Year: 2025
Type: conference-paper
Abstract: E-commerce retailers increasingly offer diverse fulfillment options (e.g., in-store pickup, same-day delivery from store, standard shipping from fulfillment centers and marketplace sellers), creating a need for search systems that understand and cater to individual customer preferences. This paper addresses the challenge of incorporating fulfillment intent into product search ranking. We propose a model that predicts customer fulfillment intent based on the search query, past user interactions, and other contextual information. A fulfillment match signal is introduced to quantify the alignment between a product's available fulfillment methods and the predicted customer intent. Integrating this signal into the ranking process ensures that search results prioritize products matching the user's preferred fulfillment type. Offline and online experiments demonstrate the efficacy of our approach and highlight the importance of fulfillment-aware ranking in omnichannel e-commerce.
Authors: Jingxu Xu, Xinyi Liu, Yang Yu, Semih Yagli, Jingbo Liu, Cun Mu
Institution: Walmart (United States)
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4412377787