B2B outreach has a timing problem, not a messaging problem. A perfect cold email sent to a prospect who is not in-market gets ignored. A mediocre email sent to a prospect who is actively comparing vendors gets a reply.
Teams that win at outbound stop guessing who is ready and start watching for the digital footprints that reveal it. Those footprints are intent signals. Five of them carry the most predictive weight for small and midsize B2B companies, where there is no analyst team to interpret the rest.
This guide breaks each one down: what it means, how strong it is, how long the window stays open, and the play to run when it fires.
What is a buyer intent signal?
A buyer intent signal is a behavioural data point indicating that a contact or company is actively researching, evaluating, or preparing to purchase in a given category. Firmographic data (industry, headcount, revenue) identifies who a contact is. Intent signals show what that contact is doing right now.
This post covers the five signals with the highest predictive value. The full framework covering all seven signal categories, scoring, routing and the failure modes that kill intent programmes is in B2B buyer intent signals: the working guide for 2026.
The 5 B2B intent signals that predict purchase readiness
1. Pricing page visits
A named contact who visits a pricing page more than once in a single week is not browsing. That contact is modelling a buying decision. Pricing is the strongest first-party intent signal available on a company's own website. Someone reading a blog post is curious. Someone returning to a pricing page three times is comparing those numbers against a competitor's.
Pricing requires intent. It is the one page where a visitor is calculating budget, return and seat counts. Nobody lands on a pricing page by accident.
2. Demo or booking page views
A contact who lands on a demo, booking or calendar page without completing the booking has taken action and then stopped. Something interrupted: timing, an internal check, a colleague who needed to be involved, or friction in the booking flow itself.
This signal sits one click away from a booked meeting. The intent is already qualified. What is missing is friction removal.
3. LinkedIn content engagement
A target contact who likes, comments on, or shares content from a company page or its team members is telling the algorithm, and the seller, that the topic is relevant right now. A single like can be casual. Two or more engagements in the same week on related themes form a pattern.
This is the only signal on the list that does not require the prospect to visit the seller's website. It works upstream, catching contacts before they enter the funnel.
4. Company-level trigger events
A contact's buying timeline is usually driven by the company's situation rather than personal preference. Funding rounds, new executive hires, product launches, market expansions, acquisitions and reorganisations all open purchasing windows.
A funding round is commonly followed by sales hiring. A new VP of Sales is often rebuilding the tech stack inside the first two quarters. A product launch usually arrives with new headcount and new targets attached.
5. Team connection activity on LinkedIn
A prospect who connects with or follows members of the seller's team, particularly the founder, head of sales, or customer success lead, is running diligence on the people. This is a late-stage signal. The prospect is past the "is this product credible" question and into "who would I actually be working with."
The signal is rare, and it rarely appears by accident. Because it sits so late in the evaluation, the window is short.
How to stack intent signals for higher accuracy
No single signal is reliable enough on its own. The predictive power comes from stacking, meaning multiple signals firing on the same contact inside the same week.
A contact who visited pricing twice and liked two LinkedIn posts inside the same seven-day window sits in a different category to a contact who visited a homepage once. The first is mid-evaluation. The second may never enter the funnel at all.
This is why intent scoring matters. A score combines weighted inputs from every signal type into a single number that shows a sales team where to focus. Without scoring, reps drown in raw activity data and miss the pattern underneath it.
The 48–72 hour window: why speed beats volume
Intent signals have a short half-life. A contact who visited a pricing page three times on a Tuesday is not still thinking about it the following Monday. That contact has bought, deprioritised, or moved on to the next vendor.
The practical outreach window is 48–72 hours from the signal trigger. Outside that window, conversion drops sharply.
This is the structural reason manual intent monitoring breaks down. By the time a rep notices a signal in a weekly report, or a Slack notification is buried under standups, demos and pipeline reviews, the moment has passed. Teams that close the gap automate both the detection and the response, so a signal firing on Tuesday morning produces outreach on Tuesday afternoon.
Reaching out on job title and company size alone is an outdated playbook. The contacts ready to buy this week are already signalling it through behaviour. What is missing is a system that watches for it and responds before a competitor does.
B2B teams running outreach without intent data are already paying for signal they are not reading. The tools generating it are usually already in the stack, sitting in separate dashboards that nobody joins up.
See which contacts are ready this week
MeetIQ consolidates the buyer signals a company already generates across its website, email, calendar and ad platforms, scores them against the accounts that matter, and drafts the outreach when a signal crosses the warm threshold.