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 693 real buying signals we detected across 1,110B2B 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 April 13, 2026 – September 24, 2026
Finding 01
The signal mix extends beyond one category.
Funding is the most frequent single category in this watchlist at this update. The rows below show how many detections fell into each type; counts do not tell us which types lead to sales.
Dated analysis · September 25, 2026
A frozen look at the 687-signal September 24 corpus shows what a funding-only filter would omit, with the category counts and a controlled timing-score check available to download.
Read the beyond-funding research snapshot →Finding 02
The best accounts stack signals.
Of the 305 companies that surfaced any signal, 29% (89 companies) showed two or more distinct signal types, for example 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 2.3 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 194 distinct outlets and enrichment feeds (press wires, financial news, job boards, LinkedIn). Of the signals our relevance judge scored, 48% came back at 0.9 confidence or higher. And it’s recent: 425 of 693 signals landed in the last 90 days.
Methodology
How we measured this
- Real detections, not a survey. Every figure is computed live from 693 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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