How it differs from A/B testing


There’s seemingly no limit to what you can test in your marketing: conversion rates, offer placements, and even top-performing headlines.

Multivariate tests

The type of tests you can run is also unlimited, but two players take center stage: A/B and multivariate testing. But is there a huge difference between them? And will my results be affected if I choose the wrong choice?

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Yes, there is a difference, and yes, your results will be affected. But you shouldn’t be afraid; In this article, we’ll break down the difference between A/B testing and multivariate testing and tell you exactly when to use each, so your testing runs smoothly and your inbound marketing can go from pretty good to incredibly good.


Multivariate testing vs. A/B testing

What is A/B testing?

What is multivariate testing?

Example of multivariate test

The key difference is that A/B testing focuses on two variables, while multivariate testing has more than 2 variables. Since the difference between the two tests is visually visible, let’s walk through an example.

Example of multivariate and A/B testing

multivariate testing vs a/b testing

In the image above, A/B testing is simply two different versions of the same element, while multivariate testing looks at several different page elements (variables) at different positions on the page.

Given their differences, let’s learn more about each and when to leverage each test in your marketing.

What is A/B testing?

When you perform an A/B test you create two different versions of something – like a landing page, call to action (CTA), or web page – to see which one performs better. The image below is an example of A/B testing.

a/b testing

A/B testing is often done with two different variables, but there are A/B/C tests that test three different versions of web pages. An A/B/C/D test that tests four different versions of web pages, etc.

If you need help running an A/B test, you can use a tool like HubSpot’s. Free Landing Page Builder, which allows you to test different page variations against each other. The best part? HubSpot will automatically crown a winner based on the results.

When to use A/B testing

Use A/B testing when you want to test two specific designs against each other and want to see meaningful results quickly. This is also the right method to choose if you don’t have a lot of traffic to your site, because you are only testing two variables, so large data is not necessary.

Advantages and limitations of A/B testing

Benefits of a/b testing limitations of a/b testing

Data is easier to track.

The focus is on two single variables, so the test results are hyper-focused.

With fewer variables to test, you don’t need a huge amount of traffic to find out which variable is most effective.

You can get results quickly.

When you do multivariate testing, you’re not simply testing a different version of a web page like you do with A/B testing. Instead, you’ll get an idea of ​​what combination of elements best helps you achieve your goals, whether that’s more CTA clicks, form signups, or time on page .

Multivariate testing is more complicated and is better suited to more people. advanced marketing testersbecause it tests multiple variables and how they interact with each other, providing many more possible combinations to the site visitor.

When to use multivariate testing

Only use multivariate testing if you have significant traffic to your website. This way, you can truly determine which components of your website deliver the best results.

Advantages and limitations of multivariate testing

advantages of multivariate testing limitations of multivariate testing
It helps you redesign site pages to have the biggest impact. Requires significant site traffic because you need enough data to test all variables accurately, and not all companies have this traffic.
You can test more than two variables at the same time. This is a more advanced and complex testing process.
The results are significant because multivariate testing requires considerable website traffic.
You can extrapolate the results because multiple variables are tested and you have important data points.

This is a tricky concept, and a visual usually helps clarify complicated ideas. The image below is an example of a multivariate test.

In this example, notice how each variation plays with placement, color, style and format. Unlike A/B testing, where the two variants are usually significantly different, the variable differences in a multivariate test can be more subtle.

multivariate test example

Back to you

Remember that for multivariate and A/B testing to yield meaningful results, it is not enough to have overall site traffic: the pages you are testing must also receive significant traffic. So make sure you select pages that people can find and visit regularly so that your test produces enough data to analyze.

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