US 11,941,655 B1
Machine learning technologies for identifying category purchases and generating digital product offers
Anthony David Smaniotto, Portage, IN (US); and Ankit Patel, Union City, NJ (US)
Assigned to FETCH REWARDS, INC., Chicago, IL (US)
Filed by FETCH REWARDS, INC., Chicago, IL (US)
Filed on Apr. 10, 2023, as Appl. No. 18/132,735.
Int. Cl. G06Q 30/02 (2023.01); G06Q 30/0202 (2023.01); G06Q 30/0207 (2023.01); G06Q 30/0241 (2023.01)
CPC G06Q 30/0224 (2013.01) [G06Q 30/0202 (2013.01); G06Q 30/0222 (2013.01); G06Q 30/0277 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A computer-implemented method of using machine learning to generate digital offers for products, the computer-implemented method comprising:
training, by at least one processor, a first machine learning model using a first set of training data identifying at least (i) a set of product catalogs, and (ii) a categorization of a purchased set of products within the set of product catalogs;
analyzing, by the at least one processor using the first machine learning model, product purchase data and a product catalog associated with an entity to determine a set of user affinity profiles respectively associated with a first set of individuals, wherein the product purchase data indicates a set of products purchased by the first set of individuals;
training, by at least one processor, a second machine learning model using a second set of training data identifying (i) an initial set of products purchased by a set of individuals, (ii) a set of offers provided to the set of individuals after the initial set of products is purchased by the set of individuals, and (iii) a subsequent set of products purchased by at least a portion of the set of individuals after purchase of the initial set of products and after the set of offers is provided to the set of individuals;
accessing, by at least one processor, a set of data identifying at least one product purchased by an individual of the first set of individuals, wherein the at least one product is associated with the entity;
analyzing, by the at least one processor using the second machine learning model, the set of data and a user affinity profile of the set of user affinity profiles associated with the individual to determine a digital offer for an additional product associated with the entity or an additional entity;
availing, by the at least one processor, the digital offer for review by the individual via an electronic device;
accessing, by at least one processor, an additional set of data indicating whether the additional product was purchased by the individual; and
updating, by the at least one processor, the second machine learning model using the additional set of data to enable more accurate digital offer determinations in subsequent analyses.