A Comprehensive Guide to Multivariate Testing

Multivariate testing, often referred to as MVT, is a powerful statistical method used to simultaneously test multiple variations of an email or digital asset. Unlike A/B testing, which compares two versions of an email, MVT allows for the comparison of multiple variations, providing more granular insights into user behavior and conversion rates.

While both MVT and A/B testing are used to improve website performance, they differ in their scope and complexity. A/B testing typically compares two versions (A and B), while MVT can test several variations. Additionally, A/B testing usually focuses on a single element (e.g., headline, button, or color), while MVT can test multiple elements at once. MVT is generally more complex to set up and analyze due to the increased number of variables and potential interactions.

Getting Started with Multivariate Testing

To implement multivariate testing, start by defining your goals. Clearly outline the specific objectives you want to achieve through MVT, ensuring they are measurable and aligned with your overall business objectives. Next, identify the elements of your email or digital asset that you want to test. Consider factors such as headlines, images, calls to action, and layout. Once you’ve identified your variables, create multiple variations of each chosen element, ensuring they are distinct in order to test different hypotheses.

Use a testing tool or platform to set up your MVT experiment. Assign a specific number of recipients to each variation to ensure statistical significance. Allow the test to run for a sufficient amount of time to gather enough data, considering factors such as engagement and conversion rates. Analyze the data collected from each variation, looking for statistically significant differences in key metrics like conversion rates and click-through rates.

Once you’ve identified the winning variations, implement them in your marketing campaigns. Customer engagement platforms like Braze can significantly simplify the process of multivariate testing by providing features such as a built-in experimentation engine, data analysis tools, segmentation capabilities, and integration with other marketing tools.

When conducting multivariate testing, follow best practices such as starting small, isolating variables, using statistical significance, continuously testing, and considering user experience. By following these guidelines and leveraging robus marketing technologies, you can effectively implement multivariate testing to drive significant improvements in your email’s performance.

Examples of Multivariate Testing: Beyond A/B Testing

Unlike A/B testing, which compares two versions of a page, MVT allows for the comparison of multiple variations, providing more granular insights into user behavior and conversion rates.

For instance, an e-commerce website might want to test different combinations of headlines, images, and calls to action on their product pages. A/B testing would only allow them to compare two versions (e.g., headline A vs. headline B), while MVT could test multiple headlines, images, and calls to action in various combinations. This allows for a more comprehensive understanding of how these elements interact with each other to influence user behavior.

Another example is a mobile app that wants to test different layouts, button colors, and font sizes. MVT could test various combinations of these elements to determine which combination leads to the highest user engagement and conversion rates. This is a more complex scenario than A/B testing, which would only allow for the comparison of two variations of a single element.

To analyze the results of a multivariate test, it’s important to use statistical significance testing to determine if the differences between variations are truly meaningful. This involves calculating p-values and comparing them to a significance level (e.g., 0.05). If the p-value is lower than the significance level, it indicates that the difference between variations is statistically significant.

Additionally, it’s important to consider other factors such as sample size, test duration, and the overall traffic to the website or digital asset. A larger sample size and longer test duration can increase the reliability of the results.

By carefully analyzing the results of a multivariate test, businesses can identify the winning combinations of elements that lead to the best performance and make data-driven decisions to improve their website or digital asset.

Multivariate Testing in Braze

Braze, a leading customer engagement platform, offers robust multivariate testing capabilities that enable businesses to optimize their marketing campaigns and improve customer engagement. By allowing marketers to create and test multiple variations of their messages, Braze helps identify the most effective elements, such as subject lines, headlines, calls to action, and visuals. This data-driven approach ensures that businesses can deliver personalized and engaging content that resonates with their target audience, leading to higher conversion rates and improved customer satisfaction.

Optimizing Email Campaigns

• Multiple variations: Create multiple versions of an email campaign, varying elements such as subject lines, headlines, calls to action, and images.
• A/B testing limitations: While A/B testing can compare two email variations, MVT in Braze allows for testing several variations simultaneously, providing a more comprehensive understanding of which elements resonate best with your audience.

Personalizing Push Notifications

• Dynamic content: Use Braze’s MVT to test different push notification content based on user segments or behaviors. For example, you might test personalized recommendations, urgency messages, or different call-to-action buttons.
• Improved engagement: By identifying the most effective push notification variations, you can increase user engagement and drive conversions.

Optimizing In-App Messages

• Message placement: Test different locations within your app to determine where in-app messages are most effective.
• Design elements: Experiment with various design elements, such as color schemes, font sizes, and button styles, to see which combinations lead to higher click-through rates and conversions.

By leveraging Braze’s multivariate testing capabilities, businesses can make data-driven decisions to improve their customer engagement strategies and achieve better results.

The Importance of Multivariate Testing

While A/B testing is a valuable tool for comparing two versions of an email or digital asset, it can be limited in its ability to provide insights into the complex interplay of multiple variables. Multivariate testing (MVT), on the other hand, allows for the simultaneous testing of multiple variations of these variables, providing a more comprehensive understanding of how different elements work together to influence user behavior and conversion rates.

Multivariate testing (MVT) can increase return on investment (ROI) by enabling businesses to make data-driven decisions that optimize their marketing campaigns. By simultaneously testing multiple variations of a digital asset, MVT provides a more comprehensive understanding of how different elements interact with each other to influence user behavior and conversion rates. This allows businesses to identify the most effective combinations of elements.

By implementing the winning variations, businesses can improve their marketing performance, leading to higher conversion rates, increased revenue, and a better overall customer experience. This ultimately translates into a higher ROI. Additionally, MVT can help businesses avoid costly mistakes by identifying ineffective elements before they are implemented on a larger scale.

If you are looking to optimize your multivariate testing, give Relationship One a call. We are here to help.