nShift Checkout Experiments is a powerful tool that makes it easy for you to carry out A/B testing to help you optimize your checkout flow and improve conversion rates. It involves comparing two versions of your checkout flow to see which performs better. By systematically testing changes, you can make data-driven decisions to enhance the user experience and maximize sales. 

Content in this article:

• What is A/B testing?
• Why use A/B testing in the Checkout flow?
• How to run an A/B test
• Use cases - Learn how to use nShift Checkout Experiments

What is A/B testing?

A/B testing (or split testing) splits your audience into two groups:

• Group A: Sees the original version of your checkout flow (the control).
• Group B: Sees a modified version with one change, like a new design, button color, or payment option.

By measuring the behavior of both groups, you can determine if the change leads to higher conversions.

Why use A/B Testing in the Checkout flow?

The checkout flow is where users decide to complete their purchase, making it critical to your business. Small improvements here can lead to significant revenue growth. A/B testing allows you to:

• Identify and fix pain points.
• Test new ideas without risking your overall sales.
• Understand what works best for your customers.

How to run an A/B test

1. Define Your Goal - Decide what you want to improve. The most common goal in a checkout flow is to increase the conversion rate — the percentage of users who complete their purchase.
      - Pick One Variable to Test Focus on one change at a time for clear results. For example
      - Change pricing
      - Change the order of delivery options
   
   
2. Create Your Variants - It is easy to duplicate your existing Checkout configuration in the admin interface and only change the part you want to test to create a variant for A/B testing.
      - Version A: The current checkout flow (control).
      - Version B: The duplicated version with your change (variation).
   
   
3. Set Up Your Test - With nShift Checkout experiments you can choose exactly how you want to split the traffic between the Checkout configurations you want to compare. You can split the traffic percentage-wise or set up specific conditions, e.g. send a share of traffic from Sweden to a specific version. 
   
   
4. Run the Test - Let the test run for a sufficient amount of time to gather meaningful data. The duration depends on your traffic volume, but a typical test might run for 1–2 weeks.
   
   
5. Analyze Results - Download the metrics file and compare conversion rates between Version A and Version B. If the new version shows a statistically significant improvement, you have a winner and can roll out the successful variant to all users.

Use cases - Learn how to create nShift Checkout experiments

You always start by creating the variants you want to test as separate Checkout configurations under Configurations and then set up the test under Experiments to control the traffic share and duration.

The following use cases explain step-by-step how to set up different tests using nShift Checkout Experiments:

Use Case 1:

Testing reordering delivery options This use case will walk you through an experiment designed to investigate how the sequence of delivery options impacts cart conversion rates. Go to the use case →

Use Case 2:

Use Case 3:

Testing delivery fees below the free shipping threshold Many online stores set a free shipping threshold, but many orders fall below it. Understanding how delivery fees affect cart conversion rates for these customers is crucial and obvious to investigate in an A/B test. Go to the use case →

Use Case 4:

Testing a different checkout configuration for Swedish customers Want to target a specific customer segment? This use case shows how to set up an experiment using conditions to manage traffic from specific markets. Go to the use case →