A/B Testing & Experimentation Design

Phase progress0 / 0 completed

A/B testing and structured experimentation are core practices of modern product management. Instead of relying on intuition or opinions, they enable teams to validate hypotheses with real user data. By splitting users into randomized groups, testing variations, and measuring impact against clear success metrics, product managers reduce risk, uncover hidden opportunities, and continuously optimize the user experience. This module introduces the foundations of product experimentation, covers how to design and run valid A/B tests, highlights advanced techniques like multivariate and funnel testing, and provides practical guidance on turning test results into actionable product decisions.

1) Types of Experiments

A/B Testing: Compare two versions (control vs. variation) to see which performs better.
Multivariate Testing (MVT): Test multiple elements/variables at once to find optimal combinations.
Funnel Testing: Evaluate changes across an entire user journey (e.g., onboarding flow).
Split Testing: Serve different versions of entire pages/experiences to separate audiences.

2) Steps for Running an A/B Test

Research: Gather quant + qual data to understand the problem space.
Develop Hypothesis: Make it specific, measurable, and falsifiable.
Select Variable: Test one meaningful change (unless running MVT).
Define Metrics: Establish primary/guardrail metrics before launch.
Target Users: Randomize assignment or segment intentionally.
Design Variants: Control (A) vs. Challenger (B) with clear rationale.
Set Sample Size & Duration: Use a power/significance calculator to avoid false positives.
Run Simultaneously: Avoid seasonality/time bias by running in parallel.
Analyze Results: Check statistical significance and side effects on guardrails.
Turn Data into Action: Roll out winners, document learnings, and refine hypotheses.