ab-test-plan

# /digital-marketing-pro:ab-test-plan ## Purpose Dedicated A/B test planning with a structured hypothesis framework, statistical sample size calculation, variant design, and monitoring plan. Produces a complete experiment specification with statistical rigor and clear decision criteria. ## Input Required The user must provide (or will be prompted for): - **Element to test**: The specific page, component, or experience being tested (landing page headline, CTA button, pricing page layout, email subject line, checkout flow, form design, etc.) - **Current conversion rate**: Baseline conversion rate for the metric being tested (or best estimate) - **Desired minimum detectable effect (MDE)**: The smallest improvement worth detecting (e.g., 10% relative lift) - **Daily traffic or impressions**: Average daily visitors or impressions to the test page or element - **Significance level**: Desired confidence level, default 95% (alpha = 0.05) - **Statistical power**: Desired power, default 80% (beta = 0.20) - **Number of variants**: How many variants to test (default 1 treatment + 1 control; more for multivariate) - **Business context**: What prompted the test idea (analytics data, user feedback, competitive analysis, heuristic audit, stakeholder request) ## Process 1. **Load brand context**: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply voice, compliance, industry context. Check `guidelin...