A/B Test Report
Measure experiment impact
The A/B Test Report provides rigorous statistical analysis of your experiments. It calculates "certainty of improvement" to tell you not just which variant performed better, but whether that difference is statistically significant. No more guessing - know when you have a real winner.
Get Started for FreeWhy This Report Matters
Bad experiment analysis leads to bad decisions. Ship a "winner" that isn't actually better, and you've degraded your product. This report gives you the statistical confidence to ship improvements that actually improve outcomes.
Questions This Report Answers
If you're asking these questions, the A/B Test Report is your answer.
Did the new landing page actually improve conversion?
Is the difference between variants statistically significant?
How certain can we be that B is better than A?
What should we do when there's no clear winner?
How long should we run this experiment?
A/B Test Report in Action
Interactive demo or screenshot showcasing the A/B Test Report interface, configuration options, and example insights.
Key Capabilities
Everything the A/B Test Report can do for your analysis.
Statistical Significance Testing
Go beyond simple percentage comparisons. Get p-values and confidence intervals that tell you whether differences are real.
Certainty of Improvement
See the probability that one variant is actually better than another. "95% certain B beats A" is more actionable than "B is 5% higher."
Variant Comparison
Compare any number of variants against control. See performance metrics side-by-side with statistical context.
Conversion Impact
Understand the real-world impact of choosing the winning variant. Project how many additional conversions you'll get.
Inconclusive Results Guidance
When there's no clear winner, get recommendations on whether to run longer, try bigger changes, or call it a tie.
Segment Analysis
Break down results by user segment. A variant might win overall but lose for specific audiences.
Real-World Use Cases
How teams use the A/B Test Report to drive business results.
Landing Page Optimization
Test headlines, CTAs, layouts, and messaging.
Example:
New headline increased signup rate from 3.2% to 4.1% with 98% certainty.
Pricing Page Tests
Experiment with pricing presentation and plan structures.
Example:
Showing annual pricing first increased annual plan selection by 23%.
Onboarding Flow Experiments
Test different onboarding approaches and their impact on activation.
Example:
Shorter onboarding improved completion rate but reduced 30-day retention - kept the original.
Feature Variations
Test different implementations of product features.
Example:
Simplified dashboard increased daily active usage by 15% with no impact on feature adoption.
Pro Tips
Get the most out of the A/B Test Report with these expert recommendations.
Don't peek at results too early - let experiments reach statistical significance.
Calculate sample size needed before starting to know when you'll have conclusive results.
Test one thing at a time when possible for clearer attribution.
Segment your results - a winning variant overall might hurt specific user groups.
Document learnings from every experiment, even inconclusive ones.
Ready to try the A/B Test Report?
Free to start. Full access to all 9 report types.