公开(公告)号：US20240394720A1

公开(公告)日：2024-11-28

申请号：US18202876

申请日：2023-05-26

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Youdan Xu ,  Michael Chen ,  Marina Tanasyuk ,  Matthew Donghyun Kim ,  Ajay Pankaj Sampat ,  Caleb Grisell ,  Yuan Gao

IPC: G06Q10/08 ,  G08G1/14 ,  H04W4/02

Abstract: An online concierge system uses a machine-learned parking quality model to quantify the suitability of a particular parking location (e.g., a parking lot, or a street) for use when performing purchases at a retail location on behalf of customers. The parking quality model's output is determined according to input features related to parking at a candidate parking location, such as a current time, a current degree of demand for shoppers at the retail location, or a current average shopper wait time at the retail location before receiving an order. The online concierge system provides suggested alternate parking locations to a client device of the shopper, where they may be displayed, e.g., as part of an electronic map. Use of the suggested alternate parking locations helps to preserve parking availability in restricted areas such as retailer parking lots and to reduce traffic congestion in the area of the retailer.

公开(公告)号：US20250111410A1

公开(公告)日：2025-04-03

申请号：US18374462

申请日：2023-09-28

Applicant: Maplebear Inc.

Inventor： Van Nguyen ,  Fangzhou Wang ,  Ajay Pankaj Sampat ,  Ann Barzman ,  Yuan Gao ,  Amsal Lakhani

IPC: G06Q30/0241 ,  G06F40/197 ,  G06Q30/0204 ,  G06Q30/0242 ,  G06Q30/0251

Abstract: An online system receives user data for users of the online system and assigns the users to one or more user cohorts based on the user data. The online system generates a prompt for content to be included in a landing page presented to each user cohort, in which the prompt includes a template for the landing page and information describing the user cohorts. The online system then provides the prompt to a generative artificial intelligence model to obtain an output and extracts, from the output, a set of content to be included in the landing page for each user cohort. The online system generates variants of the landing page for each user cohort based on the extracted set of content.

公开(公告)号：US20240289731A1

公开(公告)日：2024-08-29

申请号：US18113566

申请日：2023-02-23

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Youdan Xu ,  Matthew Donghyun Kim ,  Michael Chen ,  Marina Tanasyuk ,  Caleb Grisell ,  Adrian Mclean ,  Ajay Pankaj Sampat ,  Yuan Gao

IPC: G06Q10/0834 ,  G06Q10/083

CPC classification number: G06Q10/08345 ,  G06Q10/0631 ,  G06Q10/0838 ,  G06Q10/1053

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.

公开(公告)号：US20250139728A1

公开(公告)日：2025-05-01

申请号：US18498445

申请日：2023-10-31

Applicant: Maplebear Inc.

Inventor： Roman Havran ,  Satish Kumar Reddy Kancherla ,  Chen Zhang ,  Sai Kannan Sampath ,  Youdan Xu ,  Yuan Gao

IPC: G06Q50/30 ,  G01C21/00 ,  G06Q30/0601

Abstract: A concierge system identifies retail locations within a distance of a picker client device of a picker. This distance defines a zone and the system provides a map of the zone for display within a picker client application. For each retail location in the zone, the system determines a batch volume for the retail location and an average batch volume for the zone and generates a batch availability score using a model trained on batch volumes for the retail location and batch volume for the zone. The batch availability score can be a value reflecting batch availability or busyness of the retail location relative to other retail locations or can be a wait time prediction in minutes until the picker receives a batch at the retail location. The system modifies how the retail locations are displayed on the map to emphasize those with batch availability scores above a threshold value.