ABOUT THIS EPISODE
...and now for another Human Factors Minute!
A/B testing is a randomized experimentation process in which two or more versions of a single variable, be that a web page or page feature, are shown to users to figure out which performs better. The “A” refers to the “control”—the original format and the “B” is a variation of that. It is also known as split testing because you split the sample of users where one half uses one version A, and the other half uses the “B” version. Say for example, you wanted to test out the effect of the location of a subscribe button on a website for new visitors. The current subscribe button is at the bottom of the webpage is “A” while the challenger B would be a button placed at the top of the webpage. You would then test these two versions of button webpage placement with a predetermined percentage of first-time site visitors. The metric would be the number of clicks the button gets.
A/B testing is useful because it eliminates all the guesswork out when designing a product and helps designers make data-informed decisions that can potentially increase user engagement, reduce bounce rates, minimize risk, and create engaging content.
Some fun facts: While A/B testing are most associated with websites and apps, the method is nearly 100 years old. Google first used A/B testing in the year 2000 and now they and other companies conducts over 10,000 A/B tests a year!
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