Maplebear Inc.

Rob Donnelly

Robert Fletcher

Sharath Rao Karikurve

Peng Qi

Tilman Drerup

Jeffrey Bernard Arnold

David Pal

Cameron Nicholas Taylor

Jonathan Gu

Bill Lundberg

Pedro Tanure Veloso

Matthew Wean

Ben Lowenstein

Sumit Garg

An online concierge system fulfills orders for items offered by retailers and may increase the price of an item offered by a retailer in some instances. The online concierge system applies a markup to an item by applying a pricing policy to a category including the item. To optimize application of pricing policies to categories, the online concierge system categorizes items offered by the retailer and applies an outcome model to combinations of categories and pricing policies. From the output of the outcome model, the online concierge system selects a set of categories and corresponding pricing policies. Using a price adjustment model, the online concierge system determines modifications to one or more of the pricing policies of the set to enforce one or more constraints across multiple pricing policies.

Counterfactual evaluation of policies for categories of items using machine learning prediction of outcomes

An online concierge system includes sponsored content items in an interface including different slots for displaying content items. A sponsored content item may be displayed in a single slot or in multiple adjacent slots. The online concierge system determines a content score for various sponsored content items indicating a likelihood of a user interacting with a sponsored content item and a position bias for slots in the interface indicating a likelihood of the user interacting with a slot independent of content in the slot. Position biases are different dependent on a number of slots in which a content item is displayed. The online concierge system generates a graph identifying potential placements of sponsored content items in slots by selecting content items in an order according to their content scores. Sponsored content items are positioned in slots according to a path through the graph that has the highest overall expected value.

Method, computer program product, and system for accounting for variable dimensions of content items when positioning content items in a user interface having slots for displaying content items

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San Francisco, CA, United States of America

Rob Donnelly