Multivariate Testing vs AB Testing: What’s the Difference?

Testing different web strategies, whether using AB or multivariate (MVT) testing, has one primary goal – optimizing a web page or digital touchpoint. Finding the optimal version of a webpage for a given audience so that it moves visitors to act, is why we test.

To employ testing effectively, you need to understand the distinction between multivariate testing vs AB testing since they each have their strengths and weaknesses. In this post, we’ll review the methodology, benefits, and limitations of AB versus multivariate testing, present a few use cases, and give you some best practices to get you started with your own testing strategy.

Difference Between Multivariate Testing vs AB Testing

A good shortcut to help remember the difference between MVT and AB testing is the former tests multiple variables on a webpage and the latter compares two (or sometimes more than 2) versions of a single page, but only looks at one element like a headline or image. Here’s a more precise explanation.

What is Multivariate Testing?

With multivariate testing, you’re comparing multiple elements (the variables) on a single page. This allows you to see what combination of page elements works the best. Maybe you’re looking at how the hero image, CTA buttons, and navigation work together to move people further along in the buying journey (for example). In this scenario, each of these elements is a variable (image, button, navigation). 

In a MVT, you’ll pick a few key items on the page, create variations for each, and then mix and match. The goal of the test is to find the most effective combination – the one that moves the needle in some way. Multivariate testing needs more traffic compared to AB testing, but it’s worth the wait to help you uncover the recipe for the perfect page (if that even exists) by seeing how – or if – the ingredients work together.

What is AB Testing?

AB testing, also called “split testing”, compares two or more versions of a web page to see which one works better. The page itself is the variable, with each page identical except for a single element – headline position, hero image, CTA text, etc. By “work” we mean achieves a goal like getting a visitor to watch a video, click on a link, or buy the featured item on the page.

Think of it as a digital face-off between two (or more) contenders. You’re basically asking your site visitors what version they like better without actually asking. AB testing is quick to set up, easy to interpret, and doesn’t need a ton of traffic to get reliable results. It’s perfect for when you want to test big ideas or small tweaks without getting lost in the weeds.

Multivariate Testing vs AB Testing Examples

Testing is important because audiences and markets are different and it’s the closest tool you have to a crystal ball in terms of knowing what resonates with people.

You’ll have your own goals and desired outcomes or actions – retailers want more sales, B2B SaaS companies want more leads, etc. But here are a few examples to add some tangibility to the “what” and “why” of multivariate and AB testing.

Multivariate Testing Examples

• Optimizing Pet Fashion: An ecommerce merchant specializing in clothing for pugs wants to sell more dog-sized Christmas sweaters. They decide to run a multivariate test on a product page. They’re testing three elements: product images (studio shots vs. action shots), color options display (swatches vs. dropdown), and customer review placement (top vs. bottom). With eight combinations to test, they testing which mix will inspire Fido’s parents to click “Add to Cart”.
• Increasing Demo Requests: A sales enablement platform wants to drive more demo requests from qualified leads. They set up a multivariate test on their landing page, tweaking the headline (“Boost Your Sales Team’s Performance” vs. “Close Deals Faster”), hero image (team in action vs. graph showing results), and CTA button text (“Get a Demo” vs. “Speak with An Expert”). As different visitors see different combinations, the marketing team learns which version mix generates the most demo requests.

AB Testing Examples

• Selling Niche Products: A craft retailer is testing some new ecommerce approaches to boost sales. They notice that the “DIY Candle Making Kit” page is getting lots of views, but sales are lukewarm. They decide to AB test the product description. Version A is the current text-heavy breakdown. Version B, a punchy bulleted list with quirky candle puns. Half of the page visitors see wordy, half see witty. Figuring out which one works helps them increase sales for DIY candle kits by 10%. 
• Driving More Trials: A marketing agency’s landing page is getting tons of traffic but few sign-ups. They suspect the page headline is the culprit, so they create two versions. Version A: “Get More From Your Media Budget Today!” Version B: “Save 20 Hours a Week on Automated Targeting – Guaranteed.” They split the traffic to the page to see which headline gets more people clicking the “Get a Custom Quote” button.

How Does Multivariate Testing Work?

To run a multivariate test, begin by identifying the elements you want to test. These are your variables. Let’s say you choose a headline, an image, and a CTA button to see how they play together on the page. For each element, you create a web page with different variations – maybe two headline options, two images, and two button designs.

The test creates every possible combination of these variations. In this case, that’s 2 x 2 x 2 = 8 different versions of your page.

When visitors land on your site, they’re randomly assigned to one of these versions. The testing software tracks how each version performs against your chosen metrics. These could be clicks, sign-ups, purchases, or whatever matters to your business. This is why you need more traffic for a MVT versus an AB test. You need to make sure the results are statistically significant. 

As data accrues, you can see what version wins and how each element contributes to that success. One of the most useful outcomes of an MVT is that it helps you understand the interplay between different page components and their impact on user behavior.

Multivariate Testing Benefits & Limitations

Multivariate testing can help you create incredibly effective web pages, but it’s complex and time consuming. That said, it also offers powerful insights. Here’s a quick snapshot of the benefits and limitations of this testing approach. 

Multivariate Testing Benefits

• Comprehensive insights about how different elements interact on a single page give you a holistic understanding of page performance.
• Evaluates multiple variables simultaneously, potentially saving time.
• Identifies the exact combination of elements that perform best, so you know where to focus your optimization strategy.

Multivariate Testing Limitations

• Requires more traffic than AB tests to achieve statistical significance.
• Can more complex to set up and analyze, especially if you’re new to testing.
• Can take longer since there are more variations being tested.
• Results can be muddled and inconclusive when too many variables are tested.

How Does AB Testing Work?

To run an AB test, start by selecting a single element to test. This is your variable. Let’s say you choose a CTA button. You create two versions of a web page: the original (A) and a variation (B).

Think of it as a digital face-off between two (or more) contenders. You’re basically asking your site visitors what version they like better without actually asking. AB testing is quick to set up and easy to interpret. You’ll also get reliable results with less traffic than you need for MVT.

AB Testing Benefits & Limitations

AB testing comes with its own set of benefits and limitations. It’s a simpler approach overall. Here are some things to consider. 

AB Testing Benefits

• Simple to set up and analyze – it’s accessible even for those new to testing.
• Requires less traffic than MVT to achieve statistical significance.
• Provides clear, actionable results by isolating the impact of a single change.
• Fast to implement – a great solution for rapid iteration and improvement.

AB Testing Limitations

• Tests one variable at a time which means you may miss potential interactions between elements.
• May oversimplify complex user behaviors and preferences.
• You’ll need to run a separate test for every element you’re optimizing.
• You lose the time advantage when you run multiple tests, since each test needs to get enough traffic to be statistically significant.

When to Use Multivariate Vs AB Testing

Choosing between MVT and AB testing depends on your goals, resources, and website traffic. Here’s a quick guide to help you decide:

When to Use Multivariate Testing

MVT is ideal if you have:

• High traffic volumes (think 100,000+ monthly visitors)
• Multiple elements to test simultaneously
• Time to run longer tests
• A desire to understand complex interactions between page elements

When to Use AB Testing

AB testing is your go-to when:

• You’re testing a single, impactful change
• Your site has lower traffic volumes
• You need quick results
• You’re new to testing and want to start simple
• You’re comparing two radically different page designs