Journey Based on A/B Test

Overview

Configuring a journey to perform A/B testing allows you to direct users to different pages and measure the effectiveness of each experience. This approach helps optimize conversions, engagement, and customer satisfaction. For example, you might want to:

• Test two different landing pages to see which drives higher conversions.

• Experiment with different messaging or layouts to determine user preference.

• Split traffic between two checkout flows to measure drop-off rates.

The Split function in Limio Journeys enables you to create multiple destinations for the same conditions. You can define the percentage of traffic allocated to each destination, ensuring that users are distributed as needed. By leveraging A/B testing in Limio Journeys, businesses can optimize customer experiences and improve key performance metrics

Before you start

Before setting up an A/B test, ensure that both pages exist and are ready for users.

Adding A/B test Criteria

1. Define your Condition criteria.

2. Under Actions, ensure Type is set to Destination.

3. Click the pencil ✏️ icon next to Starting Point to define how users enter the journey:

   • Choose an existing tag or create a new one.

   • (Recommended) Set a Fallback Tag to ensure proper routing.

4. Change the Split (%) to your desired split e.g 50%

5. Click Add Split and follow repeat steps 3 & 4

Verification Steps:

1. Open an incognito window, visit the journey URL, and confirm the variant assignment.

2. Repeat multiple times to verify randomization.

   • Expected behaviour (using below example) is to randomly be redirected to journeytest or journeytestalt

Example:

If a user is part of an A/B test campaign, they will be randomly routed to either the journeytest page or the journeytestalt page. This ensures that different experiences can be tested with equal traffic distribution.

In this setup, 50% of users will be directed to the journeytest page, while the other 50% will be sent to the journeytestalt page. This allows businesses to compare engagement, conversion rates, and overall effectiveness of each variation.

By analyzing user interactions on both pages, teams can determine which version performs better and optimize future campaigns accordingly.

📷 Screenshot: View of the example above in action

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