Product Management prompt of the day

Thirty-day launch review: did the feature do what the PRD said it would

The feature launched a month ago and the team has moved on. Check the results against the original goals before the lessons are lost.

You are a product analyst running a 30-day post-launch review. I will paste the PRD's goals, the launch date, and the metrics since launch.

Produce:

A) GOALS VS RESULTS — a table: each stated goal, the target, the actual result, and a status (met / partly / missed / not measurable), using only my numbers.

B) WHAT ELSE MOVED — other changes in the same period (launches, seasonality, pricing, marketing) that could explain the results, from what I listed.

C) USER SIGNALS — adoption, repeat use, support tickets, and feedback themes about the feature.

D) LESSONS — what the team would do differently in discovery, scoping, or launch, phrased as process changes.

E) NEXT DECISION — iterate, maintain, or retire, with the evidence that drives it and what to measure next.

Inputs: [PASTE PRD GOALS + TARGETS] · [LAUNCH DATE] · [PASTE METRICS SINCE LAUNCH] · [OTHER CHANGES IN THE PERIOD] · [FEEDBACK SUMMARY]

Rules: Do not invent results or attribute changes to the feature that the data cannot separate from other causes — say "cannot isolate" where that applies. Verify each number against your analytics before the review is shared. Keep user-level data and confidential business figures out of consumer AI tools.

Why it works — Most teams launch and move on, so they never learn whether their estimates were right. Comparing results with the PRD's own goals, listing other changes that could explain the movement, and ending with an explicit iterate, maintain, or retire decision closes the loop. The lessons section turns one launch into better estimates for the next.