Quick answer
Same-conditions retest means collecting generative answers again under the same prompts, model set, language, and sampling window, then comparing what changed and what remains uncertain. In Winin, Edith owns retest archives; the homepage states formal conclusions require retained answers, verified publication, and comparable retesting.
Treating a one-off “ChatGPT mentioned us today” as an operating win—without a stable baseline—is not comparable evidence.
Details
Conditions worth freezing
- Exact prompt text (including language)
- Model / product surface
- Sampling window and replicate policy
- Competitor set (for comparison prompts)
- Logged fields: mentioned, shortlisted, accurately recommended, reasons, cited URLs
Why it matters
Training data, retrieval paths, and generation policies drift; different answers on different days are normal. Retest constrains whether the direction of change is explainable—it does not guarantee percentage lifts.
Versus initial signal
“5 fixed questions · one sample · up to 3 active model APIs” is an initial signal, not a formal baseline. Operating teams should upgrade to a Formal Baseline (scoped quote) and keep retesting under the same conditions.
Related facts
FAQ
Q: Why must conditions match?
A: Otherwise you cannot separate content change from model drift; one answer is not a formal conclusion.
Q: Who runs retest?
A: In Winin, Edith owns retest archives.
Contact: contact@winin.ai · Canonical facts: /en/facts/*/ and https://winin.ai · Updated 2026-09-11