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How do I analyze the results of an A/B test?
How do I analyze the results of an A/B test?

Quickly see how your tests are performing so you can bring the best out of them.

Madeleine White avatar
Written by Madeleine White
Updated over a week ago

You've setup an A/B test and now would like to see the first results? This article will explain how you can consult the results of an A/B test and how these can be exported, allowing you to analyze and validate your tests outside of the Dashboard.

Have a look at our other articles in this section if you wish to understand how to create and launch an A/B test. In this article we'll focus on how to visualize the performance of your A/B test.

First, a visual approach to the Dashboard

You can find the visuals of your A/B test results anytime you want in the 'Analysis' section of the Dashboard. To do this, you just need to select a context, then a segment and finally the scenario where your A/B test is taking place (you can select this from the filter options).

The option to “Display A/B test results” will appear just below your filters.

Now that you have selected a second scenario, you'll be able to see that a new contour line is now visible on all graphs. This represents the two scenarios that you have tested: A and B.

This method is very useful for quick check-ins on your results or for observing a trend within a given time period, discovering whether one of the scenarios has out-performed another or not.

This can also help you to work out if a test is nearing completion or not, an important date to be aware of.

Analyze statistics from your exports

When you created an A/B test, you were asked to determine the audience distribution for each scenario:

It's important to take this percentage into account when analyzing the results of an A/B test, especially if you haven't distributed your audience equally (i.e. 50%:50%). You'll have to properly weigh the data before analyzing them.

For example, a result that's a bit too high or low may be due to an imbalance in the scenarios - i.e. there's an under-representation in one of the scenarios in comparison to the other.

Analyzing your data will allow you to draw conclusions about the best scenarios to use for your website as well as to create new tests and continuously optimize your strategy.

If you have any further questions, feel free to contact us via the Intercom chat!

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