B2B intent data: verify the signal before you buy the story
Quick answer
B2B intent data can give you a reason to investigate an account. It can’t, on its own, tell you that someone has a budget, buying authority or a live project. Find out what the supplier actually observed before deciding how much weight to give the signal.
The label can conceal very different observations
A visit to your own pricing page, a company’s increased reading about a topic and a contact’s declared request for information are different kinds of evidence. Vendors may describe all of them as intent, but their usefulness depends on what was observed and how it was matched.
Ask for the underlying event type, collection method, time window and identity level. Does the signal refer to a person, a browser, a household, an IP address or an organisation? How are shared networks, remote work and subsidiaries handled? A confident account name does not remove uncertainty in the matching process.
Keep declared interest separate from inferred interest. Someone requesting a meeting has provided a much clearer instruction than an organisation appearing in a topic surge report. Your response should reflect that difference.
Ask what the score is relative to
A score might compare an account with its own historical behaviour, with other accounts, or with a vendor-defined threshold. Those are different denominators. A small rise from a low baseline can look dramatic without representing many meaningful interactions.
Require an explanation of recency and decay. A six-month-old burst of research should not keep an account at the top of a live sales queue indefinitely. Ask whether the same event is counted through multiple feeds and whether bots or internal traffic are filtered.
The 6sense 2025 buyer study reports that first seller contact occurred at about 61% of the buying journey, earlier than its 2024 finding of about 69%. The practical lesson is limited but useful: buying journeys evolve, so a fixed interpretation of a behavioural signal can become stale. The survey does not validate another vendor’s intent score.
| Area | Ask | Warning sign |
|---|---|---|
| Observation | What behaviour was recorded? | Only a proprietary score is shown |
| Identity | How is the organisation matched? | No explanation of uncertainty |
| Timing | When does a signal expire? | Old activity remains permanently urgent |
| Value | What does it add beyond our current process? | Only unmatched success stories |
Test against the process you already have
An intent feed should improve a decision beyond what your existing fit criteria and first-party information can achieve. Comparing signal-positive accounts with every other company is a weak test if the first group is also larger, better known or already engaged with sales.
Start with accounts that meet the same fit criteria. Allocate comparable groups to your normal process and to a process informed by the new feed where feasible. Define the outcome and observation window before the trial. Keep effort comparable so extra seller attention does not masquerade as better data.
If one group produces 12 accepted meetings from 200 accounts and another produces eight from 200, the rates are 6% and 4%. Promising, perhaps, but four extra meetings don’t settle the case. Check whether the groups were comparable and whether the result is strong enough to justify the purchase.
Investigate the false positives
Ask sales to record why an account was unsuitable: student research, a consultant, an existing customer with a support issue, an unrelated business unit or no discernible project. These reasons can reveal a systematic mismatch between the topic definition and your offer.
Also inspect missed opportunities. A feed that surfaces only obvious late-stage buyers may look precise while contributing little new information. Compare it with the opportunities your team found through other routes.
Our guide to data mining for marketing explains why a pattern deserves testing before it becomes a causal claim. The same discipline should apply to a purchased score with an attractive dashboard.
MarTech Logic’s view: buy a better queue, not certainty
The sensible promise of intent data is a more useful research or outreach queue. It cannot establish a private budget or purchasing mandate that the underlying observation never captured.
Before committing, ask the supplier for sample records, coverage by your target market, refresh timing, matching confidence, exclusions and a practical export. Review permitted use with the people responsible for data governance. A commercially useful signal still needs an appropriate operating process.
Connect the feed through clear field ownership and data-quality checks. Keep the source and date visible to sellers. When the evidence is uncertain, use it to ask a better question; do not let it turn into a claim about the prospect that your team cannot substantiate.
Related reading
ABM account selection: build a target list sales can defend · Lead scoring for B2B marketing: keep fit and engagement separate · Marketing incrementality testing: find out what the campaign changed
