Assess App Updates

Compare the behavior of paying users on different application versions to optimize it and drive better financial performance for your business.

Analyze the activity of users on different versions of your applications

At the beginning of development, it is crucial to develop application updates to make users more involved in the project and encourage them to purchase more.

With our solution, you can easily compare how paying users behave on different versions of the application. Of course, it is important to always keep in mind that you need to compare cohorts of users of similar quality. Better is to conduct a/b test for different build versions, or at least filter countries and organic users.

The first tool to check the quality of an update is the marketing report. You can select the App build version breakdown and view graphs for different metrics across different app versions.

Marketing Report Metrics

Then you can switch to the LTV calculator and see what LTV looks like to monitor what the predictive model shows if you have enough data for such a comparison.

LTV Calculator Curves

After choosing the app build version and rolling it out to all users, it is important to quickly update the auto-learn predictive model using new data. In order to do this, you can reduce the auto-learning period of the model to last 30 days.

If your project is live for a long time and there are no frequent changes in the monetization, especially at the beginning of your user’s journey in the application, a suitable option for you would be the auto-learn predictive model for the last 3-6 months or a fixed timeframe.

When working with forecasts, it is important to keep in mind that the revenue prediction is based on actual data. None of the predictive models can take into account factors such as your future app content, monetization events, live ops, or support quality. Your team should know how to manage and operate a product in the long run to achieve your payback period.