Maplebear Inc.

Darren Johnson

Benjamin Knight

Saumitra Maheshwari

Salmaan Ayaz

Tomasz Debicki

Valery Vaskabovich

Do Quang Phuoc Dang

Ajay Pankaj Sampat

Konrad Gustav Miziolek

Christopher Billman

Kenneth Jason Sanchez

Bryan Daniel Bor

Qi Xi

Jennie Braunstein

Conor Woods

Nicholas William Sturm

Daniel Haugh

An online system receives orders from users and dispatches pickers to fulfill the orders by obtaining ordered items at a retailer. If an ordered item cannot be found by a picker, the picker may refund the item or attempt to find a replacement item. While obtaining a replacement item may increase revenue to the online system, it can also cause a bad outcome for user experience (e.g., an unacceptable replacement item, a refund request of the replacement item, etc.). To balance these interests, the online system trains a model to predict an outcome metric comprising a likelihood of a bad outcome from replacing an item or an expected amount of profit to the online system from a replacement item. The online system compares the outcome metric to a threshold to determine whether to promote or dissuade the picker from replacing a not-found item.

Replacing an unavailable item in an order using a trained outcome prediction model

An online concierge system performs asynchronous automated correction handling of incorrectly sorted items using point-of-sale data. The online concierge system receives orders from customer client devices and determines a batched order based on the received orders. The online concierge system sends the batched order to a shopper client device for fulfillment. The online concierge system receives transaction data associated with the batched order from a third party system. The online concierge system determines whether a sorting error occurred based on the transaction data and the batched order. In response to determining that a sorting error occurred, the online concierge system sends an instruction to correct the sorting error to the shopper client device.

Asynchronous automated correction handling in concierge system of incorrectly sorted items using point-of-sale data

An online concierge system receives information from a warehouse including locations of items within the warehouse. When a shopper selects an order for fulfillment from the warehouse, the online concierge system sorts the items for the shopper to minimize the time spent in the warehouse using the received information. When the online concierge system does not receive a location of an item within the warehouse, the online concierge system obtains a taxonomy for the warehouse including multiple levels, with each level having a different level of specificity. The online concierge system determines a higher level in the taxonomy for the item and identifies other items offered by the warehouse having the determined category. The online concierge system infers a location of the item within the warehouse used for sorting items of the order from locations of the other items within the warehouse and times when shoppers retrieved the other items.

Inferring a location of an item within a warehouse from a taxonomy of items offered by the warehouse and locations of other items within the warehouse

An online concierge system receives orders from users that include items from one or more warehouses. The online concierge system identifies the orders to shoppers, who select one or more orders to fulfill. The online concierge system uses models to estimate orders likely to be received at different times and shoppers likely to be available to fulfill orders at different times. Responsive to greater than a threshold difference between estimated orders and estimated shoppers during a time interval, the online concierge system selects one or more incentives for shoppers to select orders during the time interval to entice shoppers to select orders during the time interval. An interface displayed to the shoppers by the online concierge system may present a map of warehouses and their estimated number of orders and allow shoppers to identify incentives offered for fulfilling orders at different warehouses during the time interval.

Software platform to manage shoppers to fulfill orders for items received by an online concierge system

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Elko, NV, United States of America

Darren Johnson