A Fortune 500 mobile phone company conducted in-depth analysis of global customers for its mobile phone products.
The data come from the daily behavior data of users' mobile phones and the data provided by the app / mobile phone manufacturer. Models are created through inductive modeling based on users' usage behavior patterns and pure machine learning based on user attribute classification. In addition to all-around portraying of users, in-depth analysis of specific population segments is carried out to predict users' follow-up behaviors and make pre-judgment of current users' change of mobile phones.
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