A/B testing, also known as split testing or bucket testing, compares two versions of a web page, app, or other product to decide which one performs better.

With AI Personalization, A/B testing involves comparing two versions of search results. These search results are based on the effect of the personalization re-ranking level you set.

By conducting an A/B test, you can find the ideal level of personalization that suits your business and allows you to maximize user engagement and satisfaction.

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Before your begin

Before setting up an A/B test, make sure you have properly configured AI Personalization.

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Launching an A/B test

Dashboard interface for launching an A/B test

You can launch an A/B test directly from the AI Personalization dashboard. The process involves the following steps:

1

Select the index on which you want to A/B test personalization

This is the index for which search results will be compared. You only have access to indices that are configured to use AI Personalization.

2

Define the personalization re-ranking level for the A/B test

This is the level of personalization you want to A/B test against the personalization re-ranking from the configuration.

3

Set the percentage of traffic

This is the share of searches that will be boosted according to the personalization re-ranking level set.

4

Set the duration of the test

This is the maximum duration of time the A/B test will be live after you start it. For the best results, set a duration that’s more likely to lead to high confidence in results.

5

Launch A/B test

This triggers the launch of the A/B test. Your users will now receive personalized search results based on your setup.

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Viewing the results of an A/B test

You can view the results) of all AI Personalization A/B tests in the A/B testing dashboard.

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Further reading

Guide

How A/B test scores are calculated

Guide

Interpreting A/B test results