A/B Testing
The discipline of running controlled experiments to measure causal impact of product changes — the foundation of data-driven product development.
A/B testing (controlled experimentation) is the gold standard for measuring whether a product change actually improves user behavior rather than just correlating with it. Running rigorous experiments requires statistical knowledge (significance testing, power analysis, p-values, confidence intervals) and understanding of common pitfalls (novelty effects, peeking, Simpson's paradox). Platforms like Optimizely, Statsig, and LaunchDarkly operationalize experimentation at scale.
Typical time to job-readiness: ~4 weeks.