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：US11830018B2

公开(公告)日：2023-11-28

申请号：US17389281

申请日：2021-07-29

Applicant: Maplebear Inc.

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

IPC: G06Q10/00 ,  G06Q30/0201 ,  G06Q30/0601 ,  G06Q10/0631 ,  G06N5/04 ,  G06Q30/0204 ,  G06N20/00

CPC classification number: G06Q30/0206 ,  G06N5/04 ,  G06N20/00 ,  G06Q10/06312 ,  G06Q10/06313 ,  G06Q10/06315 ,  G06Q30/0205 ,  G06Q30/0635 ,  G06Q30/0641

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：US11803894B2

公开(公告)日：2023-10-31

申请号：US17202190

申请日：2021-03-15

Applicant: Maplebear, Inc.

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

IPC: G06Q30/00 ,  G06Q30/0601 ,  G06Q10/0631 ,  G06Q10/087 ,  G06Q30/0283

CPC classification number: G06Q30/0635 ,  G06Q10/06313 ,  G06Q10/06315 ,  G06Q10/087 ,  G06Q30/0284

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.

公开(公告)号：US12033109B1

公开(公告)日：2024-07-09

申请号：US18114858

申请日：2023-02-27

Applicant: Maplebear Inc.

Inventor： Shuai Wang ,  Zi Wang ,  Liang Chen ,  Houtao Deng ,  Xiangyu Wang ,  Aman Jain ,  Jian Wang

IPC: G06Q10/0835 ,  G06Q10/0833

CPC classification number: G06Q10/0835 ,  G06Q10/0833

Abstract: An online concierge system delivers items from retailers to customers. The online concierge predicts a range of times during which an order may be fulfilled for presentation to a user. The online concierge system uses a trained maximum time prediction model to determine a maximum time for order fulfillment based on an order. A trained minimum time prediction model determines a minimum time for order fulfillment from the order and the maximum time. The minimum time may account for one or more rules (e.g., a percentage of orders fulfilled before the minimum time, a desired rate of selection of a range including the minimum time). A range bounded by the maximum time and the minimum time is transmitted to a customer to enable the customer to select a time interval for order fulfillment.

公开(公告)号：US20230394420A1

公开(公告)日：2023-12-07

申请号：US18235309

申请日：2023-08-17

Applicant: Maplebear Inc.

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

IPC: G06Q10/0833

CPC classification number: G06Q10/0833 ,  G06Q10/087

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：US11823102B2

公开(公告)日：2023-11-21

申请号：US17308996

申请日：2021-05-05

Applicant: Maplebear, Inc.

Inventor： Houtao Deng ,  Ji Chen ,  Christopher Shey-Tau Sun ,  Yile Liu ,  Yijia Chen

IPC: G06Q10/0631 ,  G06Q10/0875

CPC classification number: G06Q10/063112 ,  G06Q10/06315 ,  G06Q10/0875

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：US20240403812A1

公开(公告)日：2024-12-05

申请号：US18203578

申请日：2023-05-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Liang Chen ,  Xiangyu Wang ,  Houtao Deng ,  Ganesh Krishnan ,  Kevin Charles Ryan ,  Aman Jain ,  Jian Wang

IPC: G06Q10/0834 ,  G06Q10/083 ,  G06Q10/0833 ,  G06Q30/0601

Abstract: An online concierge system generates a set of candidate estimated times of arrival (ETAs) for delivery of a set of items being purchased by a user. Each candidate ETA is scored by using a machine-learned model to estimate values for different criteria of interest, such as likelihood of acceptance of the ETA, cost of delivery of the items to the user, and the like. The values for the different criteria may be combined to generate the overall score for a candidate ETA. One or more of the highest-scoring ETAs are selected and provided to the user, who may then approve one of the ETAs for use with delivery of the user's set of items.

公开(公告)号：US20240144355A1

公开(公告)日：2024-05-02

申请号：US17977712

申请日：2022-10-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Liang Chen ,  Aman Jain ,  Xiangyu Wang ,  Houtao Deng ,  Jae Cho

IPC: G06Q30/06 ,  G06Q30/02

CPC classification number: G06Q30/0641 ,  G06Q30/0201 ,  G06Q30/0607

Abstract: The present disclosure is directed to selecting order checkout options. In particular, the methods and systems of the present disclosure may, responsive to receiving data describing a potential order for an online shopping concierge platform: generate, based at least in part on the data describing the potential order, a plurality of different and distinct checkout options for the potential order; determine, for each checkout option of the plurality of different and distinct checkout options and based at least in part on one or more machine learning (ML) models, a probability that a customer associated with the potential order will proceed with the potential order if presented with the checkout option; and select a subset of checkout options for presentation to the customer based on their respective determined probabilities that the customer will proceed with the potential order if presented with the subset of checkout options.

公开(公告)号：US20240070697A1

公开(公告)日：2024-02-29

申请号：US18503078

申请日：2023-11-06

Applicant: Maplebear Inc.

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

IPC: G06Q30/0201 ,  G06N5/04 ,  G06N20/00 ,  G06Q10/0631 ,  G06Q30/0204 ,  G06Q30/0601

CPC classification number: G06Q30/0206 ,  G06N5/04 ,  G06N20/00 ,  G06Q10/06312 ,  G06Q10/06313 ,  G06Q10/06315 ,  G06Q30/0205 ,  G06Q30/0635 ,  G06Q30/0641

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：US20240037467A1

公开(公告)日：2024-02-01

申请号：US18485554

申请日：2023-10-12

Applicant: Maplebear Inc.

Inventor： Houtao Deng ,  Ji Chen ,  Christopher Shey-Tau Sun ,  Yile Liu ,  Yijia Chen

IPC: G06Q10/0631 ,  G06Q10/0875

CPC classification number: G06Q10/063112 ,  G06Q10/0875 ,  G06Q10/06315

Abstract: An online concierge system maintains a data store with discrete time intervals for fulfilling orders and information on shoppers categorized in a tree structure based on their characteristics. When an order is received from a user's client device, the system employs a machine learning model trained on historical data to estimate the number of available shoppers and their corresponding levels in the tree structure. The order is tagged based on the items it contains, and these tags are matched to the levels of capable shoppers. Shoppers are grouped and scored based on their levels, and a group with the minimum score and capability to fulfill the order is selected. A shopper from this group is then dispatched for order fulfillment, leading to a decrement in the estimated number of shoppers in the selected group. This approach optimizes the allocation of shoppers to orders, ensuring efficient and timely fulfillment.