What is A/B Testing? Definition, Benefits & Best Practices

A/B testing, also known as split testing, is a method used to determine which version of a design or feature performs better by comparing user interactions between different variations. It is a crucial tool for conversion rate optimization (CRO), allowing teams to make data-driven decisions based on actual user behavior rather than assumptions. There are various types of A/B tests, such as classic A/B, A/B/n, multivariate, and multi-armed bandit testing, each suited for different objectives and scales. Feature flags and progressive rollouts enhance experimentation by enabling safe testing and gradual deployment to minimize risk. Metrics like conversion rate, click-through rate, and bounce rate are employed to measure success, while mistakes such as stopping tests too early or running overlapping experiments can lead to inaccurate conclusions. A/B testing is particularly significant in app development due to challenges like app store versioning and the risk of uninstalls. Automation, especially AI-powered tools, is essential to ensure seamless testing and maintain user experience. Ultimately, A/B testing is about learning and refining designs to improve user experience, supporting sustainable growth by identifying what resonates best with the audience.