A/B testing vs. multivariate testing: What’s the difference and which is best for your website?

Should you optimize your web pages using a multivariate test or an A/B test? Both can assist you in achieving a conversion target and assisting you in making data-driven decisions. However, there are considerable distinctions between the two tests’ results and methods.

Definitions of A/B Testing and Multivariate Testing

A/B Test:

An A/B test, commonly referred to as a split test, contrasts two versions of a web page (and occasionally more) to see which one performs better in terms of achieving a particular conversion objective. 

The two pages typically differ significantly from one another and occasionally are completely unrelated. This testing technique can be used to contrast two iterations of an email, app UI, or advertisement.

Multivariate Test:

To determine how variations in several page parts or elements behave when combined, a multivariate test is employed. For every combination of variants, very similar yet distinctive pages are created to see which one has the highest conversion rates.

 This kind of test can help you optimize specific web page elements by revealing which ones have the most effect on user engagement.

Examples:

Two pages with entirely different headlines, text, CTAs, and graphics are compared in an A/B test.

In a multivariate test, otherwise, identical pages are contrasted, with the exception of the text’s typeface and CTA’s size. In order to compare every potential combination of variants, four pages are constructed.

Major Differences Between Multivariate And A/B Testing

A/B tests and multivariate testing are very different from one another in a number of respects, even though some of the equivalent principles and technologies are utilized in both.

Combinations of Differences

Due to the numerous combinations of variables, many people believe that multivariate testing is more complicated than A/B tests. In addition, unlike an A/B test, it is not an either/or situation.

 To contrast and compare, there may be dozens of different variable combinations. In contrast to an A/B test, you also are testing how different variables react with each other on the page.

A Number Of Test Pages:

There will only be two versions of a web page in an A/B test (sometimes three or four). On the other hand, a multivariate test may consist of dozens of distinct variations of the web page due to the testing of various variable combinations.

Requirements For Traffic:

Both A/B tests, as well as multivariate tests require an equal distribution of traffic among the web pages. So, compared to an A/B test with only two-page versions, a multivariate test that can contain numerous page versions requires more traffic to achieve statistically significant results.

Every page in an A/B test could receive 500 views, for instance, if your landing page received 1,000 views in a single week. Yet, each of the 12-page variations in a multivariate test would receive just about 83 views.

Local vs. Global Optimization:

Multivariate testing is typically used to determine the best version of distinct website design elements, whereas A/B tests are frequently used to identify the most effective overall page. The global optimum vs the local optimum is another name for this.

Large Versus Small Changes:

A/B tests typically compare vastly different sites that have undergone significant changes. The variations are typically more subtle in a multivariate test. Therefore, the differences aren’t as obvious.

 In essence, an A/B test compares two completely different versions of a web page, whereas a multivariate test compares various features on the same web page.

Understanding The Outcomes:

Because there are fewer and more drastically varied test pages, the findings of A/B tests are typically simpler to understand. The findings of multivariate tests can occasionally be less definite due to the subtlety of the changes and quantity of various pages.

Duration of Results:

Because there are just two options getting evaluated, and they are both obviously distinct, an A/B test will yield results much faster. A multivariate test can take months to perform, depending on the volume of traffic and the complexity of the variables.

Do an A/B Test Whenever Possible When:

.testing just one parameter

.Comparing two very different web page iterations

.Making a significant adjustment (like having two totally different layouts)

.Data and insight are urgently required.

.A multi-scenario experience is available.

.Managing a little quantity of traffic 

.in the early stages of development, still working with customers

Use of Multivariate Tests:

Although multivariate tests are less common than A/B tests, they offer information that split testing cannot.

.Use a multivariate test whenever possible when:

.There are multiple variables to combine for testing.

.A landing page receives a lot of traffic.

.Optimising an already-optimized landing page and making it even better

.Attempting to determine the page components that have the most influence on conversion and KPIs

.Attempting to improve certain components

.A landing page’s conversion rate is high (above 10%).

When an element is used on multiple pages, such as a universal CTA, navigation, or footer, a multivariate test is especially helpful.

Making Use of Multivariate and A/B Tests:

The employment of both A/B testing and multivariate tests is, in some circumstances, the ideal choice, according to several analytics & web design professionals. 

To find out where the design or landing page design responds best, run an A/B test first. Multivariate testing is able to be utilized to optimize the landing page and gather information for subsequent development once it has attracted a sizable quantity of traffic. You can achieve the highest conversion rate possible by combining the results of the two tests.

A/B Testing Limitations:

A/B testing is a flexible tool that, combined with clever experiment design and a dedication to iterative cycles of testing and redesign, may help you significantly improve your website. Yet, it’s critical to remember that this type of test’s limits is encapsulated in the name.

 A/B testing works well for determining how two to four variables affect how users interact with the website. A/B testing will not provide insight into how different variables interact on a single page, and tests with many variables take longer to run.

Multivariate Testing Has Some Restrictions:

The volume of traffic required to complete the test is the single biggest constraint of multivariate testing. All experiments are completely factorial, thus if too many variables are changed at once, the variety of potential possibilities that must be investigated increases quickly. 

Even a popular website might struggle to finish a test with much more than 25 possible choices in a reasonable amount of time. 

It’s crucial to think about how multivariate tests will fit into your testing and redesign cycle as a whole when implementing them.

Even if you have knowledge of how a specific aspect affects your website, you may still want to run more A/B testing cycles to investigate completely unrelated concepts. 

However, there are occasions when doing a full multivariate test is not worth the extra work required when many carefully planned A/B tests would suffice.

Conclusion:

Ultimately, A/B and multivariate testing are helpful approaches to aid in the testing of hypotheses and the making of judgments based on facts rather than preconceptions. Which ones are most useful depends on their respective advantages and disadvantages. Weigh them both carefully before working on your own customized website design.

But combining them can be the most effective strategy to completely optimize not only a single web page but also your whole website, app, email marketing, or advertising campaign.