公开(公告)号：US12198173B2

公开(公告)日：2025-01-14

申请号：US17731608

申请日：2022-04-28

Applicant: Maplebear Inc.

Inventor： Konrad Gustav Miziolek ,  Bryan Daniel Bor

IPC: G06Q30/00 ,  G06N20/20 ,  G06Q30/0201 ,  G06Q30/0601

Abstract: A user treatment engine uses user data describing characteristics of a user to evaluate a set of treatments that the user treatment engine may apply to the user. The user treatment engine generates treatment cost predictions for the treatments and generates treatment scores for the set of treatments based on the treatment cost predictions for the treatments and the user data for the user. The user treatment engine selects and applies a treatment from the set of treatments based on the generated treatment scores. The user treatment engine determines a reward to the online concierge system for the application of the treatment to the user and updates treatment selection parameters for the applied treatment based on the determined reward.

公开(公告)号：US20230351465A1

公开(公告)日：2023-11-02

申请号：US17731608

申请日：2022-04-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Konrad Gustav Miziolek ,  Bryan Daniel Bor

IPC: G06Q30/06 ,  G06N20/20 ,  G06Q30/02

CPC classification number: G06Q30/0617 ,  G06Q30/0625 ,  G06N20/20 ,  G06Q30/0206

Abstract: A user treatment engine uses user data describing characteristics of a user to evaluate a set of treatments that the user treatment engine may apply to the user. The user treatment engine generates treatment cost predictions for the treatments and generates treatment scores for the set of treatments based on the treatment cost predictions for the treatments and the user data for the user. The user treatment engine selects and applies a treatment from the set of treatments based on the generated treatment scores. The user treatment engine determines a reward to the online concierge system for the application of the treatment to the user and updates treatment selection parameters for the applied treatment based on the determined reward.

公开(公告)号：US11341554B1

公开(公告)日：2022-05-24

申请号：US17210949

申请日：2021-03-24

Applicant: Maplebear, Inc.

Inventor： Nicholas William Sturm ,  Bryan Daniel Bor ,  Konrad Gustav Miziolek ,  Ajay Pankaj Sampat ,  Darren Bartholomew Johnson

IPC: G06Q30/00 ,  G06Q30/06 ,  G06Q30/02

Abstract: 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.

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.