What problem does it solve? Teams often run experiments without clear hypotheses, stop tests too early, or misread results, leading to false conclusions and wasted traffic. This Skill provides a structured framework for planning, running, and analyzing A/B tests and building a continuous experimentation program. ## Core Features & Use Cases - Hypothesis & Test Design: Builds structured hypotheses, selects test types (A/B, A/B/n, MVT), defines primary, secondary, and guardrail metrics, and plans traffic allocation. - Sample Size & Duration Guidance: Provides quick-reference sample size tables, duration formulas, and sequential testing guidance via the references/sample-size-guide.md file. - Experimentation Program Management: Covers ICE prioritization, experiment velocity tracking, playbooks, and documentation templates in references/test-templates.md. - Use Case: A marketer wants to test a new pricing page headline. The Skill calculates the required sample size from the baseline conversion rate, defines metrics, warns against peeking early, and produces a complete test plan. ## Quick Start Ask the assistant to help you design an A/B test for a specific page or change, providing your current conversion rate and traffic volume.
