A/B testing of product prices is one of the key tools in the arbitration of traffic on Facebook. This method allows you to determine the optimal price that maximizes profit and increases conversion. In this article, we will look at how to conduct A/B testing of prices for goods in the longrid format and give examples from practice.
What is A/B testing?
A/B testing is a method that allows you to compare two or more versions of the same item, for example, product prices. At the same time, each version represents a hypothesis that needs to be tested. During testing, users are randomly divided into two groups: control and experimental. The control group sees the old version, and the experimental group sees the new one. Then the results are compared and it is determined which version works better.
How to conduct A/B testing of product prices?
Step 1. Define the testing goals
Before starting A/B testing, it is necessary to define the testing goals. For example, you may want to increase conversion, increase the average check, or increase profits. Each goal requires its own approach to testing.
Step 2. Select products for testing
Select the products you want to test. Usually, products that have a high marginality and a large volume of sales are selected.
Step 3. Determine the sample size
The sample size depends on the number of users who will see your test. The larger the sample, the more accurate the results you will get. It is recommended to conduct tests on samples of at least 1000 users.
Step 4. Determine the duration of testing
The duration of testing depends on the sample size and the number of users who will see your test. Tests are usually carried out from 7 to 14 days.
Step 5. Create price options
Create two or more versions of product prices. For example, you can make one version with a price 10% higher, and another one 10% lower.
Step 6. Run the test
Run the test and give it time to collect data. It is important that users are randomly divided into control and experimental groups.
Step 7. Analyze the results
Analyze the test results and determine which version of prices works better. If the results are statistically significant, then you can decide to implement a new price.
Practical examples
Example 1. An electronics company conducted A/B testing of prices for its products. In the control group there were old prices, and in the experimental group there were new ones that were 10% higher. The test results showed that the new prices reduced the conversion rate by 5%, but increased the average receipt by 15%. The company has decided to introduce new prices.
Example 2. An online store conducted A/B testing of prices for its products. In the control group there were old prices, and in the experimental group there were new ones, which were 5% lower. The test results showed that the new prices increased conversion by 10% and increased profit by 20%. The store has decided to introduce new prices.
Conclusion
A/B testing of product prices is an effective tool that allows you to determine the optimal price to maximize profits and increase conversions. When conducting testing, it is necessary to define goals, select products, determine the sample size and duration of testing, create price options, run the test and analyze the results. Practical examples show that properly conducted A/B testing can lead to a significant increase in profits and conversions.
