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The State of B2B Buying Signals

The figures below are aggregated from 1,414 stored business-event records associated with 847companies, including funding, hiring, executive changes, launches, press, and M&A. They describe Intakra’s own early corpus, not the entire B2B market or purchase intent.

Dataset window October 29, 2025July 18, 2026

1,414
stored signal records in the clean corpus
847
companies represented in tracked records
100%
include a source URL
28%
of companies with records show 2+ event types

Finding 01

Launch and hiring records are frequent in this corpus.

Funding is the second-most-common event type in this dataset. Product-launch and hiring records appear more often here, but frequency does not measure predictive value, budget, or readiness to buy.

Funding428 · 30%
Hiring surge376 · 27%
Product launch294 · 21%
M&A114 · 8%
Press mention113 · 8%
Exec change69 · 5%
Layoffs15 · 1%
Tech change3 · 0%
news2 · 0%
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Finding 02

Some companies have more than one event type.

Of the 497 companies that surfaced any signal, 28% (141 companies) showed two or more distinct signal types, such as a funding round and a hiring surge. Multiple records may provide more context for review, but do not establish intent or predict conversion. Across the corpus, companies with at least one record averaged 2.8 signals each.

Finding 03

Source-link coverage is measured, not assumed.

Intent scores you can’t inspect are easy to distrust. In this dataset, 100% of signals link to a public source, drawn from 403 distinct outlets and enrichment feeds (press wires, financial news, job boards, LinkedIn). Of the signals our relevance judge scored, 61% came back at 0.9 confidence or higher. And it’s recent: 1,350 of 1,414 signals landed in the last 90 days.

Methodology

How we measured this

  • Stored records, not a survey. Figures are computed from 1,414rows in Intakra’s signal table, the same corpus used by 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 does not include those known date-parsing artifacts.
  • 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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