Multivariate testing is a good technique for the purpose of testing a hypothesis. The method uses variables which go through a number of modifications. The purpose of the multivariate testing is to figure out which one of all the possible combinations and variations will yield the highest result hence being the best possible combination.
Both websites as mobile applications consist of different combinations of various elements which could be changed. The finished result is the best possible combination so far for the specific site or mobile app. The primary components of such are the headline, an image, and the text. Those are the elements that the multivariate test will change.
As with any other thing in life, multivariate testing also has its pros and cons. The main benefit of this technique is that it is useful for creating variations of several elements on the same page in tandem. Most commonly the goal of such pages is yielding a higher conversion rate meaning clicks, sign-ups, shares, and completion of forms. Unlike A/B testing, if the multivariate testing is done right, it has the potential to turn a higher number of combinations in less time.
Multivariate testing comes with one big challenge, however. It has to do with visitor traffic, and it is split into several parts. A/B testing sets the visitor traffic half by half while multivariate testing divides it into quarters, or sixths, or eights, and possibly even shorter segments. One way to combat the issues is to project the sample size of the traffic needed for each variation before running the multivariate testing. That will ensure more significant and better results overall. In case the traffic to the particular page is on the low side, an A/B test would be more suitable for the particular page.
One other challenge of the multivariate testing effect on the method is when any of the variable tested do not have an effect on the rate of conversion that could be measured. That could be an image for example. The headline does to have a measurable impact, but if the photo does not, then the testing would prove more useful if A/B tests are used instead.
One of the leaders in multivariate testing technology is Sentient AI. The company has been bringing AI to the table for e-commerce, commerce, as well as digital marketing and it is dedicated to creating revolutionary products for business to use and achieve their goals.