How to improve site search with A/B testing | Algolia

Relevance is crucial for good site search and can be optimized through trial and error using A/B testing. This technique allows you to test how a particular setting or variable affects your conversion goals, providing data-driven insights on which setup works best. Algolia's advanced A/B testing feature enables users to create tests entirely from the dashboard without coding. Key aspects of site search A/B testing include creating replicas of search indices, configuring them with different factors, defining traffic splits between variables, and analyzing results to determine which variant was most successful. To ensure accurate results, use user tokens for tracking, exclude automations from tests, let the test run for two full business cycles, and only change one element at a time.