Checklist

Rapid Experiment Review Rubric

A concise, interactive review checklist and decision rubric to evaluate short-cycle experiments and record a clear stop/iterate/scale decision with next steps and learning capture.

Interactive Tool

Rapid Experiment Review Rubric

Use this short review to capture reliable evidence from a rapid experiment and make a clear decision: scale, iterate, stop, or monitor. Record facts, signal strength, operational risks, and recommended next steps so learning is preserved and decisions are repeatable.

Quick decision rules (examples): Scale when the hypothesis is clear, metrics are reliable, effect size is meaningful, evidence strength is at least preliminary or better, and operational risks are acceptable. Iterate when findings are promising but noisy, metrics are immature, or learnings point to a refined hypothesis. Stop when there is no meaningful effect or risks outweigh benefits. Monitor when results are inconclusive but worth tracking.

Short name that matches your experiment tracker
Person responsible for next steps and follow-up
A clear hypothesis names expected change, metric, direction, and audience
Paste the exact hypothesis used for the experiment
Metric used to judge success (include units)
1 = Not reliable, 5 = Highly reliable
1.0 10.0
Describe the size and direction (e.g., +12% conversion, -3 minutes per transaction). Include confidence interval or error if available.
Number of users, transactions, days, impressions, etc.
How strong is the supporting evidence?
Consider safety, compliance, cost, staffing, technical debt, and customer impacts
Describe the risks, mitigation options, and conditions required to accept them
List negative or surprising side effects noticed during the experiment
Short summary of qualitative feedback informing the decision
Choose the recommended next action
Explain clearly why this recommendation follows from the evidence and risk assessment
List immediate actions, owners, and target dates. For 'scale', include rollout scope; for 'iterate', describe the variation to test.
Link to your experiment tracker, notes, or post-mortem document
What should others know? What assumptions changed? What constraints matter?
1 = Low confidence, 5 = High confidence
1.0 10.0
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