The Hidden Flaws in Your A/B Testing Strategy Nobody Talks About

Safe testing offers a more flexible and reliable approach to experimental design by allowing the combination of p-values and optional continuation without invalidating statistical results. This method addresses common A/B testing challenges such as novelty effects, metric convergence delays, and sample ratio mismatches (SRMs). By incorporating guardrail metrics, monitoring sample ratios, and enabling mid-test decisions, safe testing ensures more accurate, bias-resistant insights for product and feature evaluation.