US 11,710,140 B1
Systems and methods for tailoring marketing
Lee Chau, New York, NY (US); Tirthankar Choudhuri, Gurgaon (IN); Ajay Choudhary, Gurgaon (IN); Vikas Grover, Ambala Cantt (IN); Mohd Arshad Naeem, Gurgaon (IN); Subhajit Sanyal, Bangalore (IN); Dawn Thomas, Kew Gardens, NY (US); Amit Jagdish Agarwal, Bangalore (IN); Pranav Mehta, Gurgaon (IN); Kamal Gupta, Bangalore (IN); Subhra Purkayastha, Gurgaon (IN); and Prakruthi Prabhakar, Cuddalore (IN)
Assigned to American Express Travel Related Services Company, Inc., New York, NY (US)
Filed by AMERICAN EXPRESS TRAVEL RELATED SERVICES COMPANY, INC., New York, NY (US)
Filed on Jan. 21, 2020, as Appl. No. 16/748,451.
Application 16/748,451 is a continuation of application No. 14/961,614, filed on Dec. 7, 2015.
Claims priority of provisional application 62/205,580, filed on Aug. 14, 2015.
Int. Cl. G06Q 30/00 (2023.01); G06Q 30/0204 (2023.01); G06Q 30/0251 (2023.01); G06Q 30/0601 (2023.01)
CPC G06Q 30/0204 (2013.01) [G06Q 30/0254 (2013.01); G06Q 30/0631 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
receiving, by a computing device, a first set of data from a first source and a second set of data from a second source, the first set of data comprising a plurality of items available from the first source for a first set of users and the second set of data comprising transaction purchase data for a second set of users that have transaction accounts with a transaction account issuer;
receiving, by the computing device, global positioning location data for a user from a global positioning system (GPS) user device, wherein the first set of users comprises the user;
building, by the computing device, a predictive data model using a transfer function that determines a propensity score for the user from only behavior data that is not attributed to the user, the behavior data comprising the second set of data, wherein the user is absent from the second set of users and the propensity score represents a likelihood that the user will act on a recommendation or an offer for one or more of the plurality of items from the first source;
receiving, by the computing device, a third set of data from a third source, the third set of data comprising social media channel data for a third set of users, wherein the third set of users are absent from the second set of users;
updating, by the computing device, the transfer function to determine the propensity score for the user based at least in part on the third set of data;
generating, with the predictive data model using the transfer function by the computing device, the propensity score for the recommendation or the offer for the user based at least in part on the global position location data for the GPS user device; and
providing, over a computing network, a graphical user interface to the user having the recommendation or the offer in response to the propensity score meeting or exceeding a predefined threshold, wherein a positioning of the recommendation or the offer in the graphical user interface with respect to another recommendation or another offer in the graphical user interface is determined based on social media channel data of the user.