What is A-B Testing?
A-B testing is an experiment that compares two versions of a webpage/app against one another. It can also be referred to as split-run testing or bucket testing. A-B testing is done to determine which of the two versions are performing better. Statistical analysis is performed after the A-B testing is done to mathematically determine which of the variations performs better for the conversion goal that is set.
Every site has a goal, and that goal is to move visitors through the sales funnel to do something. This can be a subscription, a download, a purchase, or even a like/share of a page. The rate at which you’re able to do this is what we refer to as the “conversion rate”. By measuring the performances of A versus B, you can measure the rate at which it converts your visitors to the goal you’re trying to reach.
Comparing variations lets you choose focuses aspects of your site/app that you want to alter. This allows you to see what works better for your customers. It lets you collect data about the impact of your change. You’ll be able to analyze whether a change will be beneficial or detrimental to your site/app. This method of introducing changes to a user experience also allows the experience to be optimized for a desired outcome.
Read this article for more on how to use A-B testing in the Fera App Tools.