Marketing professionals use a variety of techniques and tests to assess the best marketing methods as well as how their marketing campaigns are performing. Two common tests used by marketers are multivariate testing and A/B testing. While similar in nature, these tests look at a different number of information and reveal varying information for each variable. In this article, we’ll answer several frequently asked questions about multivariate testing and its relationship with A/B testing, including when multivariate and A/B testing are used, the benefits of each and which one is best.
When is multivariate testing used?
Multivariate testing is most frequently used when a business or person wants to test several different elements of a product, service or website. Whereas other methods only allow you to test one variable or two at the most, multivariate testing allows companies to test several different variables at once.
This type of testing is most commonly used by marketing experts who either work as an employee of a company or who are hired to come in and analyze a companys marketing strategy.
Its important to note that multivariate testing is not used to completely change a website or other marketing tool. It is used to make small changes that could potentially have a large impact. Common variables tested include headlines, images, text, calls-to-action (CTAs), text copy, font, form length and headings.
What is multivariate testing?
Multivariate testing is a marketing technique used to test a hypothesis that involves several different variables being changed. This testing is used to assess which variable combinations perform the highest out of all possible variable combinations. For example, if a company wants to test several features on a new app it plans to launch, the company would likely use multivariate testing to determine which combination of features is the most effective with users.
In multivariate testing, more than one variable is always testing. For example, a company may change the picture on its webpage as well as the type of font used on the webpage. Several different variations of each variable are created and combined with the variations of other variables. For example, the company may choose three different fonts to test and four different pictures for a combined total of seven versions of the webpage to test. The variables are then tested at the same time to determine which variation performs the best.
What are the limitations of multivariate testing?
There are also a few limitations of multivariate testing that are important to keep in mind when using this type of testing. The primary limitations include:
What are the advantages of multivariate testing?
A primary advantage of multivariate testing is that it allows marketers to specifically target redesigns in a way that is proven effective. This enables marketing professionals to focus on areas of a website or other marketing tool that will have the most impact on users.
Other benefits of multivariate testing include:
What is A/B testing?
A/B testing, also referred to as split testing, is another type of marketing testing method that works to optimize websites by assessing two different version of a webpage and comparing them to see which one performs the best. Two versions of the same webpage are created—version A and version B—and they are made live to test how users interact with and respond to each version. Which webpage each visitor views is randomized.
A/B testing tracks the way in which users interact with the webpage. For example, if the A/B test is analyzing how well two different calls-to-action work, the A/B test would track how many visitors click the call-to-action button on each webpage. The webpage that gets the most clicks on the CTA is considered most effective.
When is A/B testing used?
A/B testing is frequently used by marketers who want to test only one or two variables on a webpage or other marketing platform. This test is especially popular when analyzing how two very different variables affect users. For example, if a company wants to test the call-to-action button on its websites homepage, and one version of the CTA has more text and is a different color than the other, A/B testing would likely be used.
A/B testing may also be used when optimizing a webpage in which only one variable is being altered. For example, if a company wants to determine whether visitors respond better to a pink newsletter sign-up form or a blue one, they would use A/B testing to compare the two and see how they perform with visitors. The newsletter sign-up form version that gets the most sign-ups will be considered the more effective of the two.
What are the advantages of A/B testing?
The primary advantage of A/B testing is that it is a simple yet powerful tool for marketers to assess and compare two different variables. Because A/B testing only involves two different variables, its easier to keep track of the changes made and how each variable performs. Its also a great way to introduce testing as a form of optimization to marketing teams who may be more skeptical about this approach.
What are the limitations of A/B testing?
A main limitation of A/B testing is that it can only test two to four variables at once. This means that marketers who want to test more variables will have to run several A/B tests or use a different method of testing such as multivariate testing. Additionally. A/B testing only tests variables on two different pages. This means that this form of testing will not provide any information as to the interaction between variables on a single webpage.
Which type of testing is better: multivariate testing or A/B testing?
Both A/B testing and multivariate testing are useful when it comes to marketing and optimization. While there is not a test that is necessarily better than the other, there are specific circumstances in which one test would be more appropriate than the other. For example, if you want to test multiple variables, youd likely want to use a multivariate test. However, if you are only interested in testing one or two variables on a webpage, youd likely want to use A/B testing.