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How to Interpret Your Price Test Results

Once your price test is complete, you can access and interpret the results through the Price Test Results page. This guide walks you through each section of the page, helping you understand the key metrics and statistical data.

Step 1: Accessing the Price Test Result Page​

  1. Navigate to the Price Test tab in your left APPs panel.
  2. In the list of tests, find the specific test you want to review.
  3. In the Analysis column of the test, click the Processing or Completed button to access the Price Test Result page.

Step 2: Understanding the Results​

Once you're on the Price Test Result page, you’ll find three main sections: the AB Test Setting ,the AB Test Result and the Conversion Metrics.

The main interpretion part is looking at AB Test Result and Conversion Metrics.

1. AB Test Result​

Below the Data Panel, you'll find the results of the Chi-Square Independence Test. This statistical test is used to determine whether the pricing changes made a significant impact on the conversion rate. The results are broken down into the following:

  • Chi-Square Value: This number indicates the magnitude of difference between the observed and expected conversion rates across the different price points.

  • p-value: The p-value tells you whether the observed differences are statistically significant. If the p-value is below 0.05, the results are considered significant, meaning the pricing changes had a measurable effect.

  • Result: This section will state whether the test outcome was Significant or Not Significant based on the p-value.

    • Significant: The pricing variation has a statistically meaningful impact.
    • Not Significant: No strong evidence was found that the pricing variation affected the conversion rate.

2. Conversion Metrics​

In this section, you will find various performance metrics that help further break down the test’s effectiveness:

  • Conversion Rate: The percentage of customers who completed the desired action (e.g., made a purchase) under each price variation.
  • Lift: The percentage increase or decrease in conversion rate compared to the baseline price.
  • Vaiance:

When you read your price test result, you need to combine the AB Test Result and Conversion Metrics. If your price test result is Significant, ensure that the variant group performed better than the control group, which is the desired outcome. If the result is significant but the variant group performed worse than the control group, you should reconsider changing your pricing strategy. If the result is Not Significant, it means your pricing variation didn't perform differently than your original price setting.

Conclusion​

Understanding your price test results is crucial for making informed decisions. If your result is significant, it means the price change likely had an impact, while non-significant results suggest that the price change didn't make a large enough difference to be statistically meaningful.

If you have any questions, feel free to reach out to our statistics experts for assistance. You can check our help-and-support page.