There seems to be no end to what to test in your marketing – conversion rates, offer placements, and even which titles do better.
There is also no limit to the types of tests you can take, but two players take center stage: A / B and multivariate tests. However, is there a huge difference between them? And will my results be affected if I choose the wrong one?
Yes there is a difference and yes it will affect your results. But no fear; In this post, we’re going to break down the difference between A / B testing and multivariate testing, and tell you exactly when to use each, so your tests can go smoothly and your inbound marketing can go from pretty good to amazingly well.
Multivariate tests vs. A / B tests
While an A / B test allows marketers to learn which key formatting of a website or content is most appealing, Multivariate allows them to find out which specific page elements are most interesting by showing the audience several unique variations.
The key difference is that A / B testing focuses on two variables while multivariate are 2+ variables. Since the difference between the two tests can be seen visually, let’s go over an example.
Example of multivariate vs. A / B tests
In the figure above, the A / B test simply consists of two different versions of the same with tiny changes, while the multivariate test examines several different page elements (variables) in different positions on the page.
Given the differences, let’s learn more about each one and when to use each test in your marketing.
What is an A / B test?
When you run an A / B test, you create two different versions of a webpage and split the traffic evenly to see which does better. The picture below is an example of an A / B test.
A / B testing is often done with two different variables, but there are A / B / C tests that test three different website versions, an A / B / C / D test that tests four different website versions, and well, you get the picture. You can change any variable from side to side in an A / B test, and it is a test best practice to create two different sides for your test.
When to use A / B testing
Use A / B testing when you want to test two specific designs against each other and get meaningful results quickly. This is also the way to go if you don’t have a lot of traffic on your website as you are only testing two variables so meaningful data is not required.
Advantages and Limitations of A / B Testing
| Benefits of a / b testing | Limitations of a / b testing |
| Fewer variables so data is easier to follow and you can get a clear sense of what is working and what is not. | The focus is on two individual variables, so the test results are hyper-focused and not generalizable. |
| You will get results quickly |
What is multivariate testing?
A multivariate test shows the audience different variations of different elements on a page (CTA placement, text placement, images, etc.) to understand which aspects are most interesting to users.
When doing a multivariate test, you’re not just testing a different version of a web page like you are doing an A / B test. This process gives you an idea of which elements on a page play the most important role in achieving a page’s goal.
The multivariate test is more complicated and best for more advanced marketing testers, as it tests several variables and their interaction with one another, which offers the website visitor far more combination options.
When should multivariate tests be used?
Only use a multivariate test if you have a lot of website traffic. If you have a lot of website traffic, the following use case is when you have pages that contain several different elements and you want to know what would happen if you made significant changes to the features on the page, such as: B. their placement.
Advantages and limitations of multivariate tests
| Advantages of multivariate testing | Limits to multivariate testing |
| It helps you redesign site pages to get the most impact. | Requires significant website traffic because you need enough data to accurately test all of the variables and not all companies have this traffic. |
| The results are significant as multivariate testing requires significant website traffic. | Is a fairly advanced and laborious marketing process. |
| You can extrapolate results because you are testing multiple variables and you have significant data points. |
Example of multivariate tests
While an A / B test might show the audience two different website formats or designs, multivariate differences like different wording or fonts can show the audience 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. The picture below is an example of a multivariate test.
Remember, multivariate and A / B testing is not enough to get meaningful results overall – the pages you are testing must receive significant traffic too! So make sure you select pages that users can find and visit regularly so that your test provides some data for analysis.