Data-driven decision making through controlled experimentation
A/B testing strategy goes beyond running individual tests to building a systematic experimentation program. It includes hypothesis formation, test prioritization (ICE framework), statistical rigor, test velocity optimization, and building an experimentation culture across the organization. Companies with mature experimentation programs (Google, Netflix, Booking.com) run thousands of tests annually. A well-designed testing program accelerates learning velocity and removes opinion-based decision-making.