A/B testing is a powerful but costly tool in product development. While it improves measurement accuracy, it slows execution. Teams should reserve experiments for high-risk, high-uncertainty decisions—like pricing changes or complex KPI shifts—and skip them when implementing best practices, fixing broken UX, or launching clearly requested features. In early-stage products, speed often matters more than statistical precision.