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：US11574325B1

公开(公告)日：2023-02-07

申请号：US17403400

申请日：2021-08-16

Applicant: Maplebear Inc.

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

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

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：US12008590B2

公开(公告)日：2024-06-11

申请号：US18149646

申请日：2023-01-03

Applicant: Maplebear Inc.

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

IPC: G06Q30/02 ,  G06N3/084 ,  G06Q10/0631 ,  G06Q10/087 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q30/0601

CPC classification number: G06Q30/0202 ,  G06N3/084 ,  G06Q10/06312 ,  G06Q10/087 ,  G06Q30/0201 ,  G06Q30/0607 ,  G06Q30/0633

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：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：US20230153847A1

公开(公告)日：2023-05-18

申请号：US18149646

申请日：2023-01-03

Applicant: Maplebear Inc. (dba Instacart)

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

IPC: G06Q30/0202 ,  G06N3/084 ,  G06Q30/0201 ,  G06Q30/0601 ,  G06Q10/087 ,  G06Q10/0631

CPC classification number: G06Q30/0202 ,  G06N3/084 ,  G06Q30/0201 ,  G06Q30/0633 ,  G06Q10/087 ,  G06Q30/0607 ,  G06Q10/06312

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.