There's seemingly no end to the things you can test in your marketing, and if you've laid a solid framework for your inbound marketing programs, now's a great time to start optimizing and making what works pretty well work amazingly well . And the best way to get started is to conduct some A/B tests !
Or...multivariate tests? What's the difference between A/B tests and multivariate tests? Will it affect my results if I choose the wrong one?
Yes, there is a difference, and yes, it will affect the integrity (and thus usefulness) of your results if you choose the wrong test. But no fear! We're going to break down the difference between A/B tests and multivariate tests in this post, and tell you exactly when to use each so your tests can run smoothly and make your inbound marketing rock even harder than it already does.
What Is an A/B Test?
When you perform an A/B test , you create two different versions of a web page, and split the traffic evenly between each page. You can also perform an A/B/C test that tests three different web page versions, an A/B/C/D test that tests four different web page versions, and, well, you get the picture. In an A/B test, you can change literally any variable you want from page to page, and it is in fact a testing best practice to create two (or three, four, whatever) radically different pages for your test.
What is multivariate testing?
A multivariate test shows audiences slightly different variations of a web page or other content where only slight subtle changes are made to each option. This can help marketers determine which fine details are most engaging to users.
When you perform a multivariate test, you are not testing a different version of a web page like you are with an A/B test. You are performing a far more subtle test of the elements inside one web page . The point of the multivariate test is to give you an idea of which elements on a web page play the biggest role in letting you achieve the objective of that page. The multivariate tests is more complicated and best suited for more advanced marketing testers , as it tests multiple variables and how they interact with one another, giving far more possible combinations for the site visitor to experience.
Multivariate Testing Example
While an A/B test might show audiences two different website formats or designs, mulivariate might show subtle differences such as different wording or fonts on a call-to-action to see which button is clicked more.
This is a tricky concept, and a visual usually helps clarify complicated ideas. Luckily, Search Engine Land shared an image on its site from Yam Designs that visually illustrates what a multivariate tests looks like.
Multivariate vs. A/B Testing
While an A/B test allows marketers to learn which major formatting of a site or piece of content is most engaging, multivariate allows them to zone in on which tiny details are most engaging by showing audiences variations that only have subtle differences.
A/B testing is a great testing method if you need meaningful results fast. Because the changes from page to page are so stark, it will be easier to tell which page is most effective. It is also the right method to choose if you don't have a ton of traffic to your site. Because of the multiple variables being tested in a multivariate test, you'll need a highly trafficked site to get meaningful results with MVT.
If you do have enough site traffic to pull off a successful multivariate test (though you can still use A/B testing if you're testing brand new designs and layouts!) a great time to use the testing method is when you want to make subtle changes to a page and understand how certain elements interact with one another to incrementally improve on an existing design. You can also use multivariate testing to perform a test that will give you results you can extrapolate out and apply to a larger site redesign.
Just remember that, in order for the multivariate and A/B tests to give meaningful results, it's not enough to have site traffic overall; the pages being tested also need to receive substantial traffic! Make sure you select pages that people can find and visit regularly so your test actually yields some data to analyze.
Have you performed A/B tests or multivariate tests on your website? Did the results of the tests cause you to make any changes to your site?