Experiments Overview
Learn about Deepwall experiments
The Experiments Tool in Deepwall helps you to carry out A/B tests to compare performance of different paywalls, and Deepwall provides a powerful optimization tool to maximize your revenue by analyzing app-specific in-app purchase metrics, making accurate lifetime value predictions and offering the most revenue-generating options to each user.
You can perform design experiments to understand your users' reaction to different paywall designs or you can compare the conversion of subscription options with different prices, durations or introductory offers for specific target users using experiments.
You can run multiple experiments for different user groups.
Optimization is an option for all experiments which can be easily enabled/disabled and optimization results are monitored from the Deepwall Console.
If you enable optimization on an experiment, the Deepwall optimization algorithm analyzes app-specific in-app purchase metrics and makes accurate lifetime value predictions to offer the most revenue-generating options to each user.
See the following guide to learn more about how optimization works.
If you disable optimization on an experiment, and it behaves like an A/B test. In this case, you need to monitor experiment results, determine the best performing paywalls and change traffic allocation between paywalls.
See the following guide to learn more about manual traffic allocation.
The first step for starting to use an experiment is to create an experiment, select the paywalls you want to test and your target users for your experiment.
See the following guide to learn about experiment creation.
After you have started an experiment, you can see the experiment results using the experiment report.
See the following guide to learn more about experiment reports.
You can edit your experiments and make allowed changes on them, and you can stop a running experiment and/or archive forever.
See the following guide to learn more about managing experiments.
Last modified 2yr ago