Frontiers: Recommending What to Search: Sales Volume and Consumption Diversity Effects of a Query Recommender System

Shuang Zheng (), Siliang (Jack) Tong (), Hyeokkoo Eric Kwon (), Gordon Burtch () and Xianneng Li ()
Additional contact information
Shuang Zheng: School of Economics and Management, Dalian University of Technology, Dalian City 116024, China
Siliang (Jack) Tong: Nanyang Business School, Nanyang Technological University, Singapore 639798
Hyeokkoo Eric Kwon: Nanyang Business School, Nanyang Technological University, Singapore 639798
Gordon Burtch: Questrom School of Business, Boston University, Boston, Massachusetts 02215
Xianneng Li: School of Economics and Management, Dalian University of Technology, Dalian City 116024, China; and Institute for Advanced Intelligence, Dalian University of Technology, Dalian City 116024, China

Marketing Science, 2025, vol. 44, issue 3, 516-524

Abstract: This study examines the impact of a query recommender system on user search behavior, sales volume, and consumption diversity within a leading mobile food delivery app in Asia. We find that access to a query recommender increases consumer purchase volumes by 1%–2% over 30 days while broadening consumption diversity at both the individual and market levels. Exploring the mechanisms by which these effects arise, we highlight the complementary, balancing role of query auto-completion features. Whereas the query recommender helps to expand a user’s consideration set by suggesting alternative and adjacent queries, the auto-complete feature helps to extend and refine the queries in a personalized manner. Our findings highlight the potential of query recommenders for increasing demand while enhancing consumer exploration and consumption diversity, particularly when deployed in tandem with auto-complete. Our study contributes to the literature on search behavior and recommendation systems, offering actionable insights for platform managers into the strategic design and integration of query recommenders to improve user engagement and market outcomes.

Keywords: query recommendation; mobile shopping; mobile search; field experiment; query generation; auto-completion; market concentration (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/mksc.2024.1121 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:44:y:2025:i:3:p:516-524

Access Statistics for this article

More articles in Marketing Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().