A/B testing, also called split testing, is a quantitative UX research method that compares two design versions using real user behavior to identify the top-performing option. Version A is the control, typically the existing design, and Version B is the variant, the new design competing against it. The winning version is selected using performance metrics such as click-through rate, conversion rate, bounce rate, and average session duration. A/B testing supports fair, effective, data-driven decisions and helps incrementally improve existing user interfaces. It can be used when there are two strong candidate designs for a specific interface element and when proper experiment setup can be maintained to avoid common mistakes.
"In UI/UX design, A/B testing, also known as split testing, refers to a quantitative UX research method that compares two design versions based on real user behavior to identify the top-performing design version. It's named with "A/B" since two versions, A and B, are evaluated: Version A: Control, the original design version that usually already exists Version B: Variant, the new design variant that competes with version A"
"A/B testing selects the winning version using metrics like click-through rate (CTR), conversion rate, bounce rate, and average session duration: Benefits of A/B testing A/B testing is a powerful, user-centric decision-making technique with proven benefits to incrementally extend existing user interfaces: Fair, effective, data-driven decision making: No need to spend time arguing which design is the best in interna"
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