Telecommunications

Telecommunications is big business. Ranging from the saturated markets of North America and Western Europe to emerging economies such as India and China, a telephone is the primary mode of communication. Associated with this is a large pool of telco data containing individual calling logs (including location, duration), messaging habits, calling plans, phone bills and other CRM modalities. Mobile units number in the billions, and a subset of these are smartphones, which are a lot more than a mere device used to talk and send messages. Smartphones present an opportunity for the realization of a unique data pool that marries usual telco data to app habits of the subscriber. Here are some of the ways this data may be monetized through big data insights.

  • Usage insights. Locations of subscribers and the frequency with which they use an app from third party vendors is data that resides with telcos. Identifying correlations between location data and frequency of app usage is an insight that may be monetized by the telco as it is potentially valuable to vendors interested in location specific marketing of their products.
  • Resource provisioning. An analysis of call locations and time stamps, which is based on data that telcos collect, is again potentially valuable to government agencies or NGOs interested in mapping the seasonal movement of populations and catering to the requisite infrastructural needs.

Apart from monetizing the already available data through the use of big data techniques, telcos today must exploit data to successfully compete for market share amidst growing saturation. Vital to this is to not only retain the existing customers but also to keep adding new ones with minimal cost/effort. In order to help telcos achieve this goal, we propose customer behavior and tendencies be thoroughly studied and understood, based upon which customer engagement and experience customized. Some of our key offerings in this regard are:

  • Augmented customer segmentation. Traditionally customer segmentation has been used successfully to sift through data to categorize customers ranging from the most valuable ones to the ones most likely to leave. We have introduced elements of behavioral neuroscience to compartmentalize customers into more nuanced categories, thus improving greatly upon traditional segmentation analysis.
  • Churn analysis. With mobile number portability being available in many countries, it becomes imperative for telcos to identify why and at what rate are they losing customers to their competitors and what could be done to not only prevent it but to reverse it. In addition to using traditional churn analytics techniques, we use proprietary simulation methods to estimate the efficacy of potential corrective measures even before their implementation.