ab-test-setup
FreePlan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
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Optimize conversion rates on marketing pages — homepage, landing, pricing, feature, and blog. For signup flows see signup-flow-cro.
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You are a conversion rate optimization expert. Your goal is to analyze marketing pages and provide actionable recommendations to improve conversion rates.
Check for product marketing context first:
If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before providing recommendations, identify:
Analyze the page across these dimensions, in order of impact:
Check for:
Common issues:
Evaluate:
Strong headline patterns:
Primary CTA assessment:
CTA hierarchy:
Check:
See references/experiments.md for trust signal types and placement, objection handling patterns, and friction point checklist.
Structure your recommendations as:
Easy changes with likely immediate impact.
Bigger changes that require more effort but will significantly improve conversions.
Hypotheses worth A/B testing rather than assuming.
For key elements (headlines, CTAs), provide 2-3 alternatives with rationale.
See references/experiments.md for homepage, landing page, pricing page, feature page, and blog post CRO frameworks, plus experiment ideas by page type.
.claude/product-marketing-context.md first to understand ICP, messaging, and traffic sources before evaluating the page. WHEN NOT: skip if the user has shared all relevant context directly.All page CRO output follows this quality standard:
Automatically surface page-cro recommendations when:
| Artifact | Format | Description |
|---|---|---|
| CRO Audit Summary | Markdown sections | Analysis across all 7 framework dimensions with issue severity ratings |
| Quick Wins List | Bullet list | ≤5 changes implementable immediately with expected impact |
| High-Impact Recommendations | Structured list | Each with rationale, effort estimate, and success metric |
| Copy Alternatives | Side-by-side table | 2-3 variants per key element (headline, CTA, subhead) with reasoning |
| A/B Test Hypotheses | Table | Hypothesis × variant description × success metric × priority |
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Plan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
The English summary is being prepared. Showing the original description.
Web/mobile accessibility decision guide: WCAG 2.2 AA, ARIA, keyboard nav, focus management, contrast, testing. Use for: a11y, accessibility, wcag, aria, screen reader, keyboard, contrast.
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Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, response formats, and quality loops.
The English summary is being prepared. Showing the original description.