THE DIFFERENCE BETWEEN A MULTIVARIATE TEST AND AN A/B TEST
What is the difference between A/B testing and multivariate testing?
A/B TESTING
A/B testing, which also referred to as split testing, is a method of website optimization in which the conversion rates of two versions of a page — version A and version B — are compared to one another using live traffic.
Site visitors are bucketed into one version or the other. By tracking the way visitors interact with the page they are shown- the videos they watch, the buttons they click, or whether or not they sign up for a newsletter, you can determine which version of the page is most effective.
MULTIVARIATE TESTING
Multivariate testing uses the same core mechanism as A/B testing, but compares a higher number of variables, and reveals more information about how these variables interact with one another. As in an A/B test, traffic to a page is split between different versions of the design. The purpose of a multivariate test, then, is to measure the effectiveness each design combination has on the ultimate goal.
The data from each variation is compared to find not only the most successful design, but also to reveal which elements have the greatest positive or negative impact on a visitor's interaction. For example, varying a page footer may be shown to have very little effect, while varying the length of the sign-up form has a huge impact. This is especially useful when designing landing page campaigns- a certain element's design can be applied to future campaigns.
