Showing two versions of a page or feature to two groups of users at the same time to see which performs better.
In an A/B test, half your visitors might see version A of a page and the other half version B, which differs in one element: a headline, a button color or the order of prices. You then compare results, such as purchase or sign-up rates, to learn which version is better based on real data, not opinions.
This protects you from decisions based on personal taste and sometimes reveals that a change that looked like an improvement was worse. But it needs enough visitors for the result to be reliable; with low traffic, differences may just be chance.
Practical tip: change one element per test, decide in advance which metric you will judge by and how long the test runs, and do not stop early just because one version seems ahead. If your traffic is low, customer interviews may teach you more.