Primary Research

Our quantitative findings come from structured 45-minute interviews conducted with 41 mid-market SaaS QA teams in Q1–Q2 2026. Qualifying criteria: US-based, 25–200 engineers, at least one dedicated QA function (in-house or outsourced). Interviews were recorded with participant consent and transcribed for analysis.

Key findings from that cohort:

27 of 41 teams had paused or cancelled an SDET hire in the prior 12 months.
Average fully-loaded SDET cost (US): $200K+ annually, including benefits, recruiting, and onboarding.
83% of teams lacked a dedicated QA engineer — QA responsibility fell on developers or a shared QA contractor.

Interview notes are anonymised before publication. We do not name individual participants or their employers without explicit written permission.

Secondary Data Sources

We attribute every third-party statistic to its named primary source. Recurring sources include:

npm-stat.com — download counts for open-source testing packages (Playwright, Cypress, etc.).
Stack Overflow Developer Survey — language, framework, and toolchain adoption by year.
GitHub (via Microsoft) — repository activity, contributor counts, and release cadence for open-source projects.
G2 / Capterra — user reviews and ratings for commercial QA tools; used to cross-check vendor-supplied benchmark numbers.
US Bureau of Labor Statistics — salary data for software quality assurance roles.

Editorial Standards

We do not fabricate data or extrapolate beyond what our sample supports.
We do not publish vendor-supplied benchmark numbers without independent verification against public documentation or third-party reviews.
All competitor claims are cross-checked against the competitor's current public pricing page, documentation, and G2/Capterra reviews at the time of writing.
Posts written about QAby.AI product capabilities are clearly labelled as first-party content. We do not present marketing copy as independent analysis.

Corrections Policy

If a factual error is reported and confirmed, we correct it with an inline note indicating what changed and when. We do not make silent edits to published claims. If a correction materially changes the conclusion of a post, we note that explicitly at the top.

To report an error, email hello@qaby.ai with the URL of the post and the specific claim you believe is incorrect.

Contact

Questions about our research methodology or editorial process: hello@qaby.ai