What is multivariate testing? | Strategies for success

Every little tweak on your landing page, every change in your ad copy, every adjustment to your call-to-action (CTA) — no matter how small it may seem, it could always be the thing that tips the scales for your conversion rate (for better, or for worse).

So, wouldn’t it be a shame if you didn’t know what change made which impact?

Luckily, you don’t have to do any guessing games, as long as you use multivariate testing, which in blunt terms, is A/B testing on steroids. What it is in more practical terms and how you use it, we’ll explore in this article.

What is a multivariate test?

Multivariate testing is similar to A/B testing in terms of testing a couple of versions of something — from landing page copy, ad assets to CTAs and much more besides. But instead of comparing just two versions, you’re testing multiple variables simultaneously.

This means you can make detailed changes — a different headline here, change of colors there, and a variety of images — and test those tweaks all in different versions. That means you can say with more accuracy what has the biggest impact on the metrics you’re tracking. Ultimately, it makes it easier to find the winning variation of elements that work together to create the most effective user experience and, ultimately, drive conversions.

Where A/B testing might tell you which of two versions of a page performs better, but not necessarily what it is about each page that does the trick, multivariate testing digs deeper, showing you how multiple elements interact with each other. You get the full picture rather than just one piece of the puzzle, and learn more about how consumers react to different elements.

Learn more about how to gather consumer insights with Attest

Difference between multivariate testing and A/B testing methods

A/B testing is likely a staple in your toolkit already. It’s straightforward: you test one element against another—think two versions of a landing page, email subject line, or CTA—to see which performs better. It’s ideal when you’re focusing on a single variable (like the headline or button copy) and need a direct comparison.

But what if you’re not sure about the headline AND the button copy, and maybe also the images? That’s when you should use multivariate testing. Instead of isolating one element, a multivariate test allows you to look at multiple variables at once.

In essence, you’ll be testing several changes in parallel—like the headline, image, CTA, and color scheme—all at the same time, across different combinations.

The results of multivariate testing provide a much richer data set than A/B testing, which basically only gives you a preference for one over the other. Plus, multivariate testing answers a more nuanced question: How do all these elements interact with each other?

The insights you get from that will likely be much more useful in the future than just knowing whether the witty or the straightforward email headline works better.

Benefits of multivariate tests

If you’re already an avid user of A/B testing, you know the value of refining individual elements to boost conversion rates or engagement. But you also know the limitations of A/B testing. So what makes multivariate tests so much better in some cases? We’ll outline why multivariate tests stand out in market research and concept testing and their benefits in consumer research.

Faster, more actionable insights

With A/B testing, you’re stuck testing one element at a time. To get to the ”perfect” landing page, could take a couple of tests, and a whole lot of time. Instead, you could run a more extensive multivariate test and test a couple of elements all at once. This makes your process more efficient, and helps you launch your best-converting landing page quicker.

Deeper understanding of what works (and why)

Sometimes a change to a headline makes a difference, but only when paired with the right image or CTA. Multivariate testing uncovers these interactions between elements that you might miss with A/B tests. You don’t just learn which version is better, but also get more insights into why.

Instead of just knowing “Version B performs better,” you’ll understand that Version B works because of a combination of factors, allowing you to replicate that formula and its success across different campaigns or pages.

Data-driven decisions with confidence

You’re not guessing anymore. When you brief designers and copywriters, you can now finally explain WHY you want certain changes to be made. And in a way, those ‘demands’ come from the customer, not from you, so how could they argue with that?

All jokes aside, multivariate tests give you hard data that links your performance metrics directly to specific design or content elements. It makes future decisions much easier to make, because you can optimize based on real user interactions and concrete evidence from multiple variables.

Maximize ROI without endless tests

A/B testing costs money and time, and so does a multivariate test. But you’ll be running fewer tests, in a shorter amount of time. That means you’re able to optimize your pages or campaigns more thoroughly without running endless separate tests and tweaks. It also means your testing budget is used more efficiently—no need to run different rounds of A/B tests that take weeks or months to yield results, all while having a suboptimal landing page live. With multivariate tests, you can quickly pinpoint what’s working and what’s not, and get more out of your marketing spend.

Ready to gather consumer insights that lead to real growth? See how Attest can help you unlock this potential.

Challenges of multivariate tests

You might be thinking that it’s too complicated and messy to run multivariate tests, with all the possible combinations that you can test. And sure, testing different versions of multiple page elements is more difficult than comparing version A to version B. But you also get much deeper insights.

If you’ve ever been hesitant to dive into this method—or had colleagues push back—it’s usually because of these common concerns. But every challenge comes with a solution, especially if you approach it with the right mindset and tools.

A multivariate test is more complex to set up

There’s no getting around it: multivariate testing is more complex than A/B testing. You’re not just testing one element—you’re testing several, in different combinations. This means that you should carefully plan your test and have a crystal clear understanding of what you’re testing, and why.

To make it easier, especially at first, start by focusing on high-impact elements. Not everything needs to be tested at once. Prioritize the elements that are most likely to move the needle (like headlines, CTAs, and hero images), and build from there. Once you get the hang of it, you can test more detailed elements.

Executing multivariate tests requires more resources

Running multivariate tests often means a bigger sample size, if you want to get statistically significant results, and more time to ensure you’re gathering meaningful data. You also need to make more versions of one asset, and a tool that allows you to easily collect responses from your audience.

But the investment upfront saves time and resources down the road, and can significantly increase your conversion rates. You get all the data you need in one go, meaning you can avoid the need for multiple, drawn-out A/B tests. Multivariate testing condenses the timeline and allows you to increase your conversion rates quicker than before.

Statistical significance takes longer to achieve

As we already touched on, you need a larger sample size to reach statistical significance when you’re testing multiple variates. But this doesn’t mean multivariate testing is inherently inefficient. Especially with a tool like Attest, you can send out a multivariate test to a large audience and get data quickly.

The results of multivariate tests are harder to interpret

Yes, multivariate test results can be trickier to analyze, unless you use the right tools. With A/B testing, it’s straightforward: this headline works better than that one. But when you’re testing multiple variables, you’re analyzing how they interact with each other. To make this easier, lean on tools like Attest that visualize the data for you, highlighting which combinations of elements are working. Also, don’t feel like you have to act on every insight—focus on the biggest wins first and refine from there.

Interference from too many elements

Don’t overcomplicate things when you’re testing several page elements at once. The risk is that one change (say, a new CTA) could impact the perception of another change (like the tone of a headline). This is called the interaction effect, and it can muddy your data.

If you want to mitigate this and optimize your concept testing, be selective about the elements you test together. Stick with elements that complement rather than compete with each other. If you’re unsure, start with smaller, more focused tests before layering on complexity.

When should you use multivariate testing methods?

While A/B testing has its place in refining individual variables, multivariate testing is the way to go when you want a holistic view of how multiple changes work together. Here are some practical scenarios where multivariate testing will be the better testing method:

• Landing page creation: There are multiple elements on landing pages that could be worth testing. With multivariate testing, you can directly see how different page elements interact with each other, helping you build not just a better landing page than version A, but the best one overall.
• Web page redesign: Redesigning your website or individual high-traffic pages like a pricing page? Instead of testing each change in isolation, you can use a multivariate test to find which design elements and layout work best on your audience and what increases conversions.
• Usability testing: If you’re working on a user experience project, like building an app, multivariate testing can uncover how design elements impact usability. Use it in the early stages of designing to quickly make the major decisions, and then later on to refine your UX.
• Conducting informal research: Is your team looking for inspiration, for instance for new visuals or copy styles? If you don’t have enough traffic for A/B testing and don’t want your experiments out in the open, multivariate testing is a great choice. It gives you a safe way to try out multiple ideas and learn from qualitative insights faster than traditional methods.
• Optimizing complex marketing campaigns: If you’re running a multi-channel campaign with ads, landing pages, and email sequences, multivariate testing helps you align all the variables. Instead of testing one email subject line at a time or one ad version against another, test them in combination with your landing pages or other elements, making sure that the entire campaign is firing on all cylinders.
• Validating a product launch: Before launching a product, multivariate testing helps you fine-tune everything. From product descriptions to website imagery, you can make sure that each detail is set up for maximum conversion.

Easing into multivariate testing

Not sure where to start? Start small with elements that are most likely to have the biggest impact on your goals—like your headline, CTA button, and form length. As you gather data and feel more confident in the testing process, you can layer on more variables and optimize your pages or campaigns with data-driven decision-making.

How to implement multivariate testing methods

To get the most out of multivariate testing and make sure each element is tested correctly, it’s important to follow a structured approach. If you want your test to be both statistically sound and actionable, follow these steps:

Step 1: Define your goal and hypothesis

Do you want to improve your conversion rate on a landing page, reduce bounce rates, or boost sign-ups? Identify which elements might be influencing those metrics—CTAs, images, headlines, or form fields. Then, formulate a hypothesis for how different versions of these elements might impact user behavior.

Step 2: Identify variables to test

Once you’ve defined your goals, determine the multiple elements you want to test simultaneously. Keep in mind that the more variables you test, the more combinations (or “variations”) you will have to track, so start with elements that are likely to have the most impact on your goal. This makes it easier to identify how different variables interact and which combination delivers the best result.

Step 3: Set up a credible test environment

Your testing environment needs to reflect real-world conditions as closely as possible. This means that ideally, you set up your multivariate test in the same live environment where your users will interact with your page or campaign.

Another important thing is to avoid bias: whether you’re running the test on a landing page, email campaign, or advertisement, make sure that all versions of the tested elements are evenly distributed.

Step 4: Determine your sample size and duration

To achieve statistical significance, you’ll need enough traffic or responses to each variation of your test. The goal is to have enough data to be confident in your results—too little traffic, and your results will be meaningless. Duration is also key: make sure to run the test long enough to capture a representative snapshot of user behavior, but not so long that external factors (like a holiday promotion) skew the data.

Step 5: Monitor and analyze the incoming data

Once your test is up and running, you’ll be able to monitor how each combination of variables performs. Your testing tool will track how changes to different elements impact your key metrics, such as conversion rate or bounce rate.

Pay special attention to how page elements interact—sometimes, it’s the unexpected combination of variables that delivers the best results.

Step 6: Implement the winning combination

Once your test reaches statistical significance, and you’ve got enough actionable results, it’s time to implement the winning variation. This is the version that delivers the highest impact based on your chosen metric—whether that’s driving conversions, reducing bounce rates, or increasing sign-ups.

To make your multivariate test even more worthwhile, check if you can implement the learnings from it across other pages and assets.

Attest’s creative testing solution

Attest allows you to run multivariate testing to pinpoint which combinations of elements resonate best with your target audience. 

But it doesn’t stop there—Attest offers a wide range of creative testing options, including A/B testing, concept testing, and more, giving you the flexibility to refine every aspect of your marketing strategy.

Gain actionable insights from real-time data and make smarter decisions that improve your marketing impact. Learn more about creative testing with Attest.