How to Run Multivariate Tests on Shopify [2025]

With increasing customer acquisition costs, your conversion game has to be solid.

As an eCommerce business owner, you want to put your best foot forward, with the best version of your website or landing page. It’ll help you beat the competition and boost your conversion rate.

Multivariate tests can help you identify the best way to present your store or landing pages.

In this blog post, we’ll take you through the nuts and bolts of multivariate testing along with a step–by–step guide on how to run a multivariate test on Shopify.

Let’s begin with the basics first!

What is a Multivariate Test?

Multivariate testing (MVT) is a technique in which multiple variations of webpage elements are tested to identify which combination of elements performs the best to achieve the desired business goal.

As an eCommerce brand, your business goal is most likely to increase the conversion rate so that you can increase revenue and profits. However, there could be other business goals, too. 

Here are some goals that a brand may want to accomplish through multivariate testing:

• Increase the newsletter signups

• Entice website visitors to submit a quiz

• Get customers to download a lead magnet

• Encourage visitors to book a demo or discovery call (SaaS or service businesses)

While all of these are goals related to your business metrics, you could also use multivariate testing as a tool to better connect with your audience and enhance their experience.

Example of Multivariate Testing

Now, let’s understand how multivariate testing works with the help of a hypothetical example:

As you can see in this example, there are four different versions of a landing page. Basically, the example covers two key elements — the hero image and the CTA button — and both have two versions of their own.

All four landing pages are sent equal traffic, i.e., 25% of the total traffic, and the conversion rates are measured for each landing page version. Since landing page #3 has the highest conversion rate (10%), it will be considered a winner in this testing campaign.

A/B Test vs Multivariate Test

To better understand a multivariate test, you should be familiar with A/B testing — because a multivariate test is basically a complex version of A/B testing.

What is A/B testing?

A/B testing — also known as split testing — is a technique in which two versions of the same webpage are created and displayed to different visitors to decide which one performs better for a defined business goal.

So, both A/B and multivariate testing have the same core concept, i.e., to compare variables, measure their performance, and identify the best one. For most eCommerce brands, the key goal is also the same — conversion rate optimization (CRO).

However, the key difference lies in the technique of how they’re implemented.

Key Aspects	A/B Testing	Multivariate Testing
Variables or Elements	Different versions of a single variable or element are tested.	Different versions of multiple variables or elements are tested.
Example	Two landing page versions: “A” with a green color CTA ad “B” with a pink color CTA	Two landing page versions: “A” with a green color CTA and a free shipping banner. “B” with a pink color CTA and a 10% discount offer.
Number of pages	A typical A/B test has only two versions of a webpage or landing page.	It could have two or even more versions/pages, depending on the requirements.
Complexity	A/B testing is the basic and simplest form of testing.	Since this covers more variables/elements, it could get complex with the increasing number of elements.
Sample size	While A/B testing requires a sample size to achieve statistical significance of 90% or above, relatively, it needs a smaller sample size.	With more variables, multivariate testing requires a large sample size.
Timeframe	Relatively shorter.	May need a longer timeframe in certain cases.

How to Run a Multivariate Test on Shopify?

Here’s the step-by-step guide to conducting a multivariate test on your Shopify store:

Step 1: Identify the problem(s)

First things first, you need to know what needs to be improved on your Shopify website.

Implement a data-driven approach and not guesswork. Meaning, your process of identifying the problem(s) should be backed by data and observations.

You may consider quantitative as well as qualitative data in the process.

For example, use Shopify analytics tools to gather quantitative data on your store’s performance metrics such as conversion rate, bounce rate, cart abandonment rate, average order value, items bought together, and so on.

Let’s expand on one of the examples. Let’s say your store conversion rate is below the desired goal, and the cart abandonment rate is way too high — it’s likely a problem with the product offer or somewhere in the flow from the product page to the cart page.

Also, qualitative data can make your problem statement even more robust. For example, you can check the heatmap analysis to see where website visitors are clicking the most and if there’s a specific element you expect them to hit but aren’t. 

Step 2: Create a hypothesis for the test

So, you found the problem — now, it’s time to propose a solution.

2.1 Define the key elements pertaining to the problem

Before you could propose a solution to form a hypothesis, you should evaluate the most crucial elements related to the defined problem statement.

For an issue with a low conversion rate and high cart abandonment, these could be the most important elements:

• CTA Button

• Lack of social proof

• Trust badges

• Shipping charges

Similarly, various problems may have different key elements that influence customer behavior. Here are some more critical website elements that may impact the store’s conversion rate: Website copy, product images, discount offers, payment options, and so on.

2.2 Create the hypothesis for the multivariate test

So, you’ve defined the problem and have an idea of what elements can help resolve the problem. Now, combine those two aspects and create your hypothesis.

So, here’s an example hypothesis for a multivariate test:

“Based on the heatmap analysis, I expect that placing the product rating score next to the product title and the free shipping badge next to the CTA button will help reduce the cart abandonment rate and increase the conversion rate.”

The purpose of defining a hypothesis is to ensure that your testing campaign has a defined strategy and goals.

Step 3: Finalize and install a multivariate testing app

In order to run this test successfully on your Shopify store, you need to have the best Shopify app to perform a multivariate test.

GemX is designed for Shopify merchants to help increase conversion by enabling them to experiment with A/B testing and multivariate testing. Using GemX, you can test your store pages and even the pages built with a page builder app.

To begin installation, go to the GemX app in the Shopify App Store. Click the Install button.

Review the access permissions and click the Install button again.

Once the app is installed, you’ll land on the pricing page. Currently, there’s a 50% off for new users, so you can get the content testing plan at just $24 per month. On top of that, you can enjoy the 14-day free trial as well.

Once you’ve selected the plan and confirmed the payment approval, you’ll land on the app dashboard. Right at the top, you’ll see a pop-up to enable the GemX app in your Shopify theme so that you can enjoy a seamless experience.

To proceed, click “Turn on in Shopify Editor”.

You’ll be redirected to the Shopify theme editor, and the GemX Theme Helper will be enabled automatically. You just need to hit the Save button to confirm the change.

Now, you’re all set to start experimenting with A/B or multivariate tests on your Shopify store.

Step 4: Create the variations and run the test

To begin your first campaign, first, keep your webpage or landing page versions ready. Based on the test hypothesis, prepare the variants with different elements.

For example, if you’re testing a landing page elements like the heading copy and CTA, prepare different versions of the landing page and name them in a way that you can identify when running the test.

Pro tip: A landing page builder app like GemPages can help you easily create different versions of webpages or landing pages. Using its intuitive drag-and-drop editor, you can customize your page design with rapid speed. GemX and GemPages work seamlessly together.

Once ready, get back to the GemX app dashboard and click on the “Create new campaign” button.

GemX has quite an easy-to-use interface. You’ll see two big sections for “Control” and “Variant”. Under the first section (A - Control), click the “Select a template” button and update the main webpage.

Next, click on the “Select a template” button under “B - Variant” and upload the other version to test. Then, have the option to adjust the traffic distribution under “Set traffic for each variant”.

You can keep it as is (50%), as we want to distribute equal traffic to both versions.

Next, click on the “Advanced setting” bar to expand it. Here, you can configure other test settings such as the primary goal, device type, visitor type, and traffic source.

Once all settings are configured, go back to the top of the page and click the “Start campaign” button to make your multivariate test live. If you want, you can click the Preview button before publishing the campaign.

That’s it! Your multivariate test campaign is now live. Now, let the traffic go through the test variants for the defined timeframe or sample size.

Before you complete your multivariate test campaign, make sure the results are driven by a sufficient sample size. In order to make any robust decision, you need to have enough data to achieve statistical significance.

You should aim for a p-value of 5%, meaning, about a 95% confidence level to come to a conclusion.

Keep in mind — with more variables or elements, it may take longer to reach statistical significance. Once you have sufficient data, you can end the campaign and analyze which version performed the best.

Step 5: Measure and analyze the results

Once the test campaign is completed, it’s time to analyze the results and draw valuable insights for your business. Don’t just aim at quickly implementing the changes to increase the conversion rate. Instead, try to assess the results and understand your customers’ behavior.

Whenever you’re running any such A/B tests or multivariate tests, you’re generating useful insights for your business. You can even leverage these insights when designing your future landing pages.

Bonus Step: Repeat the test or implement the changes

Now, once the test is completed and you’ve identified which version of your web or landing page is delivering the best results, you have two options:

1. Continue testing further to see if you can find an even better version.

2.  End the entire campaign by implementing the changes as per the winning version.

If you decide to conduct a further test, you can consider the winning variant as the new “Control” version and create a new variant. This way, you can continue measuring and enhancing the same webpage.

Also, as we mentioned earlier, you can conduct multivariate tests on other store pages based on the learning and insights from the previous one.

Types of Multivariate Tests

Mainly, there are two types of multivariate tests:

1. Full factorial test:

As the name suggests, a full factorial test covers every possible combination of variables, and the traffic is distributed equally for all combinations. Since the traffic is distributed equally to all pages, you can get precise and reliable test results for each variation.

As the full factorial testing method delivers more reliable results, it’s a widely used method. The only thing you need to keep in mind is that you should have good enough traffic to distribute among all pages.

2. Fractional factorial test:

In the fractional factorial test (aka partial factorial test), the traffic is distributed to only a certain number of variations or pages. For the remaining pages/variations, the calculations are done based on the outcome of the tested variations.

 While this can be a faster way to get the test completed, it may not achieve the level of accuracy that you expect from a full factorial test. However, this could be a helpful method for brands with low traffic.

Why Perform Multivariate Testing?

We know the whole process of running multivariate tests can consume your time, effort, and resources. So, you may want to know if it’s worth performing multivariate tests.

Here are the key benefits of multivariate testing:

• Increase conversion rate: Multivariate testing can help you enhance the key webpages or landing pages and increase their conversion rates. For example, if the Cart page is not delivering the desired results, you can improve the page through a multivariate test and increase your conversion rate.

• Test multiple variables: Multivariate testing lets you experiment with multiple variables together. This way, you can find out which elements work the best together, without conducting multiple A/B tests.

• Robust decision making: Multivariate testing is a form of A/B testing, and as we know, it’s driven by data analysis instead of assumptions. This helps you make better business decisions and achieve your goals.

Challenges in Performing Multivariate Testing

While there are advantages of running a multivariate test, there are also some drawbacks or cons that you should consider before running a multivariate test.

• Requires a large sample size: You must have a big sample size in order to make a robust decision through multivariate testing. So, if you don’t have enough traffic, it might be challenging to accurately conclude the results.

• Longer duration: Since it required a large sample size to achieve statistical significance, it also requires more time. Thus, it may turn out to be a time-consuming activity.

• Complexity: As compared to A/B testing, multivariate tests are relatively more complex as you’re testing out multiple elements together. You must ensure that you have a reliable tool to implement the test accurately.

Pro tip: You can take the help of a Shopify CRO expert to perform multivariate tests effectively. CRO experts can help you design and run the campaign with their experience and expertise in the eCommerce domain. Of course, you would have to spare some budget to outsource the task; however, you can save your time and focus on other business decisions.

Final Thoughts on Multivariate Tests

Multivariate testing is one of the powerful tools that you must keep handy in your eCommerce toolkit. It can help your grow and scale your business faster and effectively.

However, it’s important to identify the areas and elements that you should experiment with. Once again, you must implement a data-driven approach to identify those areas.

Last but not least, make sure to have a reliable Shopify app to conduct your A/B and multivariate tests. Start a free trial of GemX and explore its capabilities.

To learn more about other eCommerce marketing strategies, trends, and best practices — check out more resources on the GemPages Blog. Also, join the GemPages Facebook community to network and learn from like-minded entrepreneurs and experts.

FAQs About Multivariate Tests