I joined Influ2’s session with Dmitri Lisitski and it was great. So good that it deserved an article because I learned a lot.
If you’ve been anywhere near ABM over the last decade, you’ve lived the same frustration I have: intent data looks promising on paper but collapses when you hand it to Sales. “Somebody at Acme clicked on an ABM article.” Okay… who? what? why now? The rep shrugs, ignores it, or worse, guesses wrong and burns a bridge.
That’s the wedge. Intent, in its classic account-level form, is interesting but not actionable. The Influ2 webinar finally hit that nerve head-on and offered something sharper: contact-level intent. Not the blob called “Acme,” but Melissa from Acme clicked this exact article.
The broken promise of account-level intent
Most of the tools we’ve had to date stop at the account. They tell you an organization is “surging” on a topic, but not who is actually behind the research. I’ve seen this play out in every flavour of ABM program:
- Sales gets a list of “hot accounts” with no context. Half of them are real opportunities; half are ghosts.
- Marketing tries to orchestrate campaigns, but with no contact signal, personalization turns creepy or generic.
- SDRs are told, “somebody from Acme is researching X.” They either do nothing or assume it’s the VP they want and go in with the wrong pitch.
The fallout is predictable: Sales stops trusting the signals, Marketing gets defensive, and leadership wonders why the shiny intent platform didn’t move pipeline.
“There is no such thing as an account journey”
The “account journey” doesn’t exist. There are individual journeys that occasionally sync up. The evaluator is knee-deep in research; her boss hasn’t defined the problem; procurement shows up in the eleventh hour. Roll that into one “surge” and you lose the only parts that matter.
Often, ABM programs that sputtered had plenty of signals, and even had Sales alignment on paper. But when everything rolls up to the account, nuance is lost.
That one sentence crystallized why account-level intent fails. Even within a small buying group, the paths diverge:
- The evaluator is knee-deep in research, comparing vendors side by side.
- Her boss hasn’t even defined the problem yet.
- Procurement doesn’t exist in the picture until the eleventh hour.
To call that a single “account journey” is fiction. There’s no monolith. There are individuals — each on their own curve — who eventually come together around a decision.
When you measure only the aggregate, you blur the differences that actually matter.
What contact-level intent really gives you
The session introduced a new way Influ2 helps in surfacing contact-level signals across content, search, and social. Finally, a name ties to intent, not just a domain.
- Content: who engaged and the topic-of-interest they kept coming back to.
- Search (incl. zero-click): who queried which keyword/category/brand, even when ~60% of searches end without a click—so you still see the moment curiosity spikes.
- Social: actual posts/comments mapped to your topics, not emoji noise.
The power isn’t in the labels. It’s because you can now act relevantly. Not “I saw you searched this yesterday”, but “Teams exploring [Topic] usually hit [Problem]. Does that resonate with you?”
This is where Dmitri made another critical point: relevance > personalization. Personalization is easy to fake (“Hi Amanda, saw you’re in Montreal”), but irrelevance kills the conversation instantly. Relevance means you’re speaking to what they actually care about in that moment.
Forget about personalization; focus on relevance
The line that landed for me: relevance beats personalization. Personalization is easy to fake—names, titles, city tokens. Relevance is harder because it forces you to talk about the problem they’re actually exploring right now.
Contact-level intent makes relevance possible without getting creepy. You don’t need to “out” the source (“I saw you searched X at 2:17pm”). You just need the topic and timing to shape a conversation that feels right on contact.
When your outreach leans on personalization, you get poor results.
- “Hi Melissa, loved your alma mater. Any interest in ABM?” → ignored.
And here’s the part most teams miss: AI makes personalization cheaper, not better. You can auto-spray thousands of “Hi {FirstName}” messages today. What AI can’t guess is what’s worth being relevant about. That’s why contact-level signals matter. They supply the what (topic, moment, role). Your job is to supply the why it matters in clear language.
You earn relevance by knowing the topic and timing.
The AI and zero-click shift
AI changes buying behaviour. More buyers are doing their homework in ChatGPT or stopping at AI-generated summaries instead of clicking into source content. That means your traditional “first-party signal” pool is shrinking.
Contact-level search intent fills that gap. If someone never lands on your site but you can still see that they searched for “ABM attribution framework” yesterday, you get to them before the competition. Speed matters because interest decays. The impulse window is hours, not weeks.
This matches what I’ve seen in my own ABM programs: the deals we win fastest are the ones where we acted on signals quickly — while the problem was fresh.
From signals to “why now”
The problem with intent has never been the idea — it’s the execution. At the account level, you get noise: a whole domain flagged “in market” because someone, somewhere clicked something. That’s why reps ignore it. They can’t see who leaned in, or why it matters now.
The real unlock comes when you take signals down to the contact level with context. Not just “a pageview,” but: who engaged, what topic they were actually exploring, and how often they came back to it. Even the so-called “invisible” behaviours — like the 60% of zero-click searches that stop at an AI summary — can now be surfaced and tied to a name. And on social, instead of getting buried in emoji noise, you see the actual posts that map to buying pain.
That precision makes it possible to route signals into something I’ve been pushing for with the Multi-Badge MQA™ model: a single, believable “why now.”
Badges on their own are useful: they separate why now into Expansion, Growth Momentum, Tech-Refresh, or Intent-Surge. But a badge is only as good as the signal that triggers it. If the trigger is vague — “account surging” — Sales still won’t trust it.
That’s where contact-level intent does the heavy lifting. It enriches the badge in three ways:
- It makes the trigger specific.
- Before (account-level): Expansion fires because “Acme showed product interest.”
- After (contact-level): Expansion fires because three named users in Acme’s marketing team spent the week reading articles on the analytics add-on, while their VP posted on LinkedIn about reporting gaps.
- It makes the badge timely.
- Before: Tech-Refresh only shows up once aggregate engagement hits a threshold. By the time it surfaces, the buyer may have moved on.
- After: Tech-Refresh fires the same day a RevOps lead searches ‘Competitor X vs [Your Tool]’ and a CMO comments on a peer’s post about migration headaches. Zero-click search coverage means you see it before they ever land on your site.
- It makes the story believable.
- Before: Growth Momentum means “the account is surging on category intent.” Sales gets a score of 85 and shrugs.
- After: Growth Momentum means a Director of Demand Gen and a VP of Sales at Acme both read three Forbes and G2 articles on ABM attribution in the last 10 days. The badge now comes with a short narrative Sales can actually use: “Teams like yours are clearly exploring attribution — do you want to see how peers solved the early traps?”
Most intent platforms still collapse signals into a vague account label: “somebody at Acme is surging.” It’s not actionable. Sellers don’t know who engaged, what topic sparked the interest, or whether it’s even relevant. That’s why so much intent data dies in dashboards.
What changes in execution
When you add contact-level precision, orchestration sharpens. Speed, specificity, sequencing. With a name and a topic on the record, you can act the same day, lead with the right angle, and design per-buyer journeys that roll up to the group view.
I can imagine this happening when, in a campaign, a senior manager clicks an ad and a junior manager books the meeting. Without the contact-level view, that link would’ve been invisible. With it, we could see the group dynamic unfolding and time outreach accordingly.
Where I’d take it further
Surfacing these signals in a feed that reps can actually use is probably the most important part of contact-level intent, because signals only matter if we act on them and they turn into motion.
The difference with contact-level intent isn’t “more data,” it’s how the data arrives: a name, the topic they’re actually exploring, how recent it was, and how that threads with other people in the same account.
So, my take on this is to make the reason usable. On the record, one clear language line. Not a score, not a mystery. Also, running outreach against the individual who sparked the moment, and taking in consideration that zero-click search means the trail often starts before a pageview, so acting fast is key.
And again, stay on the right side of relevance. Eight out of ten buyers ignore messages that aren’t relevant.
Where ABM teams can still slip
Even when intent data is on the table, teams sabotage their own chances. The most common mistake? Treating the signal as a script. Outreach that says, “I saw you searched X yesterday,” it’s creepy. The signal should inform the angle of the conversation, not become the conversation.
The second trap is to confuse volume with value. Giving reps massive hotlists of “intent accounts” with no expiry and no context. Within a week, it all looks like spam. Signals decay fast, if you can’t act on them quickly, don’t surface them.
And then there’s the trust problem. When the “why now” isn’t clear on the record, Sales tunes out. If intent shows up in CRM as a vague score, it gets ignored.
Contact-level intent fixes the gap we’ve all wrestled with: intent that’s interesting but not usable.
When you connect those signals into a system like Multi-Badge MQA™, you give Sales exactly what they need: one clear reason per account, tied to a real human action, routed to the right owner, acted on fast.
That’s the difference between intent as noise and intent as revenue.
Contact-level intent Takeaways
Account-level intent data shows that “someone” at a company engaged with a topic, but it stops there. Sales can’t see who it was, what they actually looked at, or whether it’s relevant to their deal cycle. That’s why most reps ignore it.
Contact-level intent fixes the gap. It identifies the individual—the name, the role, the topic they explored, and often how often they came back to it. Instead of “Acme is surging on ABM,” you see “Melissa, VP of RevOps at Acme, read three articles on attribution in the last 10 days.” That shift makes intent data credible and usable.
Personalization is easy to fake. Adding someone’s first name or alma mater to an email doesn’t make it resonate. In fact, AI makes this even cheaper—you can spray thousands of “Hi {FirstName}” messages today. But buyers don’t respond to personalization alone.
Relevance, by contrast, is harder to earn and more valuable. It means you’re speaking directly to the problem they are researching in the moment. Influ2’s webinar highlighted that 8 out of 10 buyers ignore messages that aren’t relevant. Contact-level intent provides the data to make relevance possible. Instead of creepy outreach (“I saw you searched X at 2:17 pm”), you shape a natural conversation around the theme: “Teams exploring attribution often hit [problem]. Have you seen that too?”
Buying behaviour is changing. Today, more research happens in ChatGPT or in AI-powered search summaries than on vendor websites. Roughly 60% of searches now end without a click. That means if you only track first-party signals—like site visits or gated content—you’re missing most of the journey.
Contact-level search intent solves this by detecting the query even if the user never clicks through. If Zach, a Demand Gen manager, searches “Competitor alternatives” and never hits your site, you still see the intent tied to his name and role. This makes it possible to act earlier, while the problem is fresh, and before your competitors ever know there’s a deal forming.
Badges on their own separate “why now” into useful categories—Expansion, Growth Momentum, Tech-Refresh, Intent-Surge. But a badge is only as strong as the signal that triggers it. If it’s vague (“Acme is surging”), Sales won’t trust it.
Contact-level intent gives each badge a story.
Expansion becomes credible when three named users in Acme’s team are reading upgrade content and their VP posts about reporting gaps.
Tech-Refresh surfaces the same day a RevOps lead searches “Competitor X vs [Your Tool]” and another exec comments on migration pain.
Growth Momentum is believable when both a Director and VP spend a week engaging with attribution articles.
Instead of a generic score, the badge comes with a human narrative Sales can use in their opener. That’s how signals become meetings, and why contact-level intent is the cleanest fuel for a system like Multi-Badge MQA™.