Designs statistically valid A/B tests and experiments to optimize product performance and conversion rates.
This skill transforms Claude into an experimentation expert, guiding users through the end-to-end process of setting up rigorous A/B, A/B/n, and multivariate tests. It provides structured frameworks for building actionable hypotheses, calculating required sample sizes to avoid 'peeking' errors, and selecting primary, secondary, and guardrail metrics. Whether you are testing UI changes, copy variants, or backend algorithms, this skill ensures your experiments produce mathematically sound results that drive informed business decisions.
主要功能
01Statistical significance and p-value interpretation for post-test analysis
02Guidance for both client-side and server-side implementation
03Comprehensive metric selection (Primary, Secondary, and Guardrail)
04Sample size and test duration calculation tables
