公开(公告)号：US20240144191A1

公开(公告)日：2024-05-02

申请号：US17977759

申请日：2022-10-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ganesh Krishnan ,  Xiaofan Xu ,  Kevin Ryan

IPC: G06Q10/10

CPC classification number: G06Q10/1093

Abstract: An online concierge system receives a goal and availability information for a picker, in which the availability information describes time slot-location pairs for which the picker is available. The system accesses and applies a first and a second machine learning model to predict a likelihood that an order will be available for service and an amount of earnings for servicing the order, respectively, for each time slot-location pair. The system computes an estimated amount of earnings for each time slot-location pair based on the predictions and generates suggested schedules that each includes one or more time slot-location pairs. For each suggested schedule, the system computes a total estimated amount of earnings based on the estimated amount of earnings and one or more costs. The system identifies a suggested schedule for achieving the goal based on the total estimated amount of earnings or an estimated amount of time included in the suggested schedule.

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：US20240070605A1

公开(公告)日：2024-02-29

申请号：US17897045

申请日：2022-08-26

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shuai Wang ,  Zi Wang ,  Ganesh Krishnan ,  Houtao Deng ,  Aman Jain ,  Jian Wang

IPC: G06Q10/08 ,  G06N5/02 ,  G06Q10/06 ,  G06Q30/06

CPC classification number: G06Q10/0838 ,  G06N5/022 ,  G06Q10/06393 ,  G06Q30/0617

Abstract: An online concierge system provides arrival prediction services for a user placing an order to be retrieved by a shopper. An order may have a predicted arrival time predicted by a model that may err under some conditions. To reduce the likelihood of providing the predicted arrival time (and related services) when the arrival time may be incorrect, the prediction model and related services are throttled (e.g., selectively provided) based on one or more predicted delivery metrics, which may include a time to accept the order by a shopper and a predicted portion of late orders that will be delivered past the respective predicted arrival times. The predicted delivery metrics are compared with thresholds and the result of the comparison used to selectively provide, or not provide, the predicted delivery services.

公开(公告)号：US20220343395A1

公开(公告)日：2022-10-27

申请号：US17238217

申请日：2021-04-23

Applicant: Maplebear, Inc.(dba Instacart)

Inventor： Amy Luong ,  Michael Righi ,  Graham Adeson ,  Ross Stuart Williams ,  Aman Jain ,  Radhika Anand ,  Ganesh Krishnan

IPC: G06Q30/06

Abstract: For each retailer in the geographic region, an online system predicts a number of orders placed at the retailer and a capacity to fulfill orders during a forecast time period. The capacity of the retailer is predicted based on a number of pickers expected to be available to the retailer during the forecast time period. The online system determines demand for the services of a picker at the retailer based on a comparison of the predicted number of orders and the predicted capacity to fulfill those orders. The online system displays a user interactive map of the geographic region to the picker. The map displays a pin at the location of each retailer in the geographic region, which describes the categorization determined for the retailer. The picker selects a pin, which causes the user interactive map to display a notification characterizing the demand for services at the retailer.

公开(公告)号：US20240005381A1

公开(公告)日：2024-01-04

申请号：US17855788

申请日：2022-06-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Sonali Deepak Chhabria ,  Xiangyu Wang ,  Aman Jain ,  Ganesh Krishnan ,  Trace Levinson ,  Jian Wang

IPC: G06Q30/06 ,  G06Q10/06 ,  G06Q10/08 ,  G01C21/34

CPC classification number: G06Q30/0635 ,  G06Q10/06311 ,  G06Q10/087 ,  G01C21/3407

Abstract: An online concierge system includes a marketplace automation engine for setting various control parameters affecting marketplace operation. The marketplace automation engine applies a hyperparameter learning model to the marketplace state data to predict a set of hyperparameters affecting a set of respective parameterized control decision models. The hyperparameter learning model is trained on historical marketplace state data and a configured outcome objective for the online concierge system. The marketplace automation engine independently applies the set of parameterized control decision models to the marketplace state data using the hyperparameters to generate a respective set of control parameters affecting marketplace operation of the online concierge system. The marketplace automation engine applies the respective set of control parameters to operation of the online concierge system.

公开(公告)号：US20230049669A1

公开(公告)日：2023-02-16

申请号：US17403400

申请日：2021-08-16

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Wa Yuan ,  Ganesh Krishnan ,  Qianyi Hu ,  Aishwarya Balachander ,  George Ruan ,  Soren Zeliger ,  Mike Freimer ,  Aman Jain

IPC: G06Q30/02 ,  G06N3/08 ,  G06Q10/06 ,  G06Q10/08 ,  G06Q30/06

Abstract: An online concierge system trains a machine learning conversion model that predicts a probability of receiving an order from a user when the user accesses the online concierge system. The conversion model predicts the probability of receiving the order based on a set of input features that include price and availability information. For each access to the online concierge system, the online concierge system applies the conversion model to a current price and availability and to an optimal price availability. The online concierge system generates a metric as the difference between the two predicted probabilities of receiving an 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：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：US20240070491A1

公开(公告)日：2024-02-29

申请号：US17900533

申请日：2022-08-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Lanchao Liu ,  George Ruan ,  Zhiqiang Wang ,  Xiangdong Liang ,  Jagannath Putrevu ,  Ganesh Krishnan ,  Ryan Dick

IPC: G06N5/04 ,  G06N5/02

CPC classification number: G06N5/04 ,  G06N5/022

Abstract: An online system accesses a machine learning model trained to predict behaviors of users of the online system, in which the model is trained based on historical data received by the online system that is associated with the users and demand and supply sides associated with the online system. The online system identifies a treatment for achieving a goal of the online system and simulates application of the treatment on the demand and supply sides based on the historical data and a set of behaviors predicted for the users. Application of the treatment is simulated by replaying the historical data in association with application of the treatment and applying the model to predict the set of behaviors while replaying the data. The online system measures an effect of application of the treatment on the demand and supply sides based on the simulation, in which the effect is associated with the goal.

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.