公开(公告)号：US20220414592A1

公开(公告)日：2022-12-29

申请号：US17359486

申请日：2021-06-25

Applicant: Maplebear Inc.(dba Instacart)

Inventor： Zi Wang ,  Ji Chen ,  Houtao Deng ,  Soren Zeliger ,  Yijia Chen

IPC: G06Q10/08

Abstract: An online concierge system displays an interface to a user identifying an estimated time of arrival for an order. To generate the estimated time of arrival for the order, the online concierge system trains a prediction engine to predict delivery time based on a predicted selection time for a shopper to select the order for fulfillment and predicted travel time for the shopper to deliver items of the order to a location identified by the order. The online concierge system generates a policy optimization model that computes an adjustment for the predicted delivery time. The adjustment is determined by solving a stochastic optimization problem with a constraint on a probability of the order being delivered after the estimated time of arrival. The predicted delivery time combined with the adjustment determines the estimated time of delivery displayed to the user to balance between minimizing late deliveries and wait times.

公开(公告)号：US20230351279A1

公开(公告)日：2023-11-02

申请号：US17731810

申请日：2022-04-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Soren Zeliger ,  Aman Jain ,  Zhaoyu Kou ,  Ji Chen ,  Trace Levinson ,  Ganesh Krishnan

IPC: G06Q10/06

CPC classification number: G06Q10/063116 ,  G06Q10/04

Abstract: An online concierge system assigns shoppers to fulfill orders from users. To allocate shoppers, the online concierge system predicts future supply and demand for the shoppers' services for different time windows. To forecast a supply of shoppers, the online concierge system trains a machine learning model that estimates future supply based on access to a shopper mobile application through which the shoppers obtain new assignments by shoppers. The online concierge system also forecasts future orders. The online concierge system estimates a supply gap in a future time period by selecting a target time to accept for shoppers to accept orders and determining a corresponding ratio of number of shoppers and number of orders. The online concierge system may adjust a number of shoppers allocated to the future time period to achieve the determined ratio number of shoppers and number of orders.

公开(公告)号：US20240104458A1

公开(公告)日：2024-03-28

申请号：US17955407

申请日：2022-09-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Wa Yuan ,  Jae Cho ,  Yijia Chen ,  Houtao Deng ,  Soren Zeliger ,  Aman Jain ,  Jian Wang ,  Ji Chen

IPC: G06Q10/06 ,  G06N5/02 ,  G06Q30/06

CPC classification number: G06Q10/063116 ,  G06N5/022 ,  G06Q10/06393 ,  G06Q30/0637

Abstract: An online concierge system determines a quantity of a resource available in a timeslot to fulfill orders during the timeslot. The orders include immediate orders placed during the timeslot and scheduled orders that are scheduled for fulfillment during the timeslot. The online concierge system applies the quantity of the resource to a machine learning model to produce a predicted relationship between a value of a fulfillment metric and an allocation of the quantity of the resource reserved for immediate orders. The online concierge system determines, based on the predicted relationship, an expected optimal allocation of the quantity of the resource that maximizes the fulfillment metric. The online concierge system reserves the expected optimal allocation of the quantity of the resource for immediate orders.

公开(公告)号：US20230196442A1

公开(公告)日：2023-06-22

申请号：US17556936

申请日：2021-12-20

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Trace Levinson ,  Aman Jain ,  Ji Chen ,  Andrew Kephart

IPC: G06Q30/06

CPC classification number: G06Q30/0635

Abstract: An online concierge system allocates shoppers to different geographic regions at different times to fulfill orders received from users. The online concierge system uses different methods for adjusting allocation of shoppers to geographic regions, such as obtaining new shoppers or providing incentives to additional shoppers, based on estimated numbers of orders identifying different geographic regions. To account for costs to the online concierge system for allocating shoppers to geographic regions, the online concierge system trains multiple machine learned models to predict different efficiency metrics for methods for adjusting shopper allocation. Discrete samples are obtained from each efficiency metric, and samples that do not satisfy one or more constraints removed. From the remaining samples, a combination of samples for different methods for adjusting shopper allocation is selected to optimize a value to the online concierge system based on one or more criteria.

公开(公告)号：US20220358443A1

公开(公告)日：2022-11-10

申请号：US17308996

申请日：2021-05-05

Applicant: Maplebear, Inc.(dba Instacart)

Inventor： Houtao Deng ,  Ji Chen ,  Chris Sun ,  Yile Liu ,  Yijia Chen

IPC: G06Q10/06 ,  G06Q10/08

Abstract: An online concierge system allows users to order items within discrete time intervals later than a time when an order was received. Each order may require a different set of characteristics for fulfilment by shoppers. Because different shoppers may have different capabilities, it is most efficient to reserve shoppers with specialized characteristics for orders that require them. The online concierge system maintains a set of hierarchical structures for different characteristics of shoppers, with each level in a hierarchical structure having a value. To select a shopper to fulfill an order, the online concierge system scores identifies groups of shoppers having characteristics capable of fulfilling the order based on levels in the hierarchical structure for each characteristic of a group. A shopper from a group having a minimum score is selected to fulfill the order.

公开(公告)号：US20230034221A1

公开(公告)日：2023-02-02

申请号：US17389281

申请日：2021-07-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Houtao Deng ,  Ji Chen ,  Zi Wang ,  Soren Zeliger ,  Ganesh Krishnan ,  Wa Yuan ,  Michael Scheibe

IPC: G06Q30/02 ,  G06Q30/06 ,  G06Q10/06 ,  G06N20/00 ,  G06N5/04

Abstract: An online concierge system allows users to order items within discrete time intervals later than a time when an order was received or for short-term fulfillment when the order was received. To account for a number of shoppers available to fulfill orders during different discrete time intervals and numbers of orders for fulfillment during different discrete time intervals, the online concierge system specifies a target rate for orders fulfilled later than a specified discrete time interval and a threshold from the target rate. A trained machine learning model periodically predicts a percentage of orders being fulfilled late, with an order associated with a predicted percentage when the order was received. The online concierge system increases a price of orders associated with predicted percentages greater than the threshold from the target rate. The increased price of an order is determined from a price elasticity curve and the predicted percentage.

公开(公告)号：US20220292580A1

公开(公告)日：2022-09-15

申请号：US17202190

申请日：2021-03-15

Applicant: Maplebear, Inc.(dba Instacart)

Inventor： Jagannath Putrevu ,  Zi Wang ,  Site Wang ,  Houtao Deng ,  Yijia Chen ,  Mingzhe Zhuang ,  Ji Chen ,  Deepak Tirumalasetty

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

Abstract: An online concierge system allows users to order items within discrete time intervals later than a time when an order was received. The online concierge system allocates a specified percentage of an estimated number of shoppers during a discrete time interval to fulfilling orders received before the discrete time interval. An order may include a flag authorizing flexible fulfillment of the order along with a discrete time interval, which allows the order to be fulfilled earlier than the identified discrete time interval. The online concierge system generates groups of multiple orders authorizing flexible fulfillment and determines a cost for fulfilling different groups of orders. The online concierge system identifies a group of orders authorizing flexible fulfillment having a minimum cost for fulfillment by a shopper, allowing for more allocation of shoppers by enabling grouping of orders identifying different discrete time intervals.