Abstract: An example server includes: a memory storing an account database for a centralized reward hub; a processor interconnected with the memory, the processor configured to: receive purchase data for a purchase by a customer, the purchase data including a customer identifier; determine whether account database includes an existing entry corresponding to the customer identifier; when the account database does not include an existing entry corresponding to the customer identifier, create a new entry for the customer identifier; send the customer a login link for the centralized reward hub based on the new entry or the existing entry corresponding to the customer identifier.

Abstract: An example server includes: a memory storing an account database for a centralized reward hub; a processor interconnected with the memory, the processor configured to: provide a centralized reward hub interface for display at a client device associated with a client account, the centralized reward hub providing multiple merchants for selection; receive a selection of a merchant from the client device; redirect the client device to a merchant site for the selected merchant; provide, to a discount module integrated with the merchant site, a point balance for a client account; receive, from the discount module, an updated point balance for the client account after application of a portion of the point balance to apply a discount at the merchant site; and update the point balance for the client account in the account database.

Abstract: An example e-commerce system includes an e-commerce platform to: receive a purchase order from a guest user, the purchase order including a guest user identifier representing a means of communication for the guest user; match the guest user identifier to a customer identifier; send a confirmation of the purchase order to the guest user via the means of communication for the guest user; and a loyalty rewards system to communicate with the e-commerce platform, the loyalty rewards system to: associate the customer identifier with a guest user account of the loyalty rewards system; and track reward points from the purchase order in association with the guest user account.

Abstract: Aspects include a system and method of automatic data segmentation to optimize a client's collection efforts against individuals serviced by the client. At least accounts receivables data, historical payment data, and credit related data associated with an individual may be provided to a model as input data to predict a recovery value for the individual. The recovery value may be a weighted average of a unit yield and recovery rate. Based on the predicted recovery value and client-provided segmentation boundaries that define segments as a range of recovery values, the individual may be assigned to a segment. The segment may inform the client of a particular collection strategy for the individual to optimize collection efforts. Additionally, recovery values for the individuals serviced by the client may be provided to a comparison system and utilized to directly compare collection efforts across a plurality of clients nationally and/or demographically.