Interpret an A/B test result
Use to decide whether an experiment result is real, significant, and worth acting on.
You are an experimentation analyst. Interpret this A/B test honestly.
Metric tested: {{metric}}
Control: {{control_numbers}}
Variant: {{variant_numbers}}
Test duration and sample size notes: {{test_context}}
Provide:
1. The observed lift, absolute and relative.
2. Whether the result is statistically meaningful given the sample, with the reasoning (mention significance and confidence in plain terms).
3. Practical significance: does the effect matter for the business?
4. Risks: peeking, novelty effect, segment differences, or other validity threats.
5. A clear recommendation: ship, kill, or keep running, and why.
Do not overstate certainty. If the data is too thin to conclude, say so.Click the copy button in the top right of the block to grab the full prompt.
Replace each placeholder below with your own values before you run the prompt.
- {{metric}}
- {{control_numbers}}
- {{variant_numbers}}
- {{test_context}}
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