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What Is Multivariate Testing and How It Compares To A/B Testing

With multivariate testing, you can see what resonates with your audience. Learn more about multivariate testing and how it compares to A/B testing.

Finding what marketing strategies work best for your business is crucial, but what should you do once you’ve identified those strategies and are ready to improve? There are several ways to improve upon your existing marketing campaigns in real-time without waiting months for results.

Online testing can help you enhance engagement, reduce bounce rates, and increase conversions. But unfortunately, too few businesses utilize testing in their marketing campaigns to determine which elements of a campaign perform better than others.

You can use two types of testing on your website, landing pages, emails, and digital advertisements to drive meaningful results and improve conversion rate optimization: A/B tests and multivariate tests.

While they may sound similar, there are a few key differences. Understanding A/B multivariate testing options will help you improve your marketing campaigns to boost conversions and sales without increasing your budget.

What is multivariate testing (MVT)?

A multivariate testing (MVT) method allows you to experiment with multiple elements simultaneously to give you more information about how certain variables impact your marketing campaigns.

Traffic to a page testing multiple variables is split between the different versions, allowing you to measure which combination of page elements performs best.

Marketers may use multivariate testing when they have enough website or landing page traffic to effectively measure the results.


The most significant benefit of multivariate testing is that it can help you identify which elements can be modified to improve conversion rates.

In addition, multivariate testing may eliminate the need for long A/B testing processes by allowing you to run multiple tests simultaneously.

Once you know which elements perform best, you can redesign your page to reflect the results.


While the benefit of multivariate testing is being able to test multiple variables simultaneously, the major downside is that these types of tests require significant traffic volume to get meaningful results.

Because these tests compare multiple variables and different page variations, too many possible combinations can result in too little traffic to determine whether the results are accurate. For example, suppose you have 4 variations and only 100 visits. Each page will only receive 25 visits, which isn’t enough to determine which elements are the most effective at converting your target audience.

Multivariate test examples

A multivariate test will show multiple variations of the same page. Anything on your page can be tested to help you determine which variables help you reach your marketing goals.

Testing individual elements

Consider the CTA on a landing page. Maybe you want visitors to fill out a form or click a link to purchase a product. Whatever the case, you can change different elements of your CTA, including the text, font, button size, and button color.

In this case, multivariate testing will be used to determine how changing a single element on a page will affect conversions.

Don’t forget that multivariate testing can be done for a variety of marketing campaigns, including email. For example, when writing email subject lines, you may have a few options you want to test to find one that results in higher open rates.

Complete redesign

Depending on your goals, you might consider an entire page redesign. In this case, you could create a multivariate campaign to test several elements on a page to determine which versions of each improve conversion rates.

Testing offers

Multivariate testing can be used to test offers on your landing page or website to determine which results in higher conversion rates. For example, if you have a campaign for a new energy drink, you may offer a free sample in exchange for emails and other personal information, or you can offer a discount for new customers.

Testing offers allows you to determine which deals are more likely to result in higher conversions.

Best practices for multivariate tests

Multivariate tests are more complex than A/B tests, although they share similar goals. That being said, because it’s more complex, you should dedicate more time to your campaign.

Set SMART goals

In most cases, you’ll be measuring conversion rates on a web or landing page to determine which elements increase conversions. For email or advertisements, your SMART goals might be clicks, click-through rate (CTR), conversions, or email opens.

You should set SMART goals to ensure you have something to measure before your campaign begins.

Identify variables

What elements do you want to test? Identify the different variables up for debate that you think can be modified to improve conversion rates and help you reach your goals.

At this point, you should have a hypothesis. For example, if you’re testing the placement of your call to action button and a new headline, you may make the hypothesis that a new headline will improve conversion rates.

Create test variations

Once you’ve formed your hypothesis and set goals, you can create variations. You’ll need to use a multivariate testing tool like Google Optimize to create as many variations as you need.

Drive traffic

Once your variations are published, you’ll need to continue driving traffic to your page. If your website receives significant traffic from search engine optimization (SEO), you may not have to invest in additional advertising.

However, if you want to ensure a larger sample size, you can invest in social media or Google ads to increase traffic to the page and ensure your results will be more accurate.

Analyze results

Once your campaign has finished, it’s time to analyze your test results. Compare the results with your original SMART goals to determine which elements performed best.

Take action

After analyzing your results, you’re armed with the data to help you redesign or modify your web page, email, or advertisement. For example, if you tested different email subjects, you now know which performs best and can use it in future campaigns to increase open rates, clicks, and conversions.

Multivariate testing vs. A/B testing

Multivariate testing is similar to A/B testing, but there are a few key differences, including the following:

  • Number of variables: The most significant key difference between the two experimental methods is that A/B testing only has two variations, while an MVT test will have at least four. You can still test the same types of variables, but you’ll need to wait for one test to be completed before making any further changes.
  • Ease of use: A/B testing is easier than running multivariate tests since there are only two variables possible combinations. With fewer different variations, you can better understand your data and its statistical significance to your campaign, allowing you to make more informed decisions with a smaller sample size.
  • Required sample size: Since there’s less traffic required, A/B testing is best for small businesses that don’t receive significant traffic to a single page.
  • Testing time: A/B testing gives you results faster than multivariate testing, especially if you don’t have significant website traffic. Instead of waiting for enough traffic to your site, you can use A/B testing on almost any page to make drastic changes that have a significant impact. How long you should run an A/B test depends on the amount of website traffic or the number of subscribers if you’re A/B testing an email campaign. However, the longer you let your tests run, the more accurate the results will be because you’ll have a larger sample size.
  • Types of results: A/B testing can tell you which version or variable is best. Meanwhile, a multivariate test can determine which combination of elements works best, allowing you to create more effective campaigns with a single test.
  • Expert level: A/B testing is easy for marketers of all levels. However, multivariate testing is more complex and better for individuals with experience running tests with multiple variables. In addition, too many combinations associated with MVT results can lead to confusion or inaccurate results due to a low sample size.

In most cases, A/B testing is ideal for campaigns where you want to make more drastic changes. Meanwhile, multivariate testing is best for websites with substantial website traffic that want to make small modifications to determine if they can increase conversion rates.

A/B testing is typically used to make informed decisions about redesigns, while multivariate testing is best for changing a few small elements that may not significantly impact results.

Optimize your campaigns

Multivariate testing can benefit marketing campaigns of all types to improve conversions and help you reach your goals. Compared to A/B testing, the multivariate testing method is more complicated to set up and requires higher traffic volumes. However, you can test multiple elements simultaneously if you have enough traffic on a single web page. Creating variations through either experimentation method can help increase conversions and improve your marketing campaigns.

Ready to start testing your email campaigns with multivariate or A/B testing? With Mailchimp, you can try both. Mailchimp’s multivariate testing allows you to determine which variables of your email to test to improve opens, clicks, and conversions. Optimize your campaigns today by A/B testing with Mailchimp or learn more about multivariate campaigns.

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