MyTracker e-commerce users can now forecast universal revenue over a period of one to six months. A new free predictive analytics tool allows you to build user-level forecast for Android and iOS applications, says AppTractor.
The solution allows owners of mobile e-commerce applications to predict universal income – financial receipts that cannot be transferred to the service in a standard way (advertising revenue, in-app payments or subscription write-offs). Such income includes offline payments or purchases made using electronic payment services.
The predictive model allows you to forecast revenue at the user level, not the device level. This approach makes it possible to predict universal income, even if the customer is using different devices.
The solution, based on machine learning algorithms, predicts store profits over a period of one to six months. According to the platform, the forecast accuracy is 88%. The tool also allows you to segment your audience by income level and assess the impact of different communication scenarios (for example, pop-ups with great offers) on the change in revenue indicators. The new tool is based on the S2S API, notes NIXSolutions. With its help, project events (for example, user authorization, payments, and others) are transmitted through requests to the API. The uploaded data is included in statistics that are available in the MyTracker interface.