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Multivariate testing is a technique for testing a hypothesis in which multiple variables are changed. It’s particularly beneficial for marketing teams looking to improve the success rates of different campaign strategies, by making better use of their data.
The goal of multivariate testing is to determine which combination of variables performs the best out of all possible combinations. These variables could refer to any type of app content, such as message copy, visual layout, or screen flows. Multivariate testing can be as simple or complex as is required, so it’s ideal for those looking for new ways to improve the results of both existing and planned campaigns. It can also be used to help determine campaign strategies in the future.
Multivariate testing isn’t the only good option for marketers working on improving the efficiency and ROI of their campaigns. Another popular option is A/B testing, which focuses on the testing of single variables to determine how campaigns should be planned and delivered. Take a look at our full guide to A/B testing for more information on how this testing works, and what it can be used for.
Multivariate tests must be designed carefully to obtain accurate results. There are countless variables that can be tested against each other in multivariate tests, from in-app UI (buttons, text, etc.) to messaging (audience segments, messaging channels, etc.) and channels (push notifications, email, etc.). For example, if you were marketing a retail app, you might consider testing the placement of an ”add to cart” button to measure conversion rates. You could then use these results to optimize the app further.
Multivariate testing works is a good option for experienced marketers and developers who have mastered the art of A/B testing. A thorough understanding of the benefits or A/B testing will enable teams to get the most out of their multivariate testing strategies.
The key difference between standard A/B testing and multivariate testing lies in their complexity. With multivariate testing, several changes are tested against each other at the same time (for example, call-to-action button colors and shopping cart placements). The results of these multivariate tests help marketers analyze the advantages of groups of variants over others, rather than comparing each variable in isolation.
Multivariate testing should only be used on sufficiently sized audience segments. More in-depth analysis invariably takes longer to complete. Marketers should be aware that the more variables included in a test, the longer it will take to complete. Still, with efficient testing, app users will benefit from improved usability while marketers should start seeing increased conversions and customer retention.
By enabling marketers to study multiple results, multivariate testing can bring about significant changes that may result in higher conversion rates long-term. And these conversion rates quickly translate into hugely important results for the business as a whole, rapidly increasing awareness and driving sales in a sustainable way.
Retail app Wanelo, for example, ran extensive tests with Leanplum to measure average session lengths and product saves per user. The changes made after these tests resulted in some negative feedback from users, which then inspired a new app feature, the ”Magic Feed”. The new feature saw a 27 percent increase in product sales as well as improved saves per session and average session length.
To find out more about multivariate testing and what it could mean for your business, please contact our team. They’re here to talk you through how it works.