Product Experiment Design Framework
Design a comprehensive product experiment to test [hypothesis about user behavior or feature impact]. Include: 1) Detailed hypothesis statement in 'If-Then-Because' format, 2) Independent and dependent variables with operational definitions, 3) Experimental design type (A/B, multivariate, switchback, etc.) with rationale, 4) Sampling strategy and required sample size calculation, 5) Control for confounding variables, 6) Implementation specifications, 7) Data collection plan, 8) Analysis methodology including statistical tests, 9) Decision criteria for success/failure, and 10) Follow-up actions based on potential outcomes.
How to Use This Prompt
- Copy the prompt using the button above
- Replace placeholders in [brackets] with your specific details
- Paste into your AI assistant (ChatGPT, Claude, Gemini, etc.)
- Iterate as needed - ask follow-up questions to refine the output
Why This Prompt Works
This prompt enforces scientific rigor by requiring the If-Then-Because hypothesis format, explicit variable definitions, and sample size calculations. The ten-component structure ensures you plan not just the experiment itself but also the decision criteria and follow-up actions, preventing the common trap of running tests without knowing what you will do with the results.
When to Use This Prompt
- Planning an A/B test or multivariate experiment and need a statistically sound design document
- Advocating for experimentation with stakeholders who need to see a rigorous methodology
- Building a culture of experimentation and want a standardized template your team can reuse
Tips for Better Results
- State your current traffic volume or user base size so the AI can estimate realistic sample sizes and test durations
- Describe the minimum detectable effect you care about so the statistical power calculations are meaningful
- Mention any previous related experiments and their results to help the AI build on existing learnings