A/B Testing as a PRO!

Hey! Today, I decided to write a little more about the practice of A/B testing and the positive impacts that it can bring to your business.

First of all, what is A/B testing?

This type of test is a quantitative research technique used in digital products to collect metrics about the behavior and approval of people who are using two variants, as the name says, A and B. Precisely on websites and applications, A/B testings are used to monitor the impact that visual or content changes on pages cause on browsing behavior, which can bring more or less results.

It is important to remember that are several types of tests to collect information about the use of the product, such as heat maps, usability tests or interviews. However, it is up to a deep study with a UX Researcher to choose the ideal test to use when deciding to collect answers about the user's behavior.

How to improve my business using this practice?

For context, Netflix performs several A/B testing on its platform in order to collect usage data and also to test your hypotheses. One of the easiest examples of viewing A/B testing on Netflix are series and movie banners. You know? Those big banners which appears at very top of the screen? So, most likely the images that appear in your account are not the same as mine. That said, Netflix tries to choose the right images for each type of audience.

If you want to know more about the Netflix testing process here is a link explaining everything.

What many people do not know is that this type of test does not end when we finish the experiment. The results however generate many insights about the use of the product. Through the results, we can understand when a given situation, what the person likes, and several other behaviors that are being taken as changes happen during navigation.

The more we know people, the more assertiveness we are able to bring when creating digital products, thus we can make content that aggregates and satisfies even more, therefore, the navigation time is longer and conversion rates increase.

I think it is important to highlight that after the test, it is very important to document everything and save data in addition to the results, for example, “What was the tested hypothesis?” and also “Who is the public exposed to?”, so we can have an accumulated history about what was tested in order to revisit it when there is a needed to pursue new tests and propagate the product with continuous improvements.