A/B Testing

Definition

A/B testing splits your users into two groups, shows each group a different version of a page, email, or feature, and measures which one wins on a specific metric (signups, clicks, conversion rate, etc.). It's the bedrock of evidence-based product and marketing work — instead of guessing whether a new headline is better, you measure. Good A/B tests have a clear hypothesis, a single variable changed, enough sample size for statistical significance, and a decision rule defined upfront. AI agents can help you set up tests properly, calculate sample sizes, analyze results without falling for false positives, and write up clear ship/stop recommendations.

Related agent skills