A/B Testing
Compare two versions of a design to see which performs better with real users.
What is it?
A/B testing (or split testing) presents two variants of a page, feature, or flow to different user segments simultaneously. By measuring behavior differences, you identify which version drives better outcomes, whether that's conversions, engagement, or task completion.
When to use it
Use A/B testing when you have a specific hypothesis to validate, such as 'a green CTA button converts better than blue.' It works best when you have enough traffic for statistical significance and a clear metric to optimize.
How to do it
Define your hypothesis and the metric you want to improve (e.g., click-through rate, sign-up rate).
Create two variants: a control (A) and a variation (B) with a single change.
Split your audience randomly and evenly between both versions.
Run the test long enough to reach statistical significance (typically 1-4 weeks).
Analyze the results and implement the winning variant.
Pro tips
Only test one variable at a time to isolate what actually caused the difference.
Don't stop a test early just because one variant looks ahead. Wait for significance.
Document every test, even failed ones. They build organizational knowledge.