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A/B Testing vs Multivariate Testing

Any business owner may want to improve his business level. So testing is a helpful way to improve the market. Because of the importance of testing, it is divided into some types among them A/B testing and Multivariate testing. In this article, we will show you A/B Testing vs Multivariate Testing.

Differences Between A/B Testing and Multivariate Testing

In the following paragraphs we will discuss A/B Testing vs Multivariate Testing as follow:

 A/B Testing

It is a method of comparing two versions of a webpage or app against each other to determine which one performs better. After you prepare your variations, you present each version to half of your visitors. The test will tell you which version proved most popular among your audience based on specific metrics, such as conversion rate or time on page. A/B testing is the least complex method of evaluating a page design and is useful in a variety of situations. testing radically different ideas for conversion rate optimization. You will find A/B testing in this article.

Pros:

  • Useful in low-data-rate tests.
  • Ease of implementation.
  • Ease of analysis.
  • Flexibility in defining the variable values.
  • Ease of test design.

Cons:

  • A limited number of recipes.
  • Inefficient data collection.

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Multivariate Testing

It is a technique for testing a hypothesis in which multiple variables are modified. The goal of multivariate testing is to determine which combination of variations performs the best out of all of the possible combinations. Websites and mobile apps are made of combinations of changeable elements.

There is Multivariate statistical analysis that refers to multiple advanced techniques for examining relationships among multiple variables at the same time. This type of analysis is desirable because researchers often hypothesize that a given outcome of interest is affected or influenced by more than one thing.

A multivariate testing software will combine all these section specific variations to generate unique versions of a page to be tested and then simply split traffic amongst those versions. optimizing and refining an existing landing page or homepage without doing significant investment in the redesign.

Pros:

  • Provides behaviour analysis.
  • Surfaces dead substance.
  • Guides you on structurization.
  • Allows you to test from a wide range of combinations.
  • Determine the contribution of each variable.

Cons:

  • requires many more variable combinations to be run than A/B.
  • requires more traffic to reach statistical significance than A/B.
  • Major layout changes are not possible.
  • The restrictions of the test setup constrain marketing creativity.
  • gives approximated results.

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