Maplebear Inc.

Qi Xi

Krishna Kumar Selvam

Benjamin Knight

Darren Johnson

Saumitra Maheshwari

Christopher Billman

Ashish Sinha

Daniel Haugh

Shang Li

David Zandman

Conor Woods

Amirali Darvishzadeh

A machine-learned predictive model is trained to predict potential for customer complaint. The model is part of an online concierge system. The online concierge system accesses a customer order that includes one or more items. The online concierge system determines input data for an item of the one or more items. The online concierge system determines a prediction value associated with potential for customer complaint for the item by applying the machine-learned prediction model to the input data. The online concierge system provides the prediction value to a picker client device associated with a picker who is assigned the item. The picker client device presents an alert to the picker based in part on the prediction value, and the alert includes a message that is customized to mitigate a cause of potential customer complaint for the item.

Machine learning assisted alerts for item picking

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

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New York, NY, United States of America

Qi Xi