Definition

A/B testing (split testing)

A/B testing, sometimes called split testing, is an assessment tool for identifying which version of something helps an individual or organization meet a business goal more effectively. A/B testing is commonly used in web development to ensure that changes to a webpage or page component are driven by data and not personal opinion.

A/B tests are blind studies and the participants are unaware that a test is being conducted. In a typical A/B test on a Web page, version A is the control and version B is the variant. During the test period, half the visitors to the Web page are served version A of the Web page, which has no changes, and half are served version B, which includes a change that is designed improve a specific metric such as clickthrough rate, conversion, engagement or time spent on page. End user behavior, which is gathered throughout the test period, is analyzed to determine whether the control or the variant performed better for the desired goal.

Online streaming service Netflix is a well-known for its extensive use of A/B testing. The company uses A/B split testing in everything from fine tuning its streaming and content delivery network algorithms to selecting what images should be associated with a specific title. According to Netflix, selecting the right image can result in 20% to 30% more viewing for a specific title. 

This was last updated in August 2016

Continue Reading About A/B testing (split testing)

Dig Deeper on Data science and analytics

Data Management
SearchAWS
Content Management
SearchOracle
SearchSAP
Close