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Guides content experimentation and A/B testing: experiment design, hypotheses, metrics, sample size, statistical foundations, CMS-managed variants, and common analysis pitfalls.
How this skill is triggered — by the user, by Claude, or both
Slash command
/sanity:content-experimentation-best-practicesThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Principles and patterns for running effective content experiments to improve conversion rates, engagement, and user experience.
Principles and patterns for running effective content experiments to improve conversion rates, engagement, and user experience.
Reference these guidelines when:
Comparing two variants (A vs B) to determine which performs better.
Testing multiple variables simultaneously to find optimal combinations.
The confidence level that results aren't due to random chance.
Making decisions based on data rather than opinions (HiPPO avoidance).
Start with the reference that matches the current problem, such as design, statistics, CMS integration, or pitfalls. See references/ for detailed guidance:
references/experiment-design.md — Hypothesis framework, metrics, sample size, and what to testreferences/statistical-foundations.md — p-values, confidence intervals, power analysis, Bayesian methodsreferences/cms-integration.md — CMS-managed variants, field-level variants, external platformsreferences/common-pitfalls.md — 17 common mistakes across statistics, design, execution, and interpretationnpx claudepluginhub sanity-io/agent-toolkit --plugin sanityGuides planning, designing, and implementing A/B tests, split tests, multivariate experiments. Covers hypotheses, sample sizes, test types, statistical principles.
Plans, designs, and implements A/B tests with statistical rigor, hypothesis frameworks, and sample size calculations.
Designs and implements A/B tests with statistical rigor, hypothesis framework, and sample size calculations. Activates on experimentation queries.