The churn measures an app loss in payments, launches, and other activity your audience for a given period. Users can stop using an app as early as the next day or a month after installation.
Predictions allow you to analyze audience engagement and prevent user drop-off. With forecast you can:
myTracker makes a forecast using a machine learning model. This model analyzes captured app data: installs, launches, payments, sessions, and can make a forecast one day after a user installed your app.
Churn can be forecast for periods of 7, 14, 21, or 28 days after app installation. Predictive churn doesn't mean the app uninstall, it is a forecast about a user will not be active during a specified inactivity window ? following a selected forecast day.
For instance, 20 users install your app on 2021.01.01. Churn Prediction LT 7d = 50% would mean 10 users will not be active for the period from 2021.01.08 till 2021.02.07 (during 30 days of inactivity window). Knowing the forecast, you can send push notifications to those 10 users.
Churn prediction LT metrics show the percentage of devices on which users installed your app during the reporting period and is forecast to be inactive after the selected period (7d, 14d, 21d, 28d) based on the inactivity window settings.
You can get reports with Churn forecast using Export API