What Is A/B Testing? How A/B Testing Works?
What is A/B testing in digital marketing? A/B testing is also known as split testing or bucket testing. It is a method of comparing two versions of a webpage or app against each other to determine which one performs better.
How A/B testing works? Now suppose a modification is done on the website/app to create a second version of it. This change can be as simple as a change in headline/button. After modification, half of the traffic is shown the original version of the page, which is called control, and half are shown the modified version of the page, which is called the variation.
For example, the control version is getting 23% traffic, and the variation version is getting 37%. So based on this information, you can decide what type of change is needed and to improve. A/B testing allows careful changes to their user experiences. You can observe everything here, like changes you’ve made should be continued or modified or are perfect.
In another perspective, an A/B test can be proven wrong if the user does not like modifications. They might not have the best experience in this variation, so the A/B test can go wrong. You have to make further changes and try again.
In the video, a survey is shown for one month of A/B testing. You can see with A/B testing, you can catch a height, and without it, you have to experiment with a lot of things. So before going to continue implement, check new variations, observe them, and then go for them. So let’s understand A/B testing with an example.
Here two examples are shown with their visits, sales & conversion rate. We can check statistical comparison between these two using many platforms. Here, we are doing it using kissmetrics. After entering data, you can see in the results; it is said that variation B was better, and changes in variation B will improve conversion rate. So this way, you can check live A/B testing by feeding data into tabs.
The A/B testing process is simple. First, collect data and identify your goals that what you want to achieve from the collected data. You have to make a situation between things you are going to test. That is called a hypothesis. Create different variations and fire traffic on them and run an experiment. After that, analyze the results. So start using A/B testing. This will guide you where you are making mistakes and where you need to improve.
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