| CPC G06Q 30/0215 (2013.01) [G06Q 10/1095 (2013.01); G06Q 20/102 (2013.01)] | 20 Claims |
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1. A system comprising:
one or more processors; and
one or more computer-readable media storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
storing, in a datastore associated a service provider, buyer profiles associated with a plurality of buyers and seller profiles of a plurality of sellers, wherein individual profiles of the buyer profiles and the seller profiles include historical interaction data corresponding to one or more interactions of the respective buyers and sellers with one or more services of a plurality of services offered by the service provider, and wherein the historical interaction data includes historical transaction data corresponding to one or more historical transactions of the respective buyers and sellers;
training, by one or more server computing devices of the service provider and using training data and a machine learning mechanism, a machine learning model configured to output a plurality of available tender options for a particular transaction, wherein the training data includes at least a portion of the historical interaction data;
receiving, by the one or more server computing devices of the service provider and from a seller computing device operable by a seller of the plurality of sellers, first transaction data associated with a transaction between the seller and a buyer of the plurality of buyers, the first transaction data including at least one item selected for purchase by the buyer, a cost associated with the at least one item, and an indication of a seller profile associated with the seller;
generating, by the one or more server computing devices, in near real time, a graphical user interface (GUI) comprising information associated with the at least one item and the cost associated with the at least one item;
causing presentation, by the one or more server computing devices, of the GUI on the seller computing device or on a buyer computing device operable by the buyer;
receiving, by the one or more server computing devices of the service provider and from the seller computing device, second transaction data, the second transaction data including an indication of a buyer profile associated with the buyer;
responsive at least in part to receiving the second transaction data and based at least in part on the second transaction data, determining, by the one or more server computing devices and by leveraging machine learning algorithms combined with the second transaction data, a plurality of tender options personalized to the buyer for tendering payment to the seller for at least a portion of a transaction amount, wherein the plurality of tender options are based at least in part on (i) the machine learning model, (ii) one or more of the buyer profile, the seller profile, or the first transaction data, and (iii) one or more services of the service provider available to the buyer based at least in part on the buyer profile;
reconfiguring, by the one or more server computing devices, in near real time, the GUI to include a plurality of actuation mechanisms associated with respective tender options of the plurality of tender options; and
causing presentation, by the one or more server computing devices, of the reconfigured GUI on the seller computing device or on the buyer computing device operable by the buyer.
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