Free A/B testing course – Framework for effective, repeatable experiments

Summary: This free, tool-agnostic course provides a six-module framework to improve A/B testing processes by focusing on hypothesis development, statistical significance, and repeatable systems. It addresses common errors like premature test termination and reliance on vanity metrics, based on insights from over 3,000 teams and real experiments.

What it does

The course teaches what to test, how to form hypotheses, calculate sample sizes, interpret results, and avoid common mistakes. It guides teams to build a monthly testing system rather than one-off experiments.

Who it's for

It is designed for teams and individuals conducting A/B tests who need a structured, process-driven approach to improve test validity and impact.

Why it matters

It solves the problem of ineffective A/B testing caused by poor methodology, helping teams generate reliable data that can drive meaningful revenue improvements.