From atum-cms-ecom
Content experimentation and A/B testing guidance covering experiment design, hypotheses, metrics, sample size, statistical foundations, CMS-managed variants, and common analysis pitfalls. Use this skill when planning experiments, setting up variants, choosing success metrics, interpreting statistical results, or building experimentation workflows in a CMS or frontend stack.
npx claudepluginhub arnwaldn/atum-plugins-collection --plugin atum-cms-ecomThis skill uses the workspace's default tool permissions.
Principles and patterns for running effective content experiments to improve conversion rates, engagement, and user experience.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Guides idea refinement into designs: explores context, asks questions one-by-one, proposes approaches, presents sections for approval, writes/review specs before coding.
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 interpretation