Cro Optimization
Run conversion rate optimization through hypothesis-driven testing including audit...
Install
npx skills add rampstackco/claude-skills --skill cro-optimization -g -a claude-code -y- Repository
- rampstackco/claude-skills1k
- Category
- Design
- Updated
- 9d ago
- License
- MIT
- Context cost
- Mediumabout 2,527 tokens
- Runs scripts
- No, instructions only
What it does
Run conversion rate optimization through hypothesis-driven testing including audit, hypothesis generation, test design, statistical analysis, and rollout decisions. Use this skill whenever the user wants to optimize conversion, run A/B tests, audit a funnel, generate test hypotheses, design experiments, or analyze test results. Triggers on conversion optimization, CRO, A/B test, split test, multivariate test, hypothesis, conversion funnel, funnel audit, experiment design, statistical significance, lift, optimization. Also triggers when the user has a conversion problem and isn't sure where to start, or when test results are ambiguous and need interpretation.
CRO Optimization
Run conversion rate optimization as a structured discipline: audit → hypothesize → test → decide. Stack-agnostic. Tool-agnostic.
This skill is for running tests against existing pages and flows. For writing landing page copy from scratch, use landing-page-copy. For setting up the analytics that make CRO possible, use analytics-strategy.
When to use
- Converting traffic at lower rate than expected
- Specific funnel step has high drop-off
- Pages with high traffic that could move the needle if optimized
- A/B testing infrastructure exists (or can be set up)
- Statistical significance and sample size questions
When NOT to use
- Without sufficient traffic to test (under ~5,000 monthly conversions per variant)
- Pre-launch (no users to test on yet)
- Strategy or messaging-level questions that need qualitative research first
- Brand-defining choices (CRO can't optimize a fundamentally wrong brand)
Required inputs
- The page or flow under optimization
- Current conversion rate and traffic volume
- Access to analytics (event tracking, funnel data)
- An A/B testing tool (or willingness to set one up)
- Time and budget for testing (typically 2 to 8 weeks per test)
The framework: 4 phases
1. Audit
Diagnose before treating.
Quantitative audit:
- Funnel data. Where are users dropping off? The biggest drop is the biggest opportunity.
- Segmentation. Does the funnel perform differently by source, device, geography, audience type?
- Performance data. Are slow pages dragging conversions?
- Search Console / on-site search. What are users looking for that they can't find?
Qualitative audit:
