US 12,217,284 B2
Matching promotions to telecom user preferences using artificial intelligence
Jignesh K Karia, Thane (IN); Mukundan Sundararajan, Bangalore (IN); Pankaj Satyanarayan Dayama, Bangalore (IN); Shilpa Shetty, Bangalore (IN); Neha Shah, Kolkata (IN); and Vishal Awal, Mumbai (IN)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Oct. 20, 2021, as Appl. No. 17/506,166.
Prior Publication US 2023/0325883 A1, Oct. 12, 2023
Int. Cl. G06Q 30/0251 (2023.01); G06Q 30/0241 (2023.01); G06Q 30/08 (2012.01)
CPC G06Q 30/0269 (2013.01) [G06Q 30/0261 (2013.01); G06Q 30/0276 (2013.01); G06Q 30/08 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A computer-implemented method for making promotional offers to telecom subscribers in roaming network areas comprising:
recording promotional preferences of subscribers for receiving promotional calls, the promotional preferences being directly recorded from subscribers by their local telecom provider by contract with the local telecom provider, the promotional preferences including at least one type of promotion the subscriber would like to receive, and at least one type of promotion that subscriber would not like to receive;
enhancing a reach of local promotional service providers to telecom subscribers in roaming network areas based on the recorded promotional preferences of subscribers through a cloud based system by:
forwarding subscriber information from a local network telecom service provider to a roaming network service provider;
measuring with the roaming network telecom service provider the subscribers that are present within a roaming network geography;
detecting a duration of the subscriber within the roaming network geography based on communicated updates by a remote telecom service provider to the cloud based system;
ranking subscribers in the roaming network geography by their duration within the roaming network geography, the subscribers ranked using an optimization model to maximize revenue based on number of telecom messages received by a subscriber, the number of promotions meeting promotional preferences of the subscriber, and by whether the duration of the subscriber is for a subscriber newly entering the roaming network geography;
generating promotion pools for the subscribers within the roaming network based on their preferences; and
matching promotional offers to the subscribers in the promotional pools, through an auction for organizations to submit bids for the promotional offers that is saved to a database based on a number of promotional calls made to the subscribers, using the ranking of subscribers and the promotional preferences.