What Is Multivariate Testing? (Including Benefits and FAQ)

By Indeed Editorial Team

Published November 9, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Marketing professionals and data analysts use multivariate testing to assess their methods, campaigns, software, and products to determine how well they are performing. The test modifies several variables to show which combination is the best option for a campaign or product. If you have an interest in data analysis and marketing, it's important to understand this testing method and know how to use it to improve operations and boost company growth. In this article, we discuss the multivariate test and its types, explain when to use it, outline its benefits and limitations, and answer frequently asked questions.

What is multivariate testing?

Data analysts and marketing professionals use multivariate testing to evaluate the productivity of several combinations of variables. It assesses which combination of variables performs the best of all the possibilities. For example, a company evaluating the performance of several features on its new website may use a multivariate test to determine which combination of website features is the most effective for its customers. In this test method, several elements of the system swap place to form different combinations, and these combinations undergo the same testing concurrently to find the winning combination.

For example, the company testing its website features may swap the background picture of its webpage, change the font, or use a different layout for the home page. The tester makes each combination slightly different from the others to achieve the combination that best matches the company's requirements. There's no limit to the number of combinations a company can test, but the higher the number of combinations, the higher the traffic and time to complete the test.

Read more: What Is STLC? Software Testing Life Cycle Phases Explained

Types of multivariate tests

There are two main types of multivariate tests:

  • Full factorial testing: Full factorial is a method that designs all combinations and tests them on an equal part of the company's traffic. For example, if a company tests three variants of one element and four variants for another element of its website, each of the four combinations receives 14.28% of its traffic.

  • Fractional factorial testing: Fractional factorial testing is a less accurate method that only subjects a select number of combinations to testing traffic. In this method, the company statistically deduces the conversation rate of its untested combinations from the results of the combinations it tested.

When do you use the multivariate test?

Companies perform this test to determine the viability of several elements of their websites, campaigns, products, or services. Most testing methods only allow you to determine the productivity of one or two variable combinations simultaneously, but the multivariate method allows you to test many more combinations. Usually, marketing experts and data analysts use this method when analyzing a company's strategies and performance. The purpose of this test isn't to change the website or product completely, but only to implement changes that can positively affect its performance.

Read more: Types of Software Testing Methodologies: A Complete Guide

How to use the multivariate test

Here's a simple framework to use when getting started with the multivariate test method:

  1. Analyze your data. Analyze your website data to identify any visitor pain areas or sections that are less productive. Using your analysis, pick the elements of that area you want to change and test.

  2. Form a hypothesis. Draft a solid hypothesis that targets the problem with each element on the website or product. You can run with the hypothesis when it provides a viable solution to the problem.

  3. Create the variations. Create the different combinations of the website, product, or system you want to test. Each combination is slightly different, so ensure you swap out one or two elements in each version.

  4. Define your goals. Configure the settings for each combination and your traffic, such as limiting how many visitors can interact with each version. After this, define the conversion goals you wish to measure against the test results.

  5. Run the test. Launch the different combinations and run the multivariate test to see how customers and visitors interact with each one. Keep the tests running until you receive results with statistical significance.

  6. Analyze the result. Analyze your test results to determine the best combination out of all the different variations. After finding the best variation, you can use the results to optimize the website or business operations.

  7. Implement analytics and insights. Use the analytics and insights from the results to better understand the target audience. The insights can also help to streamline business optimization and make general operations more effective.

Read more: What Is Web Testing? (With Definition, Types, and Examples)

Advantages of this testing method

A big advantage of this method is that it allows you to target specific redesigns and improve the overall effectiveness of software or a product. Here are a few more benefits of this testing method:

  • It allows a company to focus more on areas of the product or website that have the most positive impact or influence on users.

  • It helps a company analyze the impact of changing each variation and better measure the benefits of each combination.

  • It allows a company to avoid performing multiple single tests because it can test all combinations simultaneously.

  • It allows a company t measure the effect of the interaction of several different variables more easily.

Related: Guide on Planning a Test (Plus Importance of a Test Plan)

Limitations of this method

Several limitations come with the multivariate method. Here are a few of them:

  • It requires more traffic. When a company decides to test several combinations of variables at once, it requires a lot of traffic to get sufficient results from those combinations, especially where there are more than ten. Not many websites get enough traffic, which leads to incomplete tests and results that aren't statistically relevant.

  • Testing is complex. It's a complex testing method compared with much simpler tests, such as the A/B method. The complexity of this test sometimes makes the results confusing and challenging to understand.

  • It can be time-consuming. It can take longer than simpler methods due to the many combinations the company creates, implements, and tests all at once.

Read more: Types of Quality Control (With Definition and Importance)

FAQs about the multivariate test method

Here are answers to some of the frequently asked questions regarding this method:

What is the difference between multivariate and A/B testing?

A/B testing is another method where the company optimizes its websites, products, or services by creating and testing two different versions of the item to determine which performs better and is more in line with the company's requirements. Here are some differences between the two methods:

  • Nature of the test: In A/B testing, the test is usually random, so each visitor only interacts with one version of the item, not both. In contrast, the multivariate method may subject one visitor to several combinations of different variables.

  • Suitability for testing multiple combinations: Another core difference is that A/B testing is only suitable for performing assessments when there are just two combinations. The multivariate method is a better fit for many combinations.

  • Changes per combination: In the A/B test method, the changes between each combination are striking, as there are only two options. In contrast, the multivariate method only implements small variable changes in each combination it tests.

  • Level of required traffic: The A/B method has fewer combinations than the multivariate method, requiring minimal traffic to produce useful statistical results. In contrast, the multivariate test requires a large volume of traffic and needs even more as you add more combinations.

  • Length of testing time: The minimal traffic requirement for the A/B method also means it takes less time to test. In contrast, the multivariate method takes significantly longer to conclude and produce useful results.

Related: Test Plan vs. Test Strategy: What Are the Differences?

How does the multivariate method boost conversion rates?

Multivariate tests can be extremely powerful tools to help you drive dramatic improvements in a company's key metrics and business operations. If a company wants to optimize the landing page of its website and sales pages as part of its marketing campaign, a multivariate test can help you determine which version of both pages is the best option for the campaign. The improvement then boosts the performance and productivity of the campaign, which also improves the conversion rate.

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