Recently, a marketing leader at an environmental health and safety tech company leveraging AI took our ABM challenges poll and mentioned that the team sees limited returns from its $100K+ investment in 6sense. The problem was that while 6sense intent data may show potential interest, it doesn’t mean that accounts are strategically, operationally, and executionally aligned with the company’s solutions or that accounts are ready to adopt AI for EH&S. The Verdantix Report which recently featured the marketer’s company shows that EHS executives are clearly facing an uphill battle to successfully utilize the technology and that there is still a steadfast “no AI” policy.
In addition to intent, the company needs to uncover the key characteristics of those accounts that are allocating budget and prioritization of AI – and those that are ready from a data, technology ecosystem, maturity, and readiness perspectives. It’s those signals that need to be added on top of intent to avoid false positives with accounts that may be looking into AI, but ultimately end in no decision because they are not ready, or the champion cannot get buy-in because they are not culturally aligned.
Most Companies That Show Intent for AI-Solutions Are Not Ready
As Jason Snyder wrote in a recent Forbes article, “Rethinking How We Sell AI: From Transactions To Transformation”:
“AI isn’t a utility. It’s a transformation. And transformation doesn’t come packaged in an SKU. The miracles people expect from AI—automating entire workflows, revolutionizing supply chains, predicting disease, ending hunger—don’t live in some pre-trained model you can swipe a credit card to access. These outcomes require time, trust, and tailored guidance.”
When it comes to transformation, a change is needed in how companies operate and execute their strategic initiatives. But, intent data does not into account if shifts have been made or where the account is in the change process. Intent or the ICP proxies within 6sense, Demandbase, and others do not take into account if an organization is structured to succeed with AI. This is important as your ABM programs should focus on accounts that will predictably land and expand with you since NRR is the North Star. According to Jason Snyder, most organizations are not structured to succeed with AI.
He wrote:
“Here’s the uncomfortable truth: Most companies aren’t structured to succeed with AI. Silos are a top barrier to AI adoption, along with data fragmentation and unclear accountability. Budgets are set quarterly. Product roadmaps are set annually. Org charts are fixed in silos. Meanwhile, AI models evolve weekly, and breakthroughs don’t wait for fiscal alignment.
The CMO has some data, the CIO has another part, and the CTO is experimenting with its sandbox. None of it is connected and does not map cleanly to the kind of collaborative infrastructure AI requires.
So what happens? You try to innovate, and the system resists. You introduce a new model, and suddenly, your legacy platforms can’t talk to it. You find the insight but have no mechanism to act on it. AI isn’t just hard to implement. It’s hard to organize around. And that’s the real unlock: AI isn’t just a technology shift. It’s an organizational redesign challenge disguised as a tech opportunity.”
We Need to Uncover the Accounts That Are Redesigning Their Organizations to Succeed with AI So They Can Land and Expand.
6sense, Demandbase, and other intent data and ABM platforms only help you define your total relevant market or your ideal customer segments. As mentioned in our blog post, “How Most Companies Only Have a Total Relevant Market”:
“When you target your core and engage with them the right way, that’s when win rates go up, stage progression accelerates, sales cycles go faster, and deal sizes increase. When you align with your core, you build retention, you drive customer lifetime value, and expand deals as you provide greater value to them.
But, very few GTM teams align with their core.
They do not even know what their core is as they only defined their Total Relevant Market and not their ICP. Most ICP definitions miss the “ideal” and cast far too wide a net, targeting broad industries and revenue ranges without getting granular enough to define the “ideal” customers.”
What we wrote in that blog post is especially true when it comes to GTM teams selling AI as they haven’t looked deep enough into the characteristics of those accounts that are getting the greatest returns from their solutions and the characteristics of those accounts that churn. They haven’t looked into the maturity of those organizations that are landing and expanding/ They haven’t looked for the anti-ICP characteristics of those companies that churned or accounts that did not move forward to see how they didn’t align or how they weren’t ready for AI.
You have to remember… While 6sense and other platforms will promote a predictive platform, intent itself is not predictive.
Intent data only reflects the current state of mind or interest of potential buyers, indicating what they might be looking for or considering. But it does not necessarily guarantee future actions or buying behavior (which is what “predictive” implies) as it doesn’t consider if a company aligns with you operationally, executionally, philosophically, and culturally.
- Intent data captures current activity.
- Intent data tracks online behaviors like website visits, keyword searches, and content downloads, which show what a person is actively researching at that moment.
- Intent doesn’t show what buyers will most likely do in the future.
- And, most importantly, intent data is not predictive that an account will grow with you vs. churn.
As David Keene (European CMO at Wipro) mentioned on the ABM Done Right Podcast:
“You do not want a big, wide funnel filled with intent-qualified leads and opportunities that do not move forward. Everyone focuses on MQAs and MQLs and they focus on getting accounts to pipeline. But. you want to focus on those accounts that have a very low chance of losing and a high chance of winning at a high ACV. If accounts do not progress and if they aren’t closing at a higher ACV or staying and growing with you – then what good is that MQA. The focus should be on revenue and customer lifetime value and not MQAs. You want the customers that will stay with you and grow and become the backbone of your business.”
Click here to learn more about the signals and account insights you need to add to intent to create a more predictable pipeline