Walmart Apollo, LLC

Surnaik Prakash Srivastava

Vidyanand Krishnan

Mingang Fu

Madhavan Kandhadai Vasantham

Arun Prasad Nagarathinam

Shengyang Zhang

Apeksha Mehta

Pawan Kumar

Ankit Jasuja

Jennifer Chen

Austin Lee Smith

Rohit Jain

Puneet Srivastava

Navkaran Singh Chadha

Avaneesh Tiwari

Zekariyas Kassa Gebru

Mihir Vijay Bendale

Vineet Wason

Yiren Ye

Nitish Sarin

A method being implemented via execution of computing instructions configured to run at one or more processors. The method can include determining a primary store and one or more secondary stores for pickup of an order of a user, based at least in part on a pickup type of the order. The method also can include determining real-time availabilities of first time slots at the primary store and real-time availabilities of second time slots at the one or more secondary stores. The method additionally can include generating a list of available time slots comprising at least a portion of the first time slots at the primary store and at least a portion of the second time slots at the one or more secondary stores, based at least in part on the real-time availabilities of the first time slots at the primary store and the real-time availabilities of the second time slots at the one or more secondary stores. The method further can include facilitating displaying to the user a user interface comprising at least a portion of the list of available time slots. Other embodiments are described.

Automatically merging pickup and delivery time slots from nearby stores

In some examples, a system may include a first computing device communicatively coupled to a second computing device. Additionally, the first computing device is configured to obtain, from the second computing device, check-in data indicating an arrival of the user of the second computing device at a first location, and in response to obtaining the check-in data, determine current wait times. Moreover, the first computing device is configured to determine a first number of customers waiting for service, determine a first number of associates available to assist the first number of customers, and determine an expected wait time for the user operating the second computing device based at least on the current wait times. In some examples, the first number of customers waiting for service, and the first number of associates available. Further, the first computing device is configured to transmit the expected wait time to the second computing device.

Methods and apparatus for determining wait times

A system is provided and generally includes a server, an associate computing device, and a customer computing device. The server may receive data from the customer computing device indicating that a customer is picking up items from a predetermined location. The server may compute an estimated wait time for the customer based on one or more machine learning processes. In some examples, a number of unexpected customers that may arrive is determined. The machine learning process may compute the estimated wait time based on the number of unexpected customers. The machine learning process may be trained with historical data. The estimated wait time is transmitted to the customer computing device, and is displayed to the customer. In some examples, the server sends a list of customers waiting to be serviced to the associate computing device. The list may be prioritized based on estimated wait times for those customers.

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Santa Clara, CA, United States of America

Surnaik Prakash Srivastava