Like A/B Testing, Multivariate Testing depends on the same mechanism, but it compares higher number of variables, and provides more information about how these variables behave. In A/B Testing, you split the traffic of a page between various versions of the design. Multivariate Testing is utilized to measure the effectiveness of each design.
Let us say there is a webpage that has received enough traffic to run the test. Now the data from every variation is compared to check the most successful variation, but it additionally includes the elements, which have the maximum positive or negative effect on a visitor's interaction.
Multivariate Testing is an effective tool to enable you target as well as redesign the elements of your page and show the areas that will have the most impact. Multivariate method is helpful for creating landing page campaigns.
Data about the effect of a certain element's design can be applied to future campaigns, even if the context of the element has changed.
Limitations of Multivariate testing is the traffic needed to finish the test. As all the experiments are completely factorial, too many changing elements at once can quickly add up to a very huge number of possible combinations that must be tested. Even a site with fairly high traffic might have trouble completing a test with more than 25 combinations in a feasible amount of time.
A/B Testing also known as Split Testing is a strategy of website optimization, where you compare the conversion rates of two versions of a page namely, A and B. All visitors are divided into one version or the other. Once the visitors visit either of these versions (A or B), they click on various buttons or even sign-up for the newsletter. This permits you to determine which version of the page is more powerful.