Abstract: A method including receiving driver tracking information from a platform of a delivery driver network of multiple delivery driver networks. The method further can include determining a platform-dependent format of the driver tracking information; and when the platform-dependent format is different from a standard format, converting the driver tracking information from the platform-dependent format into uniform tracking information in the standard forma. Moreover, the method can include determining an estimated time of arrival; and verifying a reliability of an estimated delivery time of the driver tracking information. The method further can include when the reliability of the estimated delivery time is verified, incorporating the estimated delivery time into the uniform tracking information; and when the reliability of the estimated delivery time is not verified, incorporating the estimated time of arrival into the uniform tracking information as the estimated delivery time.

Abstract: A system can comprise one or more processors; and one or more non-transitory computer-readable media storing computing instructions configured to run on the one more processors and perform a method for providing uniform tracking information, in a standard format, based on tracking information provided by multiple delivery driver networks, each having different hardware and software platforms. The method in this embodiment can comprise: receiving a user tracking request from a customer; receiving driver tracking information from the platform of the delivery driver network of the driver selected for the grocery delivery; converting the driver tracking information into uniform tracking information in a standard format; and providing the uniform tracking information, with an accurate estimated delivery time, to be rendered on a user interface of a user device of the customer.

Abstract: A method for automatically processing an online return request including receiving a refund request from an electronic device of a user for returning an item previously purchased as part of a store. The method further can include processing a refund solution based on the refund request. The method can process the refund solution by: (a) determining a returnable status of the item; (b) when the returnable status for the item is negative, returning a rejection decision to the electronic device; and/or (c) when the returnable status for the item is positive: (i) generating a cost-benefit analysis result; (ii) when the cost-benefit analysis result is negative, processing the refund request by returning a return amount to the user for the item; and/or (iii) when the cost-benefit analysis result is positive, providing an authorization for a return of the item in order for the user to receive the return amount. Other embodiments are disclosed.

Abstract: A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform a method for automatically processing an online return request. The method performed by the system can receive a refund request from a user computer used by a customer of a grocery store, the refund request for returning a grocery item (a) previously purchased as part of a transaction of the grocery store and (b) paid for by a payment method via the transaction; and process a refund solution based on the transaction and the grocery item. In this system, the method can process the refund solution by determining a returnable status of the grocery item according to one or more returnability rules dynamically generated by a machine learning model. If the returnable status of the grocery item is negative, the method performed by this system can deny the return request.

Abstract: A system can comprise one or more processors; and one or more non-transitory computer-readable media storing computing instructions configured to run on the one more processors and perform a method for providing uniform tracking information, in a standard format, based on tracking information provided by multiple delivery driver networks, each having different hardware and software platforms. The method in this embodiment can comprise: receiving a user tracking request from a customer; receiving driver tracking information from the platform of the delivery driver network of the driver selected for the grocery delivery; converting the driver tracking information into uniform tracking information in a standard format; and providing the uniform tracking information, with an accurate estimated delivery time, to be rendered on a user interface of a user device of the customer.

Abstract: A system can comprise one or more processors; and one or more non-transitory computer-readable media storing computing instructions. In this embodiment, the computing instructions can be configured to run on the one more processors and perform a method for creating and closing a customer feedback loop, by using customer feedback to adjust future driver dispatching decisions. In this embodiment, the method can comprise dispatching a driver for a delivery of an order at a grocery store to a customer. In this embodiment, the driver can be selected from a delivery driver network of multiple delivery driver networks based on one or more driver selection factors associated with the driver and retrieved from a database; and the multiple delivery driver networks can comprise one or more on-demand delivery service providers and one or more scheduled omnichannel delivery service providers.

Abstract: A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform a method for automatically processing an online return request. The method performed by the system can receive a refund request from a user computer used by a customer of a grocery store, the refund request for returning a grocery item (a) previously purchased as part of a transaction of the grocery store and (b) paid for by a payment method via the transaction; and process a refund solution based on the transaction and the grocery item. In this system, the method can process the refund solution by determining a returnable status of the grocery item according to one or more returnability rules dynamically generated by a machine learning model. If the returnable status of the grocery item is negative, the method performed by this system can deny the return request.