Patents by Inventor Heather Alice Cobb

Heather Alice Cobb has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Generating recommendations to maximize loyalty earnings
    Patent number: 10867317
    Abstract: The disclosure facilitates loyalty earnings by generating purchase recommendations. Loyalty data is collected from a loyalty program data store. The loyalty data is associated with a loyalty profile of a user. Account data is collected from an account data store. The account data is associated with an account of the user that is linked to the loyalty profile of the user. Transaction data is collected from a transaction data store. The transaction data is associated with the account of the user. User recommendations are generated for prioritizing loyalty earnings on the loyalty profile based on the loyalty data, account data, and transaction data. After the recommendations are generated, the recommendations are caused to be displayed on a user interface associated with a computing device of the user. Combining the three types of collected data to generate the recommendations results in accurate recommendations that are tailored to the user to increase loyalty earnings.
    Type: Grant
    Filed: December 22, 2017
    Date of Patent: December 15, 2020
    Assignee: MASTERCARD INTERNATIONAL INCORPORATED
    Inventors: Anouska Ladds, Heather Alice Cobb, Simon Forbes, Piero Macari
  • GENERATING RECOMMENDATIONS TO MAXIMIZE LOYALTY EARNINGS
    Publication number: 20190197575
    Abstract: The disclosure facilitates loyalty earnings by generating purchase recommendations. Loyalty data is collected from a loyalty program data store. The loyalty data is associated with a loyalty profile of a user. Account data is collected from an account data store. The account data is associated with an account of the user that is linked to the loyalty profile of the user. Transaction data is collected from a transaction data store. The transaction data is associated with the account of the user. User recommendations are generated for prioritizing loyalty earnings on the loyalty profile based on the loyalty data, account data, and transaction data. After the recommendations are generated, the recommendations are caused to be displayed on a user interface associated with a computing device of the user. Combining the three types of collected data to generate the recommendations results in accurate recommendations that are tailored to the user to increase loyalty earnings.
    Type: Application
    Filed: December 22, 2017
    Publication date: June 27, 2019
    Inventors: Anouska Ladds, Heather Alice Cobb, Simon Forbes, Piero Macari