Apply the testing process iteratively for continuous system improvement. Other salient applications of A/B testing , besides e-commerce and website design, include ad performance analysis in marketing, experimentation on new features in mobile apps, comparing machine learning models, and clinical trials in healthcare. A/B testing (also known as bucket testing , split-run testing or split testing ) is a user-experience research method. [1] A/B tests consist of a randomized experiment that usually involves two variants (A and B), [2][3][4] although the concept can be also extended to multiple variants of the same variable. What Precisely Is A/B Testing ? A/B testing or split testing , in a nutshell, is a means to compare two iterations of an email, website, or other marketing asset and assess the performance differences between them. A/B testing (sometimes also referred to as split testing ) is a popular UX research method, with widespread adoption across businesses and industries. To ensure reliable, meaningful, and beneficial results for your organization, follow best practices and avoid common mistakes when planning and setting up an A/B test .
