Network traffic and accurate location data draw significant interest from network operators and many other industries for marketing and service improvement potentials. At the same time, such data draw significant scrutiny due to privacy concerns. This project attempts to address privacy concerns by building a machine learning model based on truly anonymized data where all privacy-related information is peeled off. The project solution helps improve consumer confidence by eliminating privacy exposure while allowing the sponsor to save significant resources by simplifying the data wrangling process from complex and disintegrated data sources.