Digital Marketing

Understanding Multivariate Testing: Definition and Examples

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By Pep Canals, on 6 February 2024

Multivariate testing (or MVT) in marketing is a trial in which different versions of the same element are created by altering multiple variables to validate an initial hypothesis. The goal is to test an initial hypothesis and figure out which combination produces the best results when shown to users or customers.

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Understanding Multivariate Testing


Benefits of Multivariate Testing

One of the primary advantages of this test is the ability to move beyond intuition. Multivariate testing allows your company's decisions to be more data-driven than reliant on the team's gut feelings, ensuring that your actions are on the right track.

This data-centric approach enables you to:

  • Increase the profitability of your actions.
  • Have a clearer strategy for the future, as insights from MVT can inform upcoming campaigns.
  • Save time and money by targeting more effectively and avoiding wasteful actions.

Limits of Multivariate Testing

Typically, MVT involves creating more than two or three versions of an element. To obtain significant results, it is crucial that a high number of individuals view each of the different versions. This can be challenging as the total audience must be divided among these versions, potentially extending the test duration or leading to inconclusive results.


Differences from A/B Testing

A/B testing involves creating only two versions of a variable. However, there are also A/B/C tests where three versions of a variable are created. The key distinction between these and MVT lies in the number of variables modified—A/B and A/B/C changes one variable, while MVT alters multiple.

Additionally, A/B or A/B/C tests usually provide a clearer verdict as only one aspect is changed. In contrast, validating hypotheses in multivariate testing is often more complex due to the influence of multiple factors, which can be challenging to identify.

Moreover, A/B tests are much easier to set up and execute since only one variable needs to be changed.


Which Is Better?

There is no superior type of test; it depends on what you aim to discover. If You are testing details, A/B tests are preferable, especially for beginners. However, MVT is recommended for making broader and more radical changes.


How to Conduct Multivariate Testing Step by Step


Define Your Goals

Determine what you want to enhance through MVT. Whether it's increasing sales, doubling traffic, scheduling more meetings, or tripling newsletter subscriptions, write it down as your guide.


Identify What to Change

Once you know what you want to improve, think about the aspects or variables crucial for achieving it. This might include buttons, colors, fonts, prices, images, or calls to action. Analyze which factors will have an impact.


Create Test Variations

Generate different variations. There is no fixed number of versions for this test; sometimes, creating four versions is sufficient, while other cases might require more. It depends on the number of combinations you want to test.


Formulate a Hypothesis

Decide on a hypothesis to test. When changing multiple variables, you can establish different hypotheses, but document them clearly. A good format is "change + effect + justification."


Launch the Test

Once all the preparations are complete, let the audience try the versions. Numerous software tools are available to assist in this process. Versions that lag behind and are ineffective should be turned off to concentrate traffic on the remaining versions.


Set a Test End Date

Establish a clear end date for the MVT, defining when the test will conclude for result analysis. The test cannot last indefinitely.


Analyze Results

After stopping the test, examine whether the initially hypothesis is correct or if the results are surprising. Ensure that the sample size is sufficient for reliable conclusions. Otherwise, the results may be coincidental.


Implement Winning Changes

If everything went smoothly, permanently apply the winning version and get the benefits of this improvement.


Tips for a Successful Multivariate Test

Above, we have shared some tips and warnings to make your multivariate test go as well as possible, but below are some additional factors that are also important:

  • Clearly establish the role of each team member: MVTs are complex and require each professional to be clear about their roles. Therefore, establishing them should be one of the first steps in the process.
  • Keep all the conclusions learned: A multivariate test, like an A/B test, is not something that is done in a moment, applied, and then forgotten. Quite the opposite. The data and information obtained are of great value and can be used for future campaigns or strategies. Therefore, we recommend that you keep all the results and conclusions in a safe place to have them at hand when you need them.
  • Share the results with different teams: Although we have focused here on MVT applied to marketing, the results and conclusions are not only useful for advertising teams, but also for other professionals. Therefore, it is very positive to share them with those teams that may also find them useful. This is also a way to encourage and promote communication between different groups within the same company.


Common Examples of Multivariate Testing


Subscription Button Variations

MVT is often used to test which button variations work best to increase subscription volumes, such as for newsletters. Since a button comprises various elements (font, color, CTA, and shape), MVT is ideal for testing multiple variables within the same aspect.


Complete Landing Page Redesigns

Redesigning entire landing pages is a common and complex example of multivariate testing. Brands frequently experiment with landing pages featuring numerous changes to determine which yields the highest conversions.


PPC Advertisements

PPC ads may appear similar at first glance, but upon closer inspection, they often have many differences. Conducting multivariate tests on PPC ads involves identifying those with a higher cost-per-click and turning them off, thereby retaining more cost-effective ads generating higher traffic.

By understanding and following these steps, you can harness the power of multivariate testing to refine and optimize various elements of your marketing strategy.

People-Led Marketing

Pep Canals

Graduado en Telecomunicaciones y Doctor en Fotónica por el Instituto de Ciencias Fotónicas. Cuenta con más de 5 años de experiencia trabajando con Google Ads y Google Analytics, gestionando estrategias de SEM y todo tipo de campañas a través del embudo, desde búsqueda hasta Youtube..

Graduated with a degree in telecommunications and holds a PhD in photonics from the Institute of Photonic Sciences. He has more than 5 years of experience working with Google Ads and Google Analytics, managing SEM, and all campaigns type across the funnel from search to Youtube.