An order processing system and method includes sending, to a backend, an order queue comprising at least one order identifying a delivery object associated with a client and comprising at least one ordered item, receiving, from the backend, an updated preparing status of each target ordered item in the order queue, updating the order queue based on the preparing status of each target ordered item, determining the preparing status of each target ordered item in the target order based on the updated order queue, and sending the preparing status of each ordered item in the order to the client associated with the delivery object of the order.

Methods, devices, and systems for a tag for order fulfillment are described herein. One or more embodiments include a number of tags each associated with a corresponding inventory bin of a warehouse, each tag configured to broadcast unique identification information, and a mobile device configured to receive, from a database, order information including identification information of one of the number of tags and a type and a quantity of an item of an inventory bin of the warehouse corresponding to the tag, and scan for identification information of the tag.

A system includes location indicators, a central computing system, and a mobile scanning device. The location indicators transmit location signals and are arranged in a store that includes stocked items. The central computing system stores an item association table that maps location values to the stocked items. The location values indicate locations of the stocked items in the store. The mobile scanning device receives ordered items from the central computing system, detects location signal(s), and determines a first location value based on the detected location signal(s). The mobile scanning device arranges the ordered items on a display based on the first location value, scans a first ordered item, and transmits data to the central computing system indicating that the first ordered item is associated with the first location value. The central computing system updates the item association table based on the data.

Systems and methods for a history walker interface to a time-based data structure are disclosed. A time-based data structure may contain information about updates to a set of records that change periodically over time. For example, a set of records that record state transitions of a task item as the task item progresses through its life cycle. An example task item may be represented by a change request or incident report in a help desk software application. The task item begins with an “open” state and may transition through any number of states (e.g., assigned, on-hold, test, customer response requested, etc.) on its way to ultimately being “closed” as completed. A history walker interface may assist application developers when creating applications to indicate how the task item transitioned through its different states throughout its lifecycle.

In embodiments, methods and systems for order management and processing based on a distributed commerce platform are provided. A distributed commerce platform supports end-to-end integrated product publication, order-management and payment services. In particular, the distributed commerce platform supports components based on Application Programming Interfaces (API) that standardize the implementation of a distributed commerce solution or configuration of off-site buying experiences. Using the distributed commerce platform, merchants can concurrently offer, sell, and process orders for products through a plurality of different affiliate channels. The distributed commerce platform can also be implemented as a federated portal from which a merchant can identify affiliate channels to publish product objects, access the plurality of affiliate channels and define configurations for processing objects of the merchant's distributed commerce solution. The configurations can be accessed during a purchase flow such that orders from a channel are processed based on the specific attributes identified in the configurations.

Methods and apparatus to translate and manage product data are disclosed. A disclosed example apparatus for translating and managing product data pertaining to a plurality of tenants includes at least one memory, instructions, and at least one processor to execute the instructions to verify that a first product request from a buyer is valid based on product attribute rules, the first product request to include a selected value corresponding to a first category of product attributes, reduce, via an iterative process, a set of possible values corresponding to a second category of the product attributes based on the selected value, the second category different from the first category, in response to determining the first product request is invalid, direct the buyer to provide a second product request different from the first product request, generate platform standard attributes of products corresponding to the tenants, the at least one processor to translate tenant-specific product attributes to the platform standard attributes based on the tenant-specific product attributes and the product attribute rules, evaluate an equivalency of the products based on the selected value for the first category of the product attributes and the platform standard attributes, and store the equivalency as a mapping for determining product substitutions.

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.

A method of managing inventory comprising generating a list of inventory items, identifying removal of one of the inventory items from inventory, updating the list of inventory items as inventory items are removed, predicting a future rate of removal of inventory items, and developing purchasing plan for inventory items based on predicted rate of removal.

The disclosed technologies can compute predictive reorder scores and measures of the quality of food products and food providers using objectively verifiable data, including reorder data, and use these predictive quality measures to create new functionality in an information search and retrieval system and/or a product ordering system.

A network computing system to coordinate a completion time of at least a portion of an order request with a target completion time, where the target completion time reflects an estimated time of arrival for a transportation provider with respect to a location of the supplier. The network computing system can coordinate the completion time by determining a timing of when at least a step in the preparation of at least the portion of the order request is performed by the supplier, based on an estimated arrival time of a transport provider. The network computing system can perform one or more control actions to influence the target completion time, based on the determined timing.