tl;dr Two years ago, "we have a signal on Acme" was a competitive edge. Today it is table stakes. Every growth team can see intent, even if attribution and enrichment are still rough at the edges. Far fewer can act on it before it goes cold. The advantage has quietly moved from the dashboard to the minute after the dashboard lights up, and most of the stack was never built for that minute.
Signal-based selling won the argument. What was a contrarian idea a couple of years ago is now described across the category as the dominant motion for high-performing go-to-market teams, with the tooling landscape converging on buyer signals as the foundation of the workflow rather than a feature bolted onto it (Landbase, Highspot). The data backs this movement in the market. For example, McKinsey's B2B Pulse research has commercial teams that pair personalization with gen AI 1.7x more likely to gain share than peers committed to neither.
When everyone agrees on something, the interesting question becomes the next question. Historically, the hard part was seeing intent at all: resolving the anonymous visitor (VPNs and privacy rules still make this imperfect), catching the second pricing-page view, noticing the job change of a primary contact. That problem is now broadly solved by vendors you can buy this afternoon.
So the edge is no longer just detection. But there is still an edge, and it did not disappear. It just moved one step to the right, into what you do with the signal once you have it. And that step is where most teams quietly fall apart, often without even knowing it.
Here's the pattern I see in nearly every growth org I talk to. The signals are flowing. There is a dashboard, often several. There is a Slack channel where intent alerts land. But there is a slow, human gap between the alert and anything happening because of it.
The signal fires at 10:02. It gets seen at 11:40, if someone is watching the channel. It gets discussed in a standup the next morning. It becomes an action, maybe, by Thursday. By then the visitor who looked at your pricing page three times in an hour has either bought, churned, or talked to a competitor who answered faster.
Intent has a half-life. A buying signal is not a durable fact about a company, it is a perishable statement about a moment. The value of acting on it decays, often within hours. Most go-to-market stacks treat signals like a report to be reviewed and treat the review cadence as a calendar problem. The signal does not care about your calendar.
This is the gap the market has not priced in yet. We spent the build cycle of the last two years buying better eyes. We have barely started on faster hands.
When a signal goes to waste, the instinct is to blame the data: it was noisy, it was a false positive, the score was wrong. Sometimes that's true. More often, the signal was fine and the system around it failed.
Watch where a real signal travels. It is detected by one tool, scored by another, and then it has to find a human. That human has to notice it, judge it, decide who owns the account, confirm nobody else is already working it, pick the right next move, and do that move in a different system than the one that raised the alert. Every one of those hops is a handoff, and every handoff adds latency and loses information. By the time the signal becomes an action, it has passed through three tools and two people and a routing rule that may be six months out of date.
WHERE SIGNALS DIE. Not in the data. In the handoffs. detect (10:02) -> score (+ minutes) -> alert a human (+ hours) -> route + own (+ a day) -> act (if at all) Time to action accumulates at every hop. Each handoff adds latency and drops context. The signal was fine. The system around it was not.None of those people is doing anything wrong. The failure is structural. We have built go-to-market systems that are very good at producing signals and very bad at conducting them. The org chart, not the algorithm, is where most intent goes to die.
If the edge has moved to the minute after detection, then the metric that matters has moved too.
For a decade we optimized volume metrics: how many leads, how many signals, how many touches. Those are input counts, and we are now drowning in inputs. The metric worth obsessing over in 2026 is time to action: from the moment intent is observable to the moment something credible happens because of it.
This is a humbling number to measure, because most teams can't today. They can tell you how many signals they captured last month. They usually can't tell you the median time between a high-intent signal and a relevant response, or how many high-intent signals got no response at all. When teams do measure it, the number is almost always worse than they guessed, and the act of measuring it tends to change behavior faster than any new data source would.
If you do one thing after reading this, plug that gap. It will tell you more about your real go-to-market health than another intent feed ever will.
There is a second reason teams hesitate to close the gap, and it is more reasonable than it first appears. Acting fast on behavioral signals means acting on inference. You reached out because someone did something that looked like intent. The faster and more automated that response gets, the more important it becomes to be able to answer a simple question three months later: why did we contact this person, on this day, in this way?
That question comes from your own team during a deal review. It comes from a customer who asks why they got an email. It comes from finance, and increasingly from a privacy officer, and from regulators in places like California, where automated-decision rules are already on the books. A go-to-market system that acts quickly but cannot explain itself is not actually fast. It is fragile, and it gets slower the moment anyone asks it to account for what it did.
So the goal is not simply to compress time to action. It is to compress it while keeping a clean record of what was seen, what rule applied, and what happened next. Speed without an audit trail is a liability waiting for its moment to trip you up. Speed with audit is a capability you can scale and defend. The teams that win the next phase will treat the work record not as compliance overhead but as the thing that lets them move fast without stress.
This is the lens we are looking through. At Civic we build agents, and we have come to believe that the next leg of go-to-market is not another place to look at signals. It is something that runs them: watches the product, the site, and the systems of record together, scores intent against a team's own definition of a good account, and carries the moment into action inside a workflow that records every step, with a person setting the rules and keeping the final say where it matters.
I'm not going to pretend that closing this gap is purely a tooling problem. It is also an operating discipline. But the shape of the answer is becoming clear, and it is not "buy more signals." It is "shorten the distance between intent and action, and keep the receipts."
This GTM category spent the last few years learning to see. The teams that pull ahead from here on out will be the ones that learn to act, in the minute it still matters, in a way they can stand behind later. Everyone has signals now. The question for the rest of 2026 is whether you can run them.
If you are working on the gap between intent and action on your own team, I would be glad to compare notes. You can reach the team through civic.com.