The Download and Revenue estimates that we provide rely on proprietary Machine Learning models. 

Based on the data we already have ("real data"), we are able to build a model that learns from the existing data in order to make predictions ("estimations").

The existing data comes from over 5 years collection of iTunes Connect and Play Store Console synced to the platform. Each time an AppTweak user integrate their console to AppTweak, ou system would collect, encrypt and ingest all data. 

IMPORTANT: The data is anonymised, encrypted, safely stored and only used for statistical purposes. The data is NOT shared to any third party. 

Based on the number of app downloads & revenues correlated with the app rankings, we are able to determine a predictive curve of downloads & revenue estimates.

As an example, the graph below represents both our “real data” (blue dots) vs “estimations” (red curve) for apps in “All Categories” in the United States.

As you can see, the X axis is the spread of app rankings (from 1 to 1500) and the Y axis shows the amount of downloads (from 0 to 60,000).

Each blue point is a “real” and valid data point of an existing app, currently ranked in the U.S. in the “All Categories” chart. Each blue dot therefore gives us the amount of daily downloads and app ranking of each app.

As you can see, higher the ranking, higher the number of daily downloads. Inversely, lower the ranking, lower the amount of downloads.

All these blue dots are shaping a trending curve that we tried to standardize into a more general predictive curve (red curve).

Indeed, thanks to the amount of information we have, we are now able to estimate the number of downloads for a given app in a given category for a given region, relying on our predictive curve.

Did this answer your question?