Lifestyle Segmentation from Carrier Location and Call Data - Part 2

Why can't my mobile device's map-based search engine show me restaurant recommendations tailored to my personality? Right now, our mobile devices and the telecommunication infrastructure have enough data to figure out what our preferences and lifestyle are like. The hurdle is providing a technology that can seamlessly integrate call and location data over time to accurately identify what segment a user belongs to - without storing sensitive data that may raise privacy concerns.

Is someone young and edgy or are they an elderly homebody? Using Macrosense, our latest technology platform, it is possible to convert this massive amount of data into a user's lifestyle descriptor transparently and on-the-fly. With various statistics, machine learning, and prediction algorithms, social clusters (a.k.a lifestyle tribes) can be determined.

The data can also be used to answer business relevant questions such as "is this person likely to respond to upsell promotion X?", "are they likely to churn off the network?", "are they a business traveler, and are they on a business trip right now? are they lost or in a familiar place?", "will they be interested in a music event?", and so on by using training data from existing customer interactions.