case in point Title: Leveraging mobile app data for gender prediction to ensure targeted marketing Industry: Telecom Country: Global
Challenge • • • •
The client is a pioneer in measurement of mobile subscriber behavior The metering application installed on smart devices captures behavior of the device accurately The client wanted to understand the gender of the subscribers based on installed Apps This information was to be used by advertisers in order to ensure focused and targeted marketing.
Approach • Initial data provided by the client was a set of user IDs along with the application names • Data cleansing and transformations were performed in order to ensure data can be fed to a supervised learning algorithm. • The data provided was highly imbalanced and skewed towards males as it was the dominant class to be predicted. • Applied weighted measures to give more importance to the minority class • Support Vector Machines Learning Algorithm was applied to predict gender of the subscribers
Result • Achieved accuracy close to 80% for both classes of interest • Developed an integrated solution with a GUI to enable real time results to be obtained based on real time data feeds to the learning algorithm blueoceanmi.com | 1
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