公开(公告)号：US20230325856A1

公开(公告)日：2023-10-12

申请号：US18186141

申请日：2023-03-17

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Trace Levinson ,  Nicholas Sturm

IPC: G06Q30/0202

CPC classification number: G06Q30/0202

Abstract: An online system computes an incremental cost prediction for each of a set of user-treatment pairs to select a set of treatments to apply to users to satisfy a predicted interaction gap. The online system generates a set of candidate user-treatment pairs that each include user data for a user of the online system and treatment data for a treatment of a set of treatments. The online system computes an incremental interaction prediction and a treatment cost prediction for each of the candidate user-treatment pairs by applying an incremental interaction model to the user data and the treatment data in each user-treatment pair. The online system computes incremental cost predictions for each of the user-treatment pairs based on the computed incremental interaction predictions and treatment cost predictions and selects which users to apply treatments to and which treatments to apply to those users based on the incremental cost predictions.

公开(公告)号：US20240037588A1

公开(公告)日：2024-02-01

申请号：US17877758

申请日：2022-07-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Rockson Chang ,  Licheng Yin ,  Chen Zhang ,  Michael Chen ,  Aaron Dou ,  Radhika Anand ,  Nicholas Sturm ,  Ajay Sampat

IPC: G06Q30/02 ,  G06Q10/08 ,  G06Q10/06

CPC classification number: G06Q30/0205 ,  G06Q10/0836 ,  G06Q10/0635 ,  G06Q30/0222

Abstract: The present disclosure is directed to determining shopper-location pairs. In particular, the methods and systems of the present disclosure may identify a set of available shoppers associated with an online shopping concierge platform and located in a geographic area; identify a set of available warehouse locations associated with the online shopping concierge platform and located in the geographic area; and determine, based at least in part on the set of available shoppers, the set of available warehouse locations, and one or more machine learning (ML) models, a set of shopper-location pairs optimized based at least in part on time required by the set of available shoppers to travel from their respective current locations to one or more of the set of available warehouse locations.

公开(公告)号：US20240289828A1

公开(公告)日：2024-08-29

申请号：US18113564

申请日：2023-02-23

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Wenhui Zhang ,  Shivee Singh ,  Brendan Evans Ashby ,  Xiaofan Xu ,  Konrad Gustav Miziolek ,  Bryan Daniel Bor ,  Nikita Srinivasan ,  Nicholas Sturm

IPC: G06Q30/0201 ,  G06Q30/0202

CPC classification number: G06Q30/0206 ,  G06Q30/0202

Abstract: An online concierge system schedules pickers (shoppers) to fulfill orders from users. During periods of peak demand, the system increases compensation to shoppers to encourage more to participate, thereby reducing missed orders. The system determines an optimal multiplier to increase compensation based on predictive models of supply and demand and then applying an optimization algorithm to search different hyperparameters that affect how the models generate the multipliers. The system selects the optimal multipliers for different time periods and locations. The system may further present the multipliers being offered during future time periods and enable users to activate reminder alerts for select periods. The offers may be presented in a ranked list using a model trained to infer likelihoods of the user accepting participation and/or setting a reminder notification.