product-Led Growth companies like InVision, Lucid, and more to put together a framework to help CMOs understand their ability to use (and scale) their data for go-to-market initiatives. 

The framework is organized by funnels (self-serve, sales-assisted, bottom-up, and top-down) and levels, each increasing in complexity from top to bottom.

Ideally, organizations should strive to be at level 3 (bottom row) on their core funnel and at least level 2 on the next two most relevant funnels (middle row).

For example, if the core funnel is sales-assisted, in order of increasing complexity, GTM teams should be able to use their data to

  1. Make sure every demo request is flagged and followed up on appropriately
  2. Identify good-fit product users based on activity, firmographic, technographic, and demographic traits
  3. Personalize the user experience based on persona

Level 3 is critical. If a CEO (buyer) signs up for the product, the messaging should be around why it’s valuable for their team instead of showing them individual features. On the flip side, users should be guided towards taking product actions. Segmenting the onboarding experience and supporting sales with persona-specific content will increase conversions and ultimately lead to more deals.

Following that same thread, a typical PLG company may have a secondary bottom-up funnel, where they should achieve at least level 2 in the data actionability framework. In order of importance for that funnel, here are critical data segmentation and actions to achieve:

  1. Identify active accounts 
  2. Identify accounts ready to purchase an enterprise-ready plan 
  3. Identify admin activities (adding a new user or integration, for example). While this may not core to the product, it is representative of growth. These people typically hold the keys to widespread adoption. Identifying admin roles helps expand and grow an account.

While those are just two examples, this framework can help CMOs evaluate data actionability and build a strategy to unlock level 3 across multiple funnels.

While reviewing this framework, it is important to assess:

  • Which activities and segmentations can be achieved today
  • What gaps in the data structure create roadblocks to achieving level 3
We hope this serves as a helpful resource in building a robust data strategy. For more information and insights, check out the on-demand webinar.