Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a request for an order comprising one or more items; determining when the order is eligible for batch picking by finding one or more other orders comprising at least one of the one or more items; and when the order is determined to be eligible for batch picking with the one or more other orders: creating one or more clusters by clustering together (1) the at least one of the one or more items of the order and (2) the at least one of the one or more items of the one or more other orders; estimating, for each respective cluster of the one or more clusters, an estimated fulfillment time interval to make ready the order; and assigning each respective cluster of the one or more clusters to at least one respective picker of one or more respective pickers. Other embodiments are disclosed herein.

Abstract: A method being implemented via execution of computing instructions configured to run at one or more processors. The method can include determining a primary store and one or more secondary stores for pickup of an order of a user, based at least in part on a pickup type of the order. The method also can include determining real-time availabilities of first time slots at the primary store and real-time availabilities of second time slots at the one or more secondary stores. The method additionally can include generating a list of available time slots comprising at least a portion of the first time slots at the primary store and at least a portion of the second time slots at the one or more secondary stores, based at least in part on the real-time availabilities of the first time slots at the primary store and the real-time availabilities of the second time slots at the one or more secondary stores.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving, from one or more electronic devices of one or more users, one or more orders for pickup at a location during a first window of time; at a first time during the first window of time, determining when a designated pickup area at the location exceeds a predetermined level of congestion using: (1) continuously received mobile check-ins at the location; and (2) congestion data of the designated pickup area at the location; and when the designated pickup area at the location does not exceed the predetermined level of congestion during the first window of time, as determined at the first time, causing a pickup electronic device of a pickup to display a pickup request at the location to fulfill at least one order of the one or more orders during the first window of time. Other embodiments are disclosed herein.

Abstract: In some examples, a system may include a first computing device communicatively coupled to a second computing device. Additionally, the first computing device is configured to obtain, from the second computing device, check-in data indicating an arrival of the user of the second computing device at a first location, and in response to obtaining the check-in data, determine current wait times. Moreover, the first computing device is configured to determine a first number of customers waiting for service, determine a first number of associates available to assist the first number of customers, and determine an expected wait time for the user operating the second computing device based at least on the current wait times. In some examples, the first number of customers waiting for service, and the first number of associates available. Further, the first computing device is configured to transmit the expected wait time to the second computing device.

Abstract: A system for rush order fulfilment optimization is discussed. The system includes mobile devices that are each associated with a worker and a rush fulfillment engine executed by a computing system which dynamically updates a task queue of each worker upon receipt of a new rush order according to a task completion rate difference between an estimated task completion rate and the current task completion rate of the worker.

Abstract: A system includes one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors to perform: receiving, from a customer device, an online order for a customer, wherein the online order comprises a customer identification for the customer; receiving, from the customer device, a selection of a pick-up time for retrieval at a store; receiving an additional order for the customer; linking the additional order to the online order based on the customer identification; sending instructions to an assembler configured to (1) read identifiers of the online order and the additional order, (2) retrieve the plurality of items and the one or more additional items from a facility, and (3) place the plurality of items and the one or more additional items in a designated location. Other embodiments are disclosed.

Abstract: A system including one or more processors and one or more non-transitory storage media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations including: receiving an order list for delivery at a delivery address; determining an estimated order collection time; continuously monitoring, in real-time, a respective location of each delivery driver of one or more delivery drivers of at least one delivery service by receiving the respective location of each delivery driver of the one or more delivery drivers from a respective delivery driver electronic device of each delivery driver; and instructing a first delivery driver of the one or more delivery drivers to pick up one or more items in the order list and deliver the one or more items to the delivery address. Other embodiments are disclosed herein.

Abstract: A system for rush order fulfilment optimization is discussed. The system includes mobile devices that are each associated with a worker and a rush fulfillment engine executed by a computing system which dynamically updates a task queue of each worker upon receipt of a new rush order according to a task completion rate difference between an estimated task completion rate and the current task completion rate of the worker.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising: initiating a return request for one or more items; display on the first electronic device one or more windows of time for a driver to arrive at an address; receiving a selection of at least one of the one or more windows of time for the driver; assigning the driver to pick up the one or more items from the address; causing a second electronic device of the driver to display the address; and receiving one or more acceptance scans for the one or more items from the second electronic device of the driver. Other embodiments are disclosed.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising: determining, using a predictive analysis, an estimated collection time to collect one or more items of an order; receiving a mobile check-in from an electronic device indicating that a pickup is en-route to pick-up the order from the store; tracking a location of the pickup; periodically determining an estimated travel time for the pickup to travel to the store from the location, as tracked; and transmitting instructions for the one or more employees of the store to begin collecting the one or more items of the order on a store interface Other embodiments are disclosed herein.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a request from a user; determining, using a regression analysis, an estimated order collection time for a collection of the one or more items of the order list by at least one collector; continuously monitoring a respective location of each respective delivery driver; continuously determining a respective estimated order pickup time for each respective delivery driver; and instructing the first delivery driver of the one or more delivery drivers to pick up the one or more items and deliver the one or more items to the delivery address. Other embodiments are disclosed herein.

Abstract: Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of receiving a return request for an item from a customer electronic device of a customer, determining that the return request is available for a pickup return option for (1) pickup, by a driver, of the item at an address associated with the customer and (2) transportation, by the driver, of the item from the address to the store, and, if the customer selects a pickup return option: assigning the driver to pick up the item from the address and transport the item to the store, receiving a return scan for the item from a store electronic device at the store or from a driver electronic device, and initiating a refund to the customer for the item.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: outputting, by a machine-learning model, a probability that a user will re-order two or more items at a present time; determining the two or more items to recommend to the user based on the probability exceeding a predetermined threshold that the user will re-order the two or more items at the present time; sending instructions to display the two or more items to the user, wherein the user interface comprises a single-click option to add to an electronic cart the two or more items; and after receiving the single-click option from the user interface, adding the two or more items to the electronic cart. Other embodiments are disclosed.

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: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform receiving, at the one or more processors, an order from a customer electronic device; determining, using employee device data collected from one or more electronic devices of one or more employees of a store in a predictive analysis, an estimated collection time required for an employee of the one or more employees of the store to collect the one or more items of the order; receiving a check-in from an electronic device indicating that a pickup is en-route to pick-up the order; when the electronic device authorizes location tracking, tracking a location of the pickup after receiving the check-in from the electronic device; periodically determining, at one or more time intervals, an estimated travel time for the pickup to travel to the store from the location, as tracked; and when the estimated collection time is approxima

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: determining a set of items to recommend to a user based on a probability exceeding a predetermined threshold that the user will re-order each item of the set of items at a present time, wherein the probability is determined based at least in part on previous transactions of the user and other users within a first period of time, and wherein the set of items includes at least a predetermined number of items; sending instructions to display the set of items to the user on a user interface, wherein at least a portion of the set of items is shown as selected on the user interface, and the user interface further comprises a single-click option to add to a cart all selected items of the set of items; receiving a selection of the single-click option to add to the cart the all selected items of the set of items; and after receivin

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: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a request for an order comprising one or more items; determining when the order is eligible for batch picking by finding one or more other orders comprising at least one of the one or more items; and when the order is determined to be eligible for batch picking with the one or more other orders: creating one or more clusters by clustering together (1) the at least one of the one or more items of the order and (2) the at least one of the one or more items of the one or more other orders; estimating, for each respective cluster of the one or more clusters, an estimated fulfillment time interval to make ready the order; and assigning each respective cluster of the one or more clusters to at least one respective picker of one or more respective pickers. Other embodiments are disclosed herein.

Abstract: A number of embodiments can include a system. The system can include one or more processors and one or more non-transitory computer-readable storage devices storing computing instructions. The computing instructions can be configured to run on the one or more processors and perform: receiving a request for a picked order that can comprise: a conveyance type; and one or more goods; estimating a fulfillment time interval to make ready the one or more goods of the picked order by: evaluating whether the picked order is able to be batched in a picked order batch; and when the picked order is able to be batched, evaluating the conveyance type to determine a conveyance type average fulfilment time interval; determining, using the fulfillment time interval, as estimated, and the conveyance type average fulfilment time interval, a receivable clock time at which to promise the one or more goods for receipt by a receiver; and communicating the receivable clock time to an electronic device of the receiver.

Abstract: A number of embodiments can include a system. The system can include one or more processors and one or more non-transitory computer-readable storage devices storing computing instructions.