INrange Analytics is a location-based predictive analytics solution. It works with existing communications service provider (CSP) data, analyzing subscribers’ behaviors with TEOCO’s Location Analytics and Customer Analytics big data platforms to predict subscribers’ future locations to more accurately target advertising campaigns.
By forecasting subscribers’ future whereabouts and delivering relevant messaging based on that information, INrange Analytics allows advertisers to communicate directly to consumers while still in the decision-making process, rather than at the time of purchase when it is too late. Sending timely, relevant and location-specific messaging will allow advertisers to greatly increase their response rates.
Adding intelligence to mobile ads allows CSPs to capture more of the burgeoning mobile advertising market currently dominated by over-the-top players with an enhanced offering that will provide better return on investment (ROI) to marketers.
INrange provides a multi-level opt-in mechanism directly controlled by subscribers while respecting customer privacy and mobile marketing guidelines. Providing timely, relevant messaging to subscribers improves the end-user experience and creates a means of differentiating a CSP’s service from the competition.
- New Revenue Streams: Communications service providers (CSPs) gain a competitive edge in the mobile advertising market with a solution that is more attractive to both advertisers and subscribers.
- Better Business Intelligence: Enhanced subscriber data can be used internally by CSPs or by external partners. INrange is able to segment subscribers by demographic type, historical proximity to specific locations, time of day, and predicted future locations.
- Better End-user Experience: Delivering timely, relevant, location-specific advertising to subscribers enhances the value of the CSP service and helps to differentiate from the competition by relevance or price.
- Passively gathers Call Detail Records (CDRs and IPDRs) and Radio Access Network (RAN) data that record subscriber locations.
- Refines location with a series of geo-location algorithms, clusters the data by time of day and day of week and assigns a predictive score for where a mobile device will be at a given day of the month and time.
- Targeting criteria can be used to deliver advertising, promotions, coupons, etc., including: proximity to target locations; time of day, day of week; type of device; type of subscriber location (e.g., home, work); subscriber characteristics (e.g., night worker, long commute, frequent traveler, stay-at-home); and other subscriber characteristics (billing, credit history, demographic).