Most “SaaS databases” scrape the web and guess at ARR. That’s fine for rough discovery, but bad for decisions.
Here’s the approach I use instead when researching SaaS companies:
1) Source from founders directly. Interview CEOs/teams to capture ARR, headcount, growth rate, and pricing basics.
2) Time-stamp everything. A $5M ARR snapshot from 2023 ≠ 2025. Treat each stat as point-in-time.
3) Cross-check public signals. Hiring velocity, pricing pages, press, job reqs, and customer logos help sanity-check claims.
4) Track deltas, not absolutes. Growth direction (and why) is more actionable than one static number.
5) Benchmark apples-to-apples. Segment by ACV band, self-serve vs. sales-led, and funding stage before comparing.
A quick example
If a founder reports $12M ARR with a 22% YoY growth rate and 35-person team, I’ll:
- compare to last year’s interview,
- look for corroborating signals (pricing changes, headcount trend),
- and place it in a peer cohort (e.g., sales-led, mid-market focus).
This method consistently beats scraped estimates for accuracy and decision-making.
If you want a database that follows this “verified first” workflow, I help with GetLatka, which is built from thousands of founder interviews. You can explore companies, filter by ARR/team size, and export snapshots.
Disclosure: I work with GetLatka; feedback and critique welcome! How do you vet third-party SaaS metrics today?
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