Walmart Apollo, LLC

Swati Bhatt

Kannan Achan

Sushant Kumar

Hyun Duk Cho

Vidya Sagar Kalidindi

Kamiya Motwani

A system is configured to train a customer understanding model to generate a preference score for substitution items. The customer understanding model generates a preference score for each of a plurality of related substitution items based on order data including data indicative of at least one item ordered and location data indicating a location of a first store. The customer understanding model ranks each of the substitution items based on the preference score. Order data is transmitted including substitution data identifying each of the substitution items and corresponding rank. Performance data associated with a set of operations implemented based on the order data and the substitution data is obtained. An updated customer understanding model is trained based on the performance data and iteratively modified based on the updated training dataset and updated performance metrics generated from second performance data.

Methods and apparatuses for recommending substitutions made during order fulfillment processes

A system includes a computing device configured to obtain item attribute data that corresponds to a characteristic of an item ordered by a customer on an e-commerce platform and a common characteristic of a plurality of substitution items. The computing device is also configured to obtain customer attribute data identifying preferences of the customer and to determine a preference score for each substitution item in the plurality of substitution items based on the item attribute data and the customer attribute data. The preference score indicates a likelihood that the customer will accept one of the plurality of substitution items as a replacement for the item ordered by the customer. The computing device is also configured to rank each substitution item in the plurality of substitution items based on the preference scores.

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Mountain View, CA, United States of America

Swati Bhatt