Comparison of Multivariate test and A/B testWhat is the major difference, their methodology, common uses, advantages and limitations of these testing methods is used.
This is also called split testing in this testing two version of the page are created these are called A and B page and compared to one another using live traffic where visitors are directed to any one of the page. By measuring how they move through the page and read the articles, how they interact like watching videos, cocking buttons and whether signing up for newsletter or not. You will be able to determine which will be better.
A/B testing is a very basic testing and to evaluate a page design. It is also useful as an optimization option for pages where only one element is up for debate. One of the most common ways A/B testing is utilized is to test two very different design directions against one another. For example, the current version of a company's home page might have in-text calls to action, while the new version might eliminate most text, but include a new top bar advertising the latest product. After enough visitors have been funneled to both pages, the number of clicks on each page's version of the call to action can be compared.
A/B testing is simple in concept and design which is widely used. It will deliver reliable data faster.
A/B testing is a versatile tool, and when paired with smart experiment design and a commitment to regular cycles of testing and redesign, it can help you make huge improvements to your site. However, it is important to remember that the limitations of this kind of test are summed up in the name. A/B testing is best used to measure the impact of two to four variables on interactions with the page.
Multivariate testing also uses the same mechanism of the A/B testing but the number of variable is high. Once a site has received enough traffic to run the test, the data from each variation 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.
The most commonly cited example of multivariate testing is a page on which several elements. For example, a page that includes a sign-up form, some kind of catchy header text, and a footer. To run a multivariate test on this page, rather than creating a radically different design as in A/B testing, you might create two different lengths of sign-up form, three different headlines, and two footers. Next, you would funnel visitors to all possible combinations of these elements. This is also known as full factorial testing, and is one of the reasons why multivariate testing is often recommended only for sites that have a substantial amount of daily traffic — the more variations that need to be tested, the longer it takes to obtain meaningful data from the test.
Multivariate testing is a powerful way to find out the redesign element on your pages. This is especially useful in designing landing page campaigns
The single biggest limitation of multivariate testing is the amount of traffic needed to complete the test. Sometimes it may not be worth the extra time necessary to run a full multivariate test when several well-designed A/B tests will do the job well.
Think of them as two powerful optimization methods that complement one another. Pick one or the other, or use them both together to help you get the most out of your site.