A/B Testing: Data-Driven Design
While usability testing tells you why a user behaves a certain way (Qualitative), A/B testing tells you what performs better at scale (Quantitative). It involves splitting your live traffic between two variants of a page to see which yields a higher conversion rate.
When to use A/B Testing
A/B testing is for optimization, not innovation. You don't A/B test two entirely different business models. You A/B test whether the "Add to Cart" button converts better when it's Green (Variant A) or Orange (Variant B).
Statistical Significance is Non-Negotiable
A common mistake among junior teams is stopping an A/B test too early. If Variant A gets 10 conversions and Variant B gets 12, Variant B didn't "win." It's statistical noise. You must let the test run until a statistical calculator confirms a 95% confidence level. This requires high traffic volumes.
Multivariate Testing (MVT)
An advanced version of A/B testing. Instead of testing one element on a page against another, you test multiple variables simultaneously (e.g., testing 3 headlines and 2 button colors at the same time). This requires massive amounts of traffic but provides deep insights into how variables interact.