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How to Use A/B Multivariate Testing on Your Website

A/B testing is a method of data analysis consisting of an experiment. In such test two variants of the same website are compared to measure which one performs better. 

As you can imagine, there are countless situations where this applies. You may want to improve the checkout process on your store by removing steps or adding information. On the other hand, perhaps you’d like to optimize your email sign-up for higher conversion rates. Maybe you’ve identified some key processes within your organization that aren’t delivering results as expected. Maybe you would like to test changes against what is currently being done

The first step is identifying your goal. Will it be: 

  • increased revenue?
  • lower cost per acquisition (CPA)?
  • improved customer satisfaction? 

Once you know your desired outcome, it becomes much easier to come up with a hypothesis. For example, if you want to increase revenue, your hypothesis could be: “Adding a 10% discount to all items in the shopping cart will increase the number of orders placed on the website.” If your goal is lower CPA, a suitable hypothesis could be: “Changing the text on the submit button from ‘Subscribe’ to ‘Submit’ will result in more people clicking through to the next page and subscribing.”

Once you have your hypothesis, it’s time for the fun part – testing it! You’ll need to create two variants of your website (or whatever it is you’re testing) and then measure how each one performs. 

Why Should You Conduct Multivariate Testing?

There are several reasons to conduct A/B multivariate testing on your website. First of all, it allows you to test several different elements at one time. These could include your email subject line or your landing page. The same thing can be said for these two elements but with different tones and styles. This will help you determine what works best for your visitors. A/B multivariate testing can answer a variety of questions.

For instance, a question that is frequently asked is how to get more people to share your content on social media. A/B multivariate testing gives you this answer by allowing you to test different headlines or phrases. You can try out “share our post” and see which seems to work better than the other. The same thing applies to buttons below the headline text such as “share this” versus “share”. This way, you will know what works best for your audience and what doesn’t. Although it may take some time and effort, knowing these answers can help increase traffic and conversions in the long run.

On top of answering questions, A/B multivariate testing allows you to see elements that are working well together and which ones aren’t. You may have a catchy headline but it is paired with a rather dull image, making it seem less effective. Or, you may have a great image but the text doesn’t work well with the theme of that particular photo. In this case, A/B multivariate testing can be done as follows: one group would see your current landing page design while another will see your newly redesigned version. Once you’ve calculated the data from each test, you’ll know which element works better together and what needs to change for improvement based on results.

Multivariate A/B Testing: Summary

Multivariate testing allows you to test different combinations of a single element. The primary benefit of A/B multivariate testing is that it allows you to test more variations of a particular element at one time. It helps you determine which design works best and is the most effective one. If you increase open rates or clickthrough rates, then you have a successful test. If you see an increase in unsubscribes, you know something is wrong with your campaign. It is also easy to use. A/B multivariate testing can be repeatable, so if one version of your page is performing better than another, simply halt the test. If the results aren’t what you were hoping for, you can always change the version again. And if it’s still not working for you, just stop the test and try a new one.

The results of a multivariate test are much clearer because there are fewer test pages. Secondly, multivariate tests can take months to complete, and the subtle variations can make the results difficult to decipher. That’s why many marketers prefer A/B testing, which shows results instantly. But if you’re unsure of how to use it, we have some tips for you:

  1. Multivariate testing is best used when there are several changes that you want to make to a page. For example, if you want to test a new headline, different images, and a new call to action button, then multivariate testing is the best way to go. 
  2. These tests work by splitting traffic between two or more pages. In most cases, the pages will be very different from each other. The test will run until a statistically significant difference is found between the two pages. This means that the variation in results is due to the change on the page, and not to chance.