Forrester put it bluntly in an April 2026 report: B2B intent data is “ubiquitous, increasing, and consistently underutilized.” Adoption has climbed since 2023. Results haven’t kept pace. The reasons Forrester lists are immature usage, no measurement, and trouble getting signals into the systems where sales actually works.
Notice what’s not on that list. Nobody is short on data. What most teams lack is a workflow: a repeatable path from “this account is showing interest” to “a rep with the right message reached them at the right time.” That’s what this post lays out, in the order you’d build it. (New to the topic? Start with Intent Data Explained.)
Step 1: Decide which signals count (and which don’t)
A scoring model built on weak signals produces confident nonsense, so sort your signals into three buckets before you weight anything.
First-party behavior. Repeat visits to pricing, comparison, or integration pages; case-study reads; demo forms started but not finished; several sessions from one company inside a short window. These are your strongest signals because the buyer is researching you, not the category.
Third-party research. Topic surges from providers like Bombora, review-site activity, competitor comparisons happening off your domain. Useful for finding accounts you’ve never touched, but they tell you an account is in-market, not that it’s in-market for you. (More on that tradeoff in First-Party vs. Third-Party Intent Data.)
Relationship history. Closed-lost deals from the last 18 months, expired trials, champions who changed jobs. Old data, but when it lines up with fresh behavior, it turns a warm signal into a hot one.
Two rules hold across all three buckets. No single signal is proof of anything; one pricing-page view could be a competitor, a student, or a bored procurement analyst. And momentum beats volume: three sessions in two days says more than fifteen spread across a quarter.
Step 2: Score fit and intent on separate axes
The mistake we see most often is one blended score. A perfect-fit account with zero activity and a terrible-fit account with a research spike can land on the same number, and the rep can’t tell which is which.
Keep them apart. Fit is how well the account matches your ideal customer profile (industry, size, tech stack, geography, role), graded A through D. Intent is how much relevant activity the account is showing right now relative to its own baseline, scored 0 to 100.
For a reference point on how the big vendors do it: Bombora’s Company Surge score runs 0–100, and 60 or above counts as “spiking,” a statistically significant increase over the account’s historical consumption. Bombora also recommends requiring a spike on at least 25% of your selected topics before an account counts, which is a good guard against one-off noise.
6sense’s predictive buying stages follow a similar shape: Target (0–19), Awareness (20–49), Consideration (50–69), Decision (70–85), and Purchase (86–100), each tied to the likelihood of an opportunity opening within 90 days.
You don’t need their models. You need the same structure: a floor below which nothing happens, a middle band for marketing, and a top band that goes to a human.
Then plot the two axes against each other:
- High fit, high intent: sales outreach now.
- High fit, low intent: targeted ads and nurture until the intent score moves.
- Low fit, high intent: self-serve content or nothing. Don’t spend rep time here.
- Low fit, low intent: nothing.
One more thing the score needs: decay. Intent scores should fall automatically as signals age. We wrote about why intent loses value so fast; the practical fix is a score that resets rather than one that accumulates forever.
Step 3: Route with rules a rep can predict
Routing is where good scoring goes to die. The score fires, the account lands in a shared queue, and three days later someone notices. The fix is boring and effective: every tier gets an owner and a clock. A workable starting point:
- Top band (Purchase or Decision stage, A or B fit): straight to the account owner or an AE. Contact attempt within one business hour.
- Middle band (Consideration, A or B fit): to an SDR sequence. First touch within 24 hours.
- Lower band or C/D fit: stays in marketing. Ads, email, retargeting. No rep touches it.
Why the one-hour clock? The best-known evidence is still Harvard Business Review’s 2011 study “The Short Life of Online Sales Leads.” Researchers sent a test web lead to 2,241 U.S. companies. Only 37% responded within an hour, 23% never responded at all, and the average response time was 42 hours.
A companion study of 1.25 million leads found that companies attempting contact within an hour were nearly seven times as likely to have a meaningful conversation with a decision maker as those that waited even one more hour, and more than 60 times as likely as those that waited a day or longer.
Fair caveat: that research measured inbound form leads, not intent signals, and it’s fifteen years old. But the direction isn’t in dispute, and intent signals go stale faster than form fills, not slower.
Routing hygiene matters as much as the rules. One owner per account, not per signal. Deduplicate at the account level so five people at one company don’t spawn five tasks. Log every hand-off; you’ll need it in Step 5.
Step 4: Time the message to the signal, not the calendar
The account is scored and routed. Now the rep has to say something, which is where most intent programs quietly turn into spam.
Start from what the signal says about the buying group, not the individual. Gartner puts the typical buying group for a complex B2B purchase at six to ten decision makers, each arriving with four or five pieces of independently gathered information. The person whose visit tripped your score may be the researcher, not the decider. Multi-thread from the first touch.
Then match the message to the stage. 6sense’s 2025 Buyer Experience Report found 94% of buying groups have already ranked their preferred vendors before first contact with sales. An account in the Consideration band is building a shortlist; help it compare. An account in the Purchase band has probably already made one; your job is to confirm you’re on it and remove friction.
Whatever the stage, don’t narrate the surveillance. “I noticed you were on our pricing page Tuesday” makes people close the tab. “Teams your size usually hit this problem when they outgrow spreadsheets; is that what’s driving the evaluation?” references the topic without the tracking. Same signal, very different reception.
Step 5: Measure the lift or stop paying for it
Forrester’s “lack of measurement” finding should sting. Intent data is often the priciest line in the data stack, and most teams can’t say what it produced.
The clean way to find out is a cohort test. Split your target accounts into two groups of similar fit; work one with intent-based prioritization and routing, the other the way you always have. Same reps, same sequences, same offer, 90 days. Then compare reply rate, meetings booked, pipeline per account, and close rate.
If the intent cohort doesn’t win on at least meetings and pipeline per account, the problem is in Steps 1 through 4, or the data isn’t worth what you’re paying. Either way, you’ll know.
The five ways this breaks
- Scoring on a single behavior. One page view is not intent.
- Scores that never decay. A surge from March shouldn’t outrank a visit from yesterday.
- Every surge goes to sales. Reps stop trusting the queue within a month.
- No SLA on the hand-off. The score fires; nobody owns it.
- Messaging that quotes the tracking. Reference the problem, never the page.
Where this gets hard for smaller teams
Everything above assumes an intent data contract, a CRM that can hold the scores, and someone in RevOps to build and maintain the routing. Enterprise teams have that. Most mid-market and SMB companies don’t, and the workflow stalls at Step 2.
That gap is what Smart Marketer’s Visitor Intelligence is built for. Smart Pixel identifies the people already visiting your site and connects their on-site behavior to full identity profiles. Smart Marketer then runs the qualification, routing, and follow-up, rather than handing you another dashboard to manage.
If you want to see what that looks like on your own traffic, start with a Traffic Intelligence Evaluation. 14 days. Your actual visitors. No obligation.
Sources: Forrester, “B2B Intent Data Is Ubiquitous, Increasing, And Consistently Underutilized” (April 2026); Bombora Company Surge documentation, score and topic thresholding; 6sense Support, “Predictive Buying Stages”; Oldroyd, McElheran & Elkington, “The Short Life of Online Sales Leads,” Harvard Business Review (March 2011); Gartner, “The B2B Buying Journey”; 6sense, 2025 Buyer Experience Report.
