What is multivariate testing?

Multivariate testing is an advanced way to figure out which changes on your website or app work best together. Instead of testing just one element at a time, like A/B testing, multivariate testing lets you test several different elements at once. Imagine you want to change the headline, image, and call-to-action button on a landing page. Multivariate testing can show you which combination of these changes leads to the most conversions.

This method helps you understand not just if a change works, but how different changes influence each other. It's like running many A/B tests at the same time, but in a more organized way that reveals how elements interact. This deeper insight helps marketers make smarter decisions about their website design and content to get better results.

Why multivariate testing is powerful

Multivariate testing offers a deeper level of insight compared to simpler testing methods like A/B testing. While A/B testing compares two versions of a single element, multivariate testing explores how multiple elements interact when changed simultaneously. This is crucial for experienced marketers who need to understand complex user behavior and optimize entire sections of a page, not just isolated components.

For instance, changing a headline might have one effect, but changing the headline and the hero image and the call-to-action button could lead to an entirely different, and potentially much better, outcome. Multivariate testing helps uncover these synergistic effects. It allows you to pinpoint which specific combinations of variables deliver the highest conversion rates, providing a more complete picture of user preferences and design effectiveness. This approach is particularly valuable when you have a high volume of traffic and need to optimize multiple page elements that are believed to influence each other.

How to set up and analyze multivariate tests

Setting up a multivariate test requires careful planning. First, you need to identify the elements you want to test and the variations for each. For example, if you're testing a landing page, your elements might be the headline, the main image, and the call-to-action button. Each element would have 2-3 variations. A headline could have "Get Started Today" and "Boost Your Sales Now." An image could be "Product Shot A" or "Lifestyle Shot B." A button could be "Learn More" or "Sign Up Free."

Designing your test

The total number of variations tested is the product of the number of variations for each element. If you have 2 headlines, 2 images, and 2 button texts, you'll be testing 2 x 2 x 2 = 8 different combinations. Each combination is shown to a segment of your audience. Tools like Google Optimize (though sunsetting), VWO, or Optimizely can help you create these variations and distribute them.

Analyzing the results

Analyzing multivariate test results involves statistical significance to ensure your findings are not due to random chance. You will look at the performance of each combination to identify the winner. Beyond just finding the best combination, you can also often see which individual elements had the most impact across all combinations. This helps you understand the relative importance of each element and informs future design decisions. Pay close attention to conversion rates, average session duration, and bounce rates for each variation. Ensure you run the test long enough to gather sufficient data and reach statistical significance.

Best practices for advanced optimization

To get the most out of multivariate testing, experienced marketers should follow several key practices.

Start with a hypothesis

Before testing, have a clear idea of what you expect to happen and why. For example, "We believe a benefit-driven headline combined with a human-centric image and a clear call-to-action will increase sign-ups by 15%." This guides your test design and analysis.

Focus on high-traffic pages

Multivariate tests require a significant amount of traffic to reach statistical significance for all combinations. Choose pages that receive a lot of visitors, such as your homepage, key landing pages, or product pages.Test meaningful changes

Avoid testing too many minor variations that might not move the needle significantly. Instead, focus on elements that are likely to have a substantial impact on user behavior. Consider testing radical changes if you have enough traffic and a strong hypothesis.

Don't stop at one test

Optimization is an ongoing process. The insights gained from one multivariate test can inform the next. Continuously refine your understanding of user behavior and iteratively improve your website or app.

Integrate with user research

Combine quantitative data from multivariate tests with qualitative insights from user interviews, heatmaps, and session recordings. This holistic approach provides a richer understanding of why certain combinations perform better.

Multivariate testing is a powerful tool for advanced marketers seeking to deeply understand user interactions and optimize complex web pages. By testing multiple elements simultaneously, you can uncover high-performing combinations and gain insights into element synergy. Always approach testing with clear hypotheses, ensure sufficient traffic, and integrate your findings with broader user research to drive continuous improvement in your marketing efforts.