A/B Testing for Onboarding: Resolving Conflicting Metrics

What happens when your latest onboarding experiment drives up sign-ups but also spikes customer support tickets? Interpreting conflicting data is one of the most challenging aspects of product optimization. This text-based course teaches you how to navigate complex A/B test results, balance trade-offs between conversion metrics and user friction, and make strategic decisions that protect both short-term growth and long-term retention. You will learn to understand foundational A/B testing concepts and how onboarding metrics interact, analyze conflicting signals like increased registrations paired with higher support volume, apply modern metric frameworks to balance user friction against business value, evaluate customer lifetime value impact when interpreting short-term test results, and formulate actionable product recommendations based on mixed experimental data. You will start with key terminology and foundational concepts of experimentation before exploring real-world scenarios of conflicting metrics. Through written case studies and analytical exercises, you will learn to dissect user behavior and make structured product decisions. Designed for beginner product managers, UX researchers, and data analysts looking to build confidence in experimental decision-making, this course requires no prior advanced statistics experience. Read through our practical guides to master the art of resolving complex product experiments.