What is multivariate testing?
As the name suggests, multivariate testing is an approach to hypothesis testing that involves changing multiple variables at a time to figure out the best possible combination of all variables available.
If you want a more in-depth understanding of this topic, check out the FAQ section below:
Question #1: What are the benefits of multivariate testing?
The biggest benefit of multivariate testing is that it allows you to determine which combination of changes will increase the conversion rate of your website or mobile app, which, in turn, would result in things such as:
- More sales
- More leads collected
- More sign-ups to your events
It is perfect for you whether you are building a website or app from scratch or revamping an existing one.
Question #2: What are the steps in multivariate testing?
The steps in multivariate testing are as follows:
- Determine a sample size. It is essential that you have a big enough sample size to represent your entire audience. If not, you may end up with inaccurate results or find it difficult to attribute improvements in performance to specific variables. You need a larger sample size than you would with A/B tests. This is because you will be comparing a larger number of variables, such as colors, navigation, and headlines. In contrast, A/B testing only focuses on smaller changes to a website.
- Collect data. Once you have determined your target sample size, it is time to start testing and collecting relevant data.
- Analyze the data. The analysis can assume the interaction between two or more variables. This step is critical to the success of your test.
- Select the right combination of variables. Based on the outcomes of your analysis, you will need to pick the combination of variables that results in the highest conversion rate.
Question #3: What are the downsides to multivariate testing?
The main downside to multivariate testing is that it can be extremely time-consuming. Even a website with moderate traffic or an app with a moderate user base may struggle to test more than 25 combinations of variables because of this.
Another limitation is that it cannot be performed on very small websites or apps with a very small user base. As we have seen in the previous section, you need a big sample size to get accurate results.
In addition, because of its complexity, it can be difficult to understand. This means that if you are not a web analytics expert and you are not planning to hire one, you should probably explore simpler alternatives.
For more cons on multivariate testing, check this helpful article from the DBS website.
Question #4: What is the difference between multivariate testing and A/B testing?
As we have seen earlier, the biggest difference between multivariate testing and A/B testing is the number of variables involved. While both methods are designed to help you improve your conversion rates, it reveals more details about interactions between the variables involved in the test than A/B testing.
Question #5: What can I test with multivariate testing?
You can test virtually any aspect of your website or app with multivariate testing, including:
- How well the text and visual elements on your web page or app work together
- How well your call to action, button design, and button placement work together
- How the number and arrangement of the fields in your forms affect your sign up rate
- How the length and tone of your copy affect your conversion rate
- How does the ratio of images and videos you use affect your bounce rate
The goal is to test one or just a handful of variables at a time and keep improving your website or app over time instead of testing everything at once. As we have seen earlier, multivariate testing can get overwhelming, not to mention extremely time-consuming, fast because it is designed to take into account way more variables—including the relationships between them—than regular A/B testing.