Data report · refreshed continuously

The State of B2B Buying Signals

Most “intent data” is a black box. This isn’t. Everything below is aggregated from 873 real buying signals we detected across 433B2B companies — funding rounds, hiring surges, exec moves, launches, press and M&A — each one cited to a public source. Here’s what watching that many companies actually looks like.

Dataset window October 29, 2025July 11, 2026

873
verified buying signals recorded
433
companies watched for intent
100%
carry a cited, clickable source
43%
of active companies show 2+ signal types

Finding 01

The market runs on launches and hiring, not just funding.

Funding gets the attention, but it’s the third-most-common trigger in our data. Product launches and hiring surges — the signals that a team is actively building and buying — dominate.

Product launch240 · 27%
Hiring surge228 · 26%
Funding164 · 19%
Press mention102 · 12%
M&A81 · 9%
Exec change48 · 5%
Layoffs10 · 1%

Finding 02

The best accounts stack signals.

Of the 251 companies that surfaced any signal, 43% (108 companies) showed two or more distinct signal types — e.g. a funding round anda hiring surge. Those are the “why now” accounts: multiple independent triggers pointing at the same company at the same time. Across the corpus, active companies averaged 3.5 signals each.

Finding 03

Every signal is auditable.

Intent scores you can’t inspect are easy to distrust. In this dataset, 100% of signals link to a public source, drawn from 323 distinct outlets and enrichment feeds (press wires, financial news, job boards, LinkedIn). Of the signals our relevance judge scored, 63% came back at 0.9 confidence or higher. And it’s recent: 870 of 873 signals landed in the last 90 days.

Methodology

How we measured this

  • Real detections, not a survey. Every figure is computed live from 873 signals stored in our production database — the same detection pipeline behind the free scan.
  • Clean set only. We exclude any rows whose detection timestamp resolves to a future date (an upstream date-parsing artifact), so the report never publishes a signal we can’t stand behind.
  • What we don’t claim. Detection timestamps include a historical backfill, so we deliberately do notreport a “time-to-surface” latency — the data isn’t clean enough to state one honestly. This is also an early dataset drawn from our own watchlists; it describes the signals we’ve seen, not the entire B2B market.

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