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    SELECTING ORDER CHECKOUT OPTIONS
    3.
    发明公开
    SELECTING ORDER CHECKOUT OPTIONS 审中-公开

    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.

    MACHINE LEARNING BASED RESOURCE ALLOCATION OPTIMIZATION
    7.
    发明公开
    MACHINE LEARNING BASED RESOURCE ALLOCATION OPTIMIZATION 审中-公开

    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.

    SELECTIVELY PROVIDING MACHINE LEARNING MODEL-BASED SERVICES
    8.
    发明公开
    SELECTIVELY PROVIDING MACHINE LEARNING MODEL-BASED SERVICES 审中-公开

    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.

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