Creating an A/B Test

A/B tests measure the success of messages and other areas of your app. Each test compares a control group of users, who receive no experience changes, to one or more test groups (also known as variants). In Leanplum, you can A/B test your app's variablesmessages, and interfaces. There are two different ways to create A/B tests.

Method 1: From the Message Composer or Interface Center

If you are creating a new message or interface, you can create an A/B test directly from the Message Composer or Interface Builder.

Click the additional options button ( ... ) next to Send Now in the message composer. This will reveal an A/B test option in the dropdown. 

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Choosing A/B test from the dropdown will create a new test based on the message or interface you were creating. Your message or interface's targets and other settings will automatically be applied to the A/B test. You'll have a chance to edit these settings and preview the test before you send it out to users.

Note: In general, it's best to test new messages and features before sending to all your users. If you decide to test a message or UI that is already active (or live), the test will only include users who trigger the message after the test start date.

Method 2: Test directly from the A/B Testing Dashboard

You can also create an A/B test directly from the A/B testing tab. Click the Create A/B Test button to get started.

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Next, you'll be able to configure all your test settings, including your goals, test targets, variants, and more. See below for more on each step in setting up your test:

  1. Setting and reaching your goals
  2. Targeting your A/B test
  3. Using impression criteria
  4. Setting the distribution
  5. Add and edit content for each test group
  6. Estimating your test completion date and making changes
  7. Preview an A/B test on your device
  8. Gradually roll out A/B tests to your audience
  9. View A/B test results

Note that you'll need to register a test device to preview your A/B tests before starting them.

Didn't find what you were looking for? See the A/B testing section of our Help Center.


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