Why A/B Test
Opinions differ but data doesn't. A/B testing removes guesswork from product decisions and helps you optimize for what actually works.
Experiment Design
Define a clear hypothesis. Choose a single primary metric. Determine success criteria before running the test.
Implementation
Use Firebase Remote Config, Optimizely, or LaunchDarkly for feature flags. Ensure consistent experiences for users.
Sample Size
Calculate required sample size before starting. Underpowered tests lead to inconclusive or misleading results.
Statistical Analysis
Understand statistical significance versus practical significance. Use proper analysis methods. Don't peek at results early.
Common Mistakes
Avoid multiple comparison problems. Don't stop tests early. Consider novelty effects. Document and share learnings.
Building Culture
Make testing part of your development process. Celebrate learning, not just wins. Build organizational capability over time.