In our blog article, “How ABM Tech & AI Are Widening the Gap Between GTM Teams and Buyers”, and in LinkedIn conversations, we’ve been talking about the interpretation gap that can be found within AI and all ABM platforms, including Demandbase and 6sense. The “interpretation gap” was coined by the guest for this podcast episode, Eve Chen (CEO of Growth Engine and Fractional CMO for multiple tech firms).
Eric Gruber (CEO of Personal ABM) and Eve Chen discuss how most GTM teams do not have the strategic clarity, customer understanding or the human interpretation layers that are needed to create greater account-based revenue growth – and it’s a major reason behind the fact that 80% of ABM programs fail.
Here Are the Key Points to Remember from The Conversation with Eve Chen…
- ABM is often retrofitted onto existing content, processes, and messaging. It’s all about the target account list (TAL). The teams aren’t changing the digital/social/email/live interactions that they have or the account experiences, and aligning it with where the business wants to go. They are not looking for where the teams are winning and where they are losing. They are not looking for the revenue leaks (the red) in the business. Most teams lack the strategic clarity that’s needed to build an ABM foundation. They are building their programs based on “efficiency and scaling needs,” even though GTM efficiency requires improvements in both sales/marketing productivity and effectiveness. They are not focusing on business goals and building a revenue operating system to achieve them as a team. When you create your ABM program, you should be able to answer: What problem(s) will ABM actually solve in their revenue system and what business outcomes are we trying to change?
- Most GTM teams will describe their customers and their best prospects (ICP) superficially. They don’t understand the executional, operational, and cultural characteristics that lead to greater returns for their best customers. They don’t understand the strategic priorities of their customers and prospects and the unique role they play in those priorities. They don’t understand the customer/prospect situations where they are relevant, and the competition is irrelevant. Without having a greater customer/prospect understanding, GTM teams will not know what data and signals to collect and analyze. They won’t know what’s important to guide content, messaging, interactions, and experiences.
- Most teams do not have the buyer group intelligence that’s needed to identify, map, and interpret the collective intent, readiness, and authority of all stakeholders involved in a purchase decision. Identity intelligence helps you understand who the real stakeholders are, their roles, influence, and relationships. You cannot interpret intent if you do not know the ecosystem behind it. Contextual intelligence helps you decode what drives each stakeholder’s interest, friction, and timing. Signals are only meaningful when interpreted through real-world context — the industry shifts, internal politics, and external pressures shaping their decision-making. Decision Intelligence helps you synthesize every signal and stakeholder insight into a coherent narrative that predicts readiness and consensus. This is where intelligence transforms from data into direction.
- Between every signal and every sale lies an invisible space: the Interpretation Gap. It is the distance between what your systems record and what your buyers actually mean. When teams rely on automation to define meaning, that gap widens. Signals are captured but not contextualized. Patterns appear, but stories disappear. The result is data that looks intelligent while the go-to-market motion remains blind. AI and intent can help you identify and see trends that you would have missed otherwise, but they cannot provide context behind those trends and connect the different data points to tell the account story.