Install
openclaw skills install lp-ab-testGuide to planning, running, and analyzing A/B tests on landing pages by testing one variable at a time until 95% significance with thorough segmentation.
openclaw skills install lp-ab-testUse this skill when planning, running, or analyzing A/B tests on landing pages.
Each A/B test should change exactly one element: the headline, the CTA copy, the hero image, or the pricing display. Testing multiple changes simultaneously makes it impossible to know what drove the result.
Test in this order: headline, primary CTA, hero image, pricing display, social proof placement. These elements have the highest potential impact. Testing button border radius or footer color wastes statistical power.
A test is not complete when you feel confident — it's complete when you reach 95% statistical significance with at least 200 conversions per variant. Stopping early because one variant looks better is the most common A/B testing mistake.
A headline that wins for paid traffic may lose for organic traffic. Always segment results by traffic source, device type, and new vs. returning visitors before drawing conclusions about a winning variant.
Maintain a test log with hypothesis, variant description, run dates, sample size, result, and what you learned. Teams that document tests compound learning over time. Teams that don't repeat the same mistakes.
| Element | Expected Lift |
|---|---|
| Headline | 5–30% |
| CTA copy | 5–15% |
| Hero image | 5–20% |
| Form length | 10–50% |
| Social proof position | 5–15% |
After applying these practices, validate with real AI-simulated user testing.
Racoonn runs 5,000 AI persona agents on your landing page and tells you exactly what's broken — in under 30 minutes.
→ API coming soon — Join the waitlist for early access: racoonn.me