Getting as much information as you can is usually a good plan no matter what you are aiming to do. Sometimes, it's about experimenting with how end users prefer to receive or look for information. Other times, it's about uncovering ways to offer a deeper layer of information. In "The ABCs of A/B Testing," Erik J. Martin offers this explanation: "A/B testing is the term used for randomly experimenting with a control variable (A) and an experimental variable (B) for the purpose of statistically testing a hypothesis." According to one digital analytics expert, epublishers and content providers need to test every component of their site to meet "an objective that is easy to understand yet difficult to execute."
Reproduced with permission of the copyright owner. Further reproduction or distribution is prohibited without permission.