Multivariate Testing: A glance at its Pros and Cons Overview of Multivariate Testing Multivariate testing is a technique for testing different site elements and their
combinations on a website. This method allows us to test multiple combinations of site elements simultaneously on your website. The goal is to find out which combination of site elements variations best suits your business interests out of all possible combinations. A website is a combination of various customizable elements that are grouped together on a platform. With this multivariate testing approach, you can change the multiple components of a website at a time. Like, you can change the website slider and heading at the same time or can make changes in the CTA button, links or web form simultaneously for determining the usability of various site components. Here in this web testing approach, we can create all the site components variations we want to test on our site. After this, we prepare a sample space of all the possible combination of these site changes and can test each combination simultaneously at a given time interval. In this way, you can effortlessly choose the right combination of site elements that can provide you maximum conversion rates and sales. Pros which make Multivariate testing “ an accomplished testing tool" Multivariate testing is very useful in testing multiple elements of a page to accomplish a particular goal of conversion at one time. For example, filling of sign up form, product selling, newsletter subscription and other such conversion metrics. This testing approach is capable of providing test results in a shorter time as compared to A/B testing or Split testing technique as multiple variations are tested simultaneously. It eliminates the hassle of multiple sequential tests for different elements in case of A/B testing where only a single element is allowed to be tested in a given time interval. It saves time as it gives desired results in a shorter time span. Provides highly accurate test results as it provides facility to test all the possible combinations. For example, let us study the image given below for understanding more about