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Multivariate testing

What is Multivariate Testing?

Multivariate testing (MVT) is a method of statistical testing that involves multiple variables, each of which is modified as part of the experiment to test variations of the same idea. In such experiments, sets of variations are compared to one another to determine which set performs the best.

Multivariate testing can be largely beneficial when used as part of a website optimization program to support conversion goals like getting sign-ups, clicks, or form submissions from visitors to your site.

What Are the Types of Multivariate Testing?

The term multivariate testing encompasses several other types of testing which can be analyzed and selected by a research team depending on the objective of the test.

Full Factorial Testing

Full factorial testing is the first level of multivariate testing that involves dividing web traffic equally for each testing combination. This can be particularly useful to learn which website variation performs the best and which element has the greatest impact on achieving your optimal objective. Full factorial testing is the ideal choice for teams that want to run multiple tests due to its simplicity and straightforward methodology, but should be noted that it requires a relatively large amount of traffic and therefore may not be practical for the majority of websites and pages.

Partial or Fractional Factorial Testing

Alternatively, partial or fractional factorial testing reveals only a fraction of the results of a multivariate test. In website testing, for example, these types of tests wouldn’t analyze every element on a webpage but only a fraction of them. Partial or fractional factorial testing can be wrought with complicated mathematical equations but it typically requires less website traffic so it can be a good option for newer websites.

How is Multivariate Testing Used in Statistics?

Multivariate testing is used in statistical tests as a way to observe how radical changes in variations can affect the metrics measured during the experiment. In multivariate statistics, more than one outcome variable is analyzed to learn more about the relationship between each set of variables. This may include several rounds of both univariate and multivariate analyses.

To conduct a Multivariate test, you need a minimum of two variations to reach a conclusion that reveals which variation will be most effective in reaching the optimal outcome.

How is Multivariate Testing Performed in a Website Conversion Experiment?

Multivariate testing is particularly useful in website experimentation as multiple components are involved in the performance success of any given webpage. If a marketing team wants to determine whether a certain webpage is successful in collecting a specific number of sign-ups, the team might run a series of multivariate tests featuring alterations of different aspects of the webpage.

For example, a tester could alter multiple components at once, such as the copy, imagery, and other visual elements to determine not only which elements are most likely to result in optimal performance but also how they’re configured on the page. Multivariate testing enables the most granular level of testing webpage components and generally requires less effort to alter these components for each round of testing than A/B experiments.

Each variation can be tested against the others to gauge the best-performing combination of elements that is likely to lead to the ultimate goal, like form conversions, clicks, or other user actions.

What’s the Difference Between Multivariate Testing and A/B Testing?

Multivariate testing and A/B testing are both used to test the effectiveness of a webpage’s elements to achieve conversions, but multivariate testing is often the preferred method.

Rather than running multiple tests one after another to test a single hypothesis, as would occur with A/B testing, multivariate testing only requires a single test to reach the same conclusion. With multivariate testing, a greater number of variations can be tested in a shorter amount of time.

However, the simplicity of A/B testing lies in the dividing of web visitors into two distinct groups: Group A and Group B. With multivariate testing, the groups are divided into even smaller segments depending on the number of versions tested, which can make it more difficult to achieve meaningful results.

A/B testing typically requires subsequent tests to reach the desired result, whereas multivariate testing can be completed in a shorter amount of time with less effort.

Finally, A/B testing is typically more effective for analyzing drastically different changes on two or more given webpages, while multivariate testing is best for testing  varying combinations of elements.

What’s the Difference Between Multivariate Testing and Split URL Testing?

While multivariate testing allows researchers to test individual page elements and mix and match these elements to see which combination works best, split URL testing involves a test of the entire page. In such instances, multiple URLs that have the same end goal—such as to create conversions—are tested against each other to determine the best-performing URL.

In website testing and optimization, you may find multivariate testing to be the more time-friendly option as creating an entirely separate URL to test against a control page can be a big undertaking. Another disadvantage of split URL testing is the inability to test the individual elements on a page, which would require a separate multivariate test to be run.

How To Leverage Multivariate Testing To Enhance Website Optimization and CRO

Follow these steps for an efficient and successful multivariate test within your conversion rate optimization strategy:

Identify a Problem You Want to Solve

Use data to determine where gaps might exist on your website. Are you not getting enough conversions on a particular page? Are you seeing fewer call to action (CTA) clicks caused by a recent change to your site? In addition to data analysis, take a walk through your website to see where users might be getting stuck, and review any customer feedback that might inform where there’s room for improvement.

Develop a Hypothesis

Determine the web elements you want to test. Identify the goals of the experiment and start to think of testing strategies to best help you achieve these goals. Once you have a goal in mind, formulate a hypothesis to specify how you intend to address the determined problem and what you expect the results to be.

Build Variations

Once you know which elements you want to test, create variations that present different configurations and combinations of these web elements. This might include larger CTA buttons, a brighter color scheme, or more inviting copy in specific places. Avoid too many combinations—too many in a single test can make it difficult to achieve informative results, as the variations will take longer to reach statistical significance.

Identify and Predict the Sample Size for Each Variation

As you begin to set up your test, make sure you have enough web traffic to run a multivariate test. If the traffic to each combination is too small, the results may be more muddled and less conclusive in terms of which variation performed best.

Run a quality check of your testing setup before launching to ensure all the parameters are accurate. Then, start driving traffic to your page to get the test up and running.

Analyze the Findings

Allow time to analyze the results. Even if a particular combination achieved the best results, it may not mean it’s the best option for your webpage. You have the option to accept the results as fact or run additional tests for further insight.

Multivariate Testing FAQs

What is Multivariate testing (MVT)?

Multivariate testing is a method used in marketing and website optimization to simultaneously test multiple variations of different elements on a webpage to determine which combination yields the best results.

How Does Multivariate Testing Differ From A/B Testing?

A/B Testing compares two versions of a webpage with often only one differing element, while multivariate testing tests multiple elements at once in various combinations to identify the most effective combination of changes.

What Types of Elements Can be Tested in Multivariate Testing?

In multivariate testing, you can test various elements such as headlines, images, text, buttons, forms, and layout components to optimize the overall performance of a webpage.

How Long Should I Run a Multivariate Test to Get Accurate Results?

The duration of a Multivariate Test depends on the amount of traffic your website receives and the number of variations you're testing. It's essential to collect a sufficient sample size to ensure accurate results, which may take weeks or months.

How Do I Interpret the Results of a Multivariate Test?

Analyze the results to identify which combination of elements produced the highest conversion rate. Look for statistically significant winners and use these insights to make data-driven decisions for website optimization.

Can Multivariate Testing be Used for Email Marketing Campaigns?

Yes, multivariate testing can also be applied to email marketing campaigns. You can test different email subject lines, content, images, and CTA buttons to determine the most effective combinations for improved email performance.

What are Some Common Mistakes to Avoid in Multivariate Testing?

Common mistakes in multivariate testing include not having a clear hypothesis, testing too many variations at once, not collecting enough data, and misinterpreting results.

Are There Any Sample Size Requirements for Multivariate Testing?

Yes, sample size is essential in multivariate testing to ensure that results are statistically significant. The required sample size depends on factors like the number of variations, expected effect size, and desired level of confidence.

Can Multivariate Testing be Used for Ongoing Website Optimization?

Yes, multivariate testing can be used for continuous optimization. As your website evolves and new elements are introduced, you can conduct ongoing multivariate testing experiments to ensure that you are always improving conversions.

What are Some Common Challenges in Multivariate Testing?

Common challenges in multivariate testing include the complexity of managing multiple variations, the need for a significant amount of traffic for reliable results, and the potential for false positives if not properly controlled.

Can I use Multivariate Testing for Ecommerce Websites to Boost Sales?

Yes, multivariate testing is highly effective for ecommerce sites. You can test various elements like product descriptions, images, pricing, and checkout processes to optimize for higher conversion rates and increased sales.

Can Multivariate Testing be Used for Mobile App Optimization?

Yes, multivariate testing can be applied to mobile apps. You can test various app elements, such as user interface components, navigation menus, and in-app messages, to enhance user engagement and conversions.

What are the Key Differences Between A/B Testing and Multivariate Testing?

A/B Testing

What it tests: A/B testing compares two different versions of a webpage, typically a control version (A) and a variant (B), with often only a single element changed.

How it works: Users are randomly assigned to either the control group (A) or the variant group (B). The two groups experience different versions of the webpage, and their interactions and conversions are compared.

Use case: A/B testing is ideal for testing the impact of one or a few isolated changes, such as different headlines, button colors, or call-to-action text.

Multivariate Testing

What it tests: Multivariate testing tests multiple variations of multiple elements simultaneously on a webpage.

How it works: Multivariate testing divides visitors into different groups, each exposed to a unique combination of variations for various elements (e.g. headlines, images, button colors). It systematically tests the interactions between these elements.

Use case: Multivariate testing is suitable for testing complex webpages with multiple elements that may interact with each other. It helps identify the most effective combinations of elements to maximize conversions.

In summary, while A/B testing focuses on comparing two versions of a page, multivariate testing explores the interactions between multiple elements in various combinations. A/B testing is simpler and faster to set up, while MVT is more complex but offers insights into how different elements work together to influence user behavior. The choice between them depends on your specific testing goals and the complexity of the changes you want to evaluate.

A Final Note on Multivariate Testing and Website Optimization

Not only does multivariate testing allow you to test multiple combinations of elements on a page, but it also provides learnings as to how these elements work with each other. When configuring combinations for testing, the possibilities are endless and it can be easy to get wrapped up in the infinite number of combinations. The learnings you take from multivariate testing can also be applied to future webpage design as you build your web presence.

Additionally, for folks looking to take the guesswork out of website testing and optimization, AI Optimize incorporates multivariate testing with a layer of machine learning that determines to whom and how often a variation is shown. This technology allows users to test an endless number of variations with speed and precision, maximizing resources and revenue.