Products are composed of multiple components and features, with several elements that can be swapped in favor of features that deliver better results for the user and company. Multivariate testing allows these variables to be compared in order to determine which delivers an optimal experience for all parties.
What is multivariate testing and how is it different from A/B testing?
- While A/B testing compares two versions of a product against each other, multivariate testing compares versions of specific elements.
A/B testing is generally used to compare two versions of a product, software, or web page to determine which delivers the best user experience with optimal results for the business. Multivariate testing evaluates every combination of each element on a web page or product to find the ideal mix to use within the finished product. Some variables that may be tested include the placement of page elements, font choice and color choices.
Multivariate testing is particularly useful when comparing the interaction of multiple elements on the same page towards reaching a single conversion goal, such as sign ups, form completions, shares or other goals. However, multivariate testing requires a great deal of visitor traffic to provide a significant sample, with segments divided multiple times over versus the 50 percent split found in A/B testing. Both forms of testing have optimal uses and may depend on the size of the audience and amount of variables presented to determine the best option.
How do you perform a multivariate test?
- Multivariate tests are performed concurrently by providing many variations of multiple elements of a product to several segments of users.
Multivariate testing helps uncover the optimal combination of elements featured within a product that will provide the best user and business outcomes. Multivariate testing is performed by creating several variations of the product and allowing certain segments of users to interact with the variable elements over a period of time, with the goal of receiving enough data to make a decision on which variations to keep. Multivariate tests must be performed with a large number of users to ensure data is accurate and able to be scaled for a full release.
Multivariate tests must be performed over concurrent periods of time to ensure constants are the same across each segment, and every variable must be tested to find the most optimal combination. The equation for performing a multivariate test is the number of variables of element A multiplied by the number of variables of element B equals the total number of variations.
What is multivariate testing in SEO?
Multivariate testing is performed in SEO by comparing multiple sections of a web page to determine which draws the most traffic.
Multivariate testing is particularly useful in SEO and helps determine the most effective elements to draw in the highest quality traffic to the site as possible. Multivariate testing is used to test the combined impact of multiple variations of several elements in reaching a specific goal, and in the case of SEO, that goal may be number of sessions, bounce rate, number of new users, number of unique sessions, or overall page ranking for specific keywords versus others. Due to the integral relationship between SEO and traffic, SEO managers and specialists must know when to utilize multivariate testing as opposed to A/B testing —multivariate tests being most effective when narrowing down potential options that will deliver the most impact.