Which one is better?
A/B or Multivariate testing is done to analyse versions of variables for optimization such as of web pages. These two types of testing are similar in their functions but also have differences. Let’s discuss them with their respective functionalities, advantages and disadvantages.
A/B TESTING
Also known as Split testing, it compares two versions of a web page, app interface, email or ad to determine which one is better at meeting a specific conversion goal. It is also the correct method to choose if you don’t have a lot of traffic to your site as you’re only testing two variables.
In cases where only one variable is being tested, it is best to use A/B testing because both versions of webpages being tested would have the same variables. For example, an ecommerce website redesigned its mini cart and wants to rate the conversion of both the old one and the new one. Because both websites have the same variables of information except the difference in mini cart, a split test is recommended. It makes it easy to test and get accurate results. It has a faster and quicker conversion rate because it tests just two versions. That being said, webpages do not need a lot of traffic for this test so for websites that do not have lots of traffic being driven to their site, A/B testing is the best type of testing for quicker results.
Advantages of A/B Testing
- Delivers reliable data very quickly. As said earlier, it does not require a larger amount of traffic to run this test and also, the data needed for testing is small. This allows for tests to produce reliable results faster. When website traffic is splitted, websites that have a lower traffic drive are still able to run the test.
- Provides quicker results. Easy to introduce the concept of optimization by testing to a sceptical team, as it can quickly demonstrate the quantifiable impact of a simple design change and its conversion rates.
- Easy interpretation of results. Interpretation of test results is easier because of its small quantity of data from website traffic used. The faster results are interpreted, the faster decision making is.
Disadvantages of A/B Testing
- Difficult to test many variables. As the name implies, it functions better if variables being tested are not many. Instances where more variables need to be tested, it takes a longer period of time to run such tests.
- Inability to generalise results. Data being analysed are minimal which makes it difficult to generalise results. Analysis is therefore based on one-sided data derived from website traffic.
- Interactions between variables are not shown. When the tests are being made, it compares two or three variables. Split tests do not reveal any information about interaction that ensued between these variables.
MULTIVARIATE TESTING
This test is used to gauge how variations in numerous page sections or elements perform when combined and will give a good conversion rate. You are able to test more than two variables at the same time. It shows the element that has the biggest impact on user engagement and can optimise individual elements of a webpage.
This type of test is encouraged to be used for websites with a relatively larger traffic size. In this case, every version being used for the test has enough data from website traffic to run the test. It becomes easier to ascertain elements which have a higher impact on conversion rate.
Advantages of Multivariate Testing
- Website focus. It helps you target redesign efforts to the elements of your page where they will have the most impact. This is especially useful when designing landing page campaigns.
- Provides interactions between web pages. Unlike A/B testing, multivariate testing provides information on interactions and interactions between web pages. Statistics are on variations versus their conversion rates. A user is more able to make informed decisions because they have insights as to which variables have the highest conversion rates.
- Variables are easier to track. Users can get a true sense of what works and what doesn’t. This can be known because it shows the interactions between variables.
- Significant results. Considerable amount of data from website traffic is required for multivariate testing which makes results significant. Analysis therefore is more holistic as compared to that of A/B testing.
Disadvantages of Multivariate Testing
- Not feasible for websites with less traffic. Multivariate and A/B testing counters each other which makes advantages for A/B testing a disadvantage for Multivariate testing. For instance, a larger amount of traffic is needed to complete the Multivariate testing which becomes a disadvantage for businesses with minimal amount of traffic driven to their websites.
- Time consuming. It is time consuming to analyse results from this test because the process used is much more advanced than that of A/B testing. Because more data is needed for multivariate tests it also takes time to get significant results.
USING BOTH
A/B test can be used to determine which landing page or layout gives the best conversion rate and multivariate can be used to gain insights of future developments. Using both testing makes optimization more powerful because they compliment each other.
Written by: Ruby Mankoe – Data Analyst