公开(公告)号：US20180068374A1

公开(公告)日：2018-03-08

申请号：US15258942

申请日：2016-09-07

Applicant: Maplebear, Inc.(dba Instacart)

Inventor： Emmanuel Jean Yves Turlay ,  Elizabeth Ruth Barnum ,  Ashu Khaitan ,  Moses Yung Kyu Lee ,  Denise Hoi Shuen Leung ,  Arnaud Nicolas Ferreri

IPC: G06Q30/06 ,  G06Q20/18

CPC classification number: G06Q30/0633 ,  G06Q20/18 ,  G06Q20/20 ,  G06Q20/3276 ,  G07G1/0045 ,  G07G1/0081 ,  G07G1/009

Abstract: An online shopping concierge service allows shoppers to purchase items on behalf of customers and checkout using a mobile application, circumventing traditional point-of-sale check-out systems. A customer places an order using a mobile application or website associated with the online shopping concierge service. The online shopping concierge service charges a payment instrument of the customer in the value of the selected items. The system transmits the order to a shopper, who receives an order for fulfillment on a mobile device. The shopper collects and scans items using a mobile application. The mobile application transmits an identification of the items for purchase and their total cost to the online shopping concierge service, which transmits payment to the retailer. Alternatively, the mobile application encodes an identification of the items for purchase into an encoded image, which is scanned by a cashier, allowing the shopper to complete an accelerated check-out.

公开(公告)号：US20240428324A1

公开(公告)日：2024-12-26

申请号：US18213761

申请日：2023-06-23

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Tianshu Ren

IPC: G06Q30/08 ,  G06Q30/0601

Abstract: An online concierge system includes a content selection simulation module that performs offline simulations of a content selection process to enable rapid testing of various content selection parameters. The content selection simulation module obtains historical content selection data including content delivery opportunities and candidate content items associated with those content delivery opportunities. The content selection simulation module simulates the filtering, ranking, and auction stages of a content selection process using a set of configurable content selection parameters that affects selection of a winning content item and price. The winning content items from the simulation may be used to compute performance metrics associated with the configured content selection parameters. Different content selection parameters may be compared to determine an effect of changes to the parameters.

公开(公告)号：US20240428314A1

公开(公告)日：2024-12-26

申请号：US18212122

申请日：2023-06-20

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ryan McColeman ,  Brent Scheibelhut ,  Mark Oberemk ,  Shaun Navin Maharaj

IPC: G06Q30/0601 ,  G06Q30/0201

Abstract: The present disclosure is directed to determining purchase suggestions for an online shopping concierge platform. In particular, the methods and systems of the present disclosure may receive, from a computing device associated with a customer of an online shopping concierge platform, data indicating one or more interactions of the customer with the online shopping concierge platform; determine, based at least in part on one or more machine learning (ML) models and the data indicating the interaction(s), a likelihood that the customer will purchase a particular item if presented, at a specific time, with a suggestion to purchase the particular item; and generate and communicate data describing a graphical user interface (GUI) comprising at least a portion of a listing of one or more purchase suggestions including the suggestion to purchase the particular item.

公开(公告)号：US20240428310A1

公开(公告)日：2024-12-26

申请号：US18214316

申请日：2023-06-26

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Dustin Neray ,  Licheng Yin ,  George Zeng ,  Siddarth Kalra ,  Levon Dolbakian ,  Amos Too ,  Jaclyn Tandler

IPC: G06Q30/0601

Abstract: Embodiments are related to automatic prediction of times for completion of tasks for an order by a picker associated with an online system and determination of an appropriate intervention for the picker. The online system applies a computer model to predict a plurality of times for completion of a plurality of tasks associated with the first order. The online system determines that the picker who accepted the first order did not complete a task of the plurality of tasks at a predicted time of the plurality of times increased by a threshold time. The online system determines an intervention associated with the picker, based in part on the determination that the picker did not complete the task. The online system causes a device of the picker to display a message that corresponds to the determined intervention.

公开(公告)号：US20240428157A1

公开(公告)日：2024-12-26

申请号：US18212883

申请日：2023-06-22

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Rahul Makhijani

IPC: G06Q10/0631 ,  G06N20/00 ,  G06Q10/083 ,  G06Q10/087 ,  G06Q30/0601

Abstract: Embodiments are related to using a trained computer model to predict a supply state of an online system for state-aware management of order fulfillments. The online system measures first values of a metric for a set of sample orders. The online system accesses the computer model trained to predict a value of the metric for an order placed with the online system. The online system applies the computer model to predict second values of the metric for the set of sample orders, based on one or more features of each sample order. The online system compares a distribution of the first values to a distribution of the second values and determines the supply state of the online system based on the comparison. Responsive to the determination of the supply state, the online system triggers a remedial action for the online system that adjusts the supply state of the online system.

公开(公告)号：US20240420210A1

公开(公告)日：2024-12-19

申请号：US18211107

申请日：2023-06-16

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Bhavya Gulati ,  Chakshu Ahuja ,  Karuna Ahuja ,  Girija Narlikar

IPC: G06Q30/0601

Abstract: An online concierge system receives information describing items in orders placed by a customer and a sequence of events associated with each order and identifies an impulse item included in the orders based on a set of rules, attributes of each item, and/or the sequence of events. The system applies a model to predict a measure of similarity between the impulse item and each of multiple candidate items and identifies larger-size variants of the impulse item based on this prediction and attributes of the impulse item and each candidate item. The system applies another model to predict a likelihood the customer will order each variant, computes a recommendation score for each variant based on this prediction, and determines whether to recommend each variant based on the score. Based on the determination, the system generates and sends a recommendation for a variant to a client device associated with the customer.

公开(公告)号：US20240420037A1

公开(公告)日：2024-12-19

申请号：US18210976

申请日：2023-06-16

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Zi Wang ,  Houtao Deng ,  Xiangyu Wang ,  Ganesh Krishnan ,  Aman Jain

IPC: G06Q10/04 ,  G06Q10/083 ,  G06Q30/0601

Abstract: Embodiments relate to determining an availability of a service option for delivery of an order placed with an online system. The online system receives an order placed with the online system. The online system accesses a computer model trained to predict a value of metric for an order placed with the online system. The online system applies the computer model to predict the value of the metric for the order. The online system determines which service option of a plurality of service options of the online system is available for delivery of the order, based at least in part on the predicted value of the metric and a threshold. The online system causes the device of the user to display an availability of the determined service option for delivery of the order.

公开(公告)号：US20240419941A1

公开(公告)日：2024-12-19

申请号：US18210553

申请日：2023-06-15

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ze He ,  Dian Ding ,  Hechao Sun

IPC: G06N3/045 ,  G06N3/084 ,  G06Q10/087 ,  G06Q20/40 ,  G06Q30/0601

Abstract: Embodiments relate to an automatic detection of fraudulent behavior for a transaction at an online system. The online system requests a large language model (LLM) to determine, based on a prompt input into the LLM, information about a refund event for a first order placed by a user of the online system. The online system accesses a computer model trained to detect a fraudulent behavior associated with an order placed with the online system. The online system applies the computer model to determine a score associated with the refund event, based on the information about the refund event received from the LLM. The online system determines, based on the score, whether the refund event was due to a fraudulent behavior of the user. The online system performs at least one action associated with the online system, based on the determination whether the refund event was due to the fraudulent behavior.

公开(公告)号：US20240403826A1

公开(公告)日：2024-12-05

申请号：US18204200

申请日：2023-05-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Youdan Xu ,  Aoshi Li ,  Jaclyn Tandler ,  Roman Hayran ,  Brendan Evans Ashby ,  Emily Silberstein ,  Ajay Pankaj Sampat

IPC: G06Q10/0875 ,  G06N3/084 ,  G06Q20/12

Abstract: An online concierge system allows customers to place orders to be fulfilled by pickers. An order includes an amount of compensation a customer provides to a picker when the order is fulfilled. A customer may modify the amount of compensation provided to a picker, so some customers may initially specify a large amount of compensation to entice a picker to fulfill an order and then reduce the amount of compensation when the order is fulfilled. To prevent penalizing pickers who fulfilled an order without a problem, the online concierge system trains a model to determine a probability that a reduction in compensation to a picker was unrelated to a problem with order fulfillment. The online concierge system may perform one or more remedial actions for a picker based on the probability determined by the model.

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.