The mark of a good website is its ability to keep visitors engaged and make them want to come back for more. Only if the visitors return to the website is there a better chance for conversion into sales. For this to happen, changes and updates are a part and parcel of the website’s evolution, so that it can cater to the needs and wants of the visitor.
However, it is not a good idea to simply to make changes and then deploy it live on the website. For one, there could be some errors that would make the visitor’s experience difficult, causing them to decide not to come back. Also, it is necessary to understand what the visitors want and make the changes accordingly. Therefore, testing the updates is necessary and there are two types of tests that are usually done – A/B testing and Multivariate Testing.
A/B testing is a method where a particular page is given two or more versions. The visitors that come to the website are randomly divided and each visitor will see one particular version of the page. The visitors are tracked to see which version of the page is more engaging, which can be done by such aspects as pageviews, time on site, conversion rate, etc. This kind of test is also known as split test. It allows the administrators to understand which version is more engaging and likely to get more conversion.
There is, however, one rule that needs to be followed if the test is to be successful. There can only be one metric changed for the page in its various versions so that it will be easy to determine what was responsible for the increased engagement and which update wasn’t successful. If a version of the page has more than one change, then it would be difficult to identify which metric worked for the visitor. For example, if you make some 10 odd changes on a page, it would be nigh on impossible to determine which worked and what didn’t.
There are tools like Adobe Target, Optimizely, Google Optimize and many more in the market that can help in delivering the variation as well as manage the entire process of testing. The kind of variations that can be done on the page are various, and include things such as layout, design, pictures, headlines, sub-headlines, calls to action, offers, button colours, etc.
A multivariate test is a broader testing of the website and is used to determine which combination of elements works best for the visitors. This test compares combinations of variations in elements on a page to determine which group performs the best for a specific target audience and identifies which elements have the most impact on the activity’s success. Getting this broad idea can be helpful, and later the ab test can be used to determine whether the winning combination is truly working.
It’s important to identify a few key areas/sections of a page and then create a multivariate test with the variations for specifically those sections. The test will be created as a combination of changes made in the variations and each change is attributed as a variation itself. In multivariate tests, the changes are shown to visitors in a different combination. This helps in understanding which section or change is contributing towards the goal.
WHY A/B testing IS MORE USED IN INDUSTRY THAN MULTIVARIATE TESTING
A/B testing is the most used and useful test in testing tools. It can help the conversion rate optimization of the website due to the following reasons:
- The cost and complexity of the testing is high in Multivariate testing.
- Multivariate testing is generally not backed up with good amount of data, which might cause non-reliable results.
- Even after the Multivariate testing is conducted, the combination of the winner must be tested again with A/B testing.
- The audience required for the test is high, which will increase the risk of losing out on conversions