A/B Test Planner Skill

Design experiments that produce trustworthy results — not just directional signals. Every test output includes hypothesis, success metrics, sample size, duration, and a results interpretation guide.

Required Inputs

Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked (assumed, confirm) and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about).

• What is being tested (feature, UI change, copy, pricing, onboarding step)
• Hypothesis (or ask to help formulate one)
• Primary metric (conversion rate, click-through, completion rate, etc.)
• Baseline rate and minimum detectable effect (MDE)
• Daily eligible users (to calculate duration)

Experiment Design Checklist