Segmented A/B tests: Avoiding average experiences

One of the biggest mistakes companies make when they begin A/B testing efforts in earnest is sticking to a single, simple audience. The problem being, if you want relevant, insightful results, you need a segmentation and personalization strategy in place. 

Targeting the “average” person, usually in the form of “all visitors,” is an easy trap to fall into. The idea is that by casting a wide net, you can catch everyone. In reality, there is no such thing as an “average” visitor. Sure, your website has a bell curve of visitors but that bell curve is actually made up of subgroups of visitors, each with their own bell curves in different places.

In terms of your website visitors, some common examples of subgroups are:

• New vs. returning visitors
• Men vs. women
• Mobile visitors vs. desktop
• Loyal customers vs. one-time shoppers 

In this post, learn why segmentation is essential in good test design and how to start designing your next set of A/B tests.