Multivariate testing is a technique for testing a hypothesis in which multiple variables are modified. The goal of multivariate testing is to determine which combination of variations performs the best out of all of the possible combinations.
Where A/B testing will test different content for one visual element on a page, multivariate testing will test different content for many elements across one or more pages to identify the combination of changes that yields the highest conversion rate. Multivariate Testing, or multi-variable testing, applies a statistical model to test combinations of changes which results in an overall winning experience.
Multivariate tests are performed for a range of website changes, including all parts of an offer such as images, text, color, fonts, links, and buttons, content and layout for landing pages, or elements of website processes such as a complete checkout process. It is not uncommon for a multivariate test to exceed 50 or more combinations.
Multivariate testing starts with a hypothesis of content changes that could impact your conversion rates. With multivariate testing these content changes can be broken up into multiple individual elements to determine combinations that yield the highest conversion rates. Whether it is slight changes or significant changes to the user experience, either may significantly impact the overall results for your brand.
A conversion rate is the rate at which visitors perform a desired action for the test, such as the visitor clicking on an offer or adding products to their cart. Additional metrics are used to evaluate the test, such as revenue per order. Reports tell you which combination of changes yielded the best results based upon the conversion rate or uplift in the metrics defined.
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.
Once a site has received enough traffic to run the test, the data for each variable is compared to find not only the most successful design, but also to potentially reveal which elements have the greatest positive or negative impact on a visitor’s interaction.
You might ask now, is there any advantage if you are going to use multivariate testing? Yes, there is some sort of advantage using this kind of test. Multivariate testing is a powerful way to help you target redesign efforts to the elements of your page where they will have the most impact. This is especially useful when designing landing page campaigns, for example, as the data about the impact of a certain element’s design can be applied to future campaigns, even if the context of the element has changed.