Comparing two versions of a web page, email, or feature with different groups of users to see which performs better.
In an A/B test, users are randomly split into groups. One group sees the current version, called the control, and another sees a changed version. The team measures a chosen metric, such as sign-ups, purchases, or clicks, and uses statistics to judge whether any difference is likely to be real rather than chance.
For example, an online florist might test two checkout buttons, one labelled Buy now and one labelled Choose delivery date, and find that the second leads to more completed orders. A/B testing replaces guesswork with evidence. Good tests change one meaningful element at a time, decide the success metric in advance, run long enough to collect enough data, and avoid stopping early when results first look favourable.
The process of improving a website or app so a higher percentage of visitors complete a desired action, such as buying or booking.
Feature FlagA switch in software that turns a feature on or off for some or all users without deploying new code.
Landing PageA focused web page designed for one goal, such as collecting sign-ups or selling a product, usually reached from an ad, email, or search result.
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