<aside> 💡 A/B testing is essential for product development. It allows developers to test different product variations with real users to determine which version performs better. This method can be used to improve user engagement, increase revenue, and ultimately drive the success. This document outlines the steps in running an effective A/B test

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A/B Testing Process

1. Define objectives: Start by defining clear objectives for the A/B test. What exactly do you hope to achieve through this test? Some examples of objectives might include increasing user engagement, improving retention rates, or increasing revenue.
2. Formulate hypotheses: Next, formulate hypotheses about what changes might help you achieve your objectives. These hypotheses will be the basis for your A/B test variations. Some examples of hypotheses might include changing the game mechanics, adjusting the difficulty level, or modifying the user interface.
3. Establish metrics: Identify metrics that will be used to evaluate the success of the A/B test. These metrics should be closely tied to the objectives defined in step 1. For example, if the objective is to increase user engagement, then metrics such as time spent playing the game or number of sessions per user might be appropriate.
4. Design variations: Using the hypotheses developed in step 2, design game variations that can be tested against the original version. For example, if the hypothesis is that modifying the user interface will increase engagement, then two game variations could be created: one with the current interface and one with a modified interface.
5. Develop a testing plan: Determine how the A/B test will be conducted. This includes selecting the audience, the sample size, determining the test duration, and deciding how the variations will be presented to users.
6. Execute test: Launch the A/B test and begin collecting data. Monitor the test closely to ensure that it is running smoothly, and be prepared to make adjustments if necessary.
7. Analyze results: Once the test is complete, analyze the data collected to determine which variation performed better. Use the metrics established in step 3 to evaluate the success of each variation.
8. Draw conclusions: Based on the results of the A/B test, draw conclusions about which changes should be implemented in the game. If a variation performed significantly better than the original, then consider implementing those changes in the game. If the results are inconclusive, then consider conducting further tests to gather more data. Keep an eye on statistical significance.
9. Implement changes: Finally, implement/ roll out the changes identified in step 8. Be sure to monitor the game closely after implementing changes to evaluate their impact on user engagement, retention, and revenue.

Tools

Documentation

To document and A/B test, use the Confluence template

Monitoring

A/B testing will be developed, most probably in Firebase, and results monitoring will be either in Firebase or Looker. Make sure to clarify this process regarding KPIs with the technical lead.

Firebase | Looker