What problem does it solve? Teams often run experiments without clear hypotheses, adequate sample sizes, or disciplined analysis, leading to false positives and wasted traffic. This Skill guides the planning, execution, and analysis of A/B tests so results are statistically valid and actionable. ## Core Features & Use Cases - Hypothesis & Test Design: Structures hypotheses with a formal framework and selects the right test type (A/B, A/B/n, MVT, split URL) based on traffic and goals. - Sample Size & Duration Planning: Provides quick-reference tables, duration formulas, and guidance for multiple variants and sequential testing via detailed reference guides. - Metrics & Analysis Framework: Defines primary, secondary, and guardrail metrics, plus checklists for significance testing, segment analysis, and avoiding the peeking problem. - Use Case: A marketer wants to test a new pricing page headline. The Skill calculates required sample size from the baseline conversion rate, defines success and guardrail metrics, sets a fixed duration, and produces a documented test plan. ## Quick Start Ask the assistant to help design an A/B test for a specific page or change, providing your current conversion rate and traffic volume.
