research-article

User Intent, Behaviour, and Perceived Satisfaction in Product Search

Authors:

Shaoping MaAuthors Info & Claims

WSDM '18: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining

Pages 547 - 555

https://doi.org/10.1145/3159652.3159714

Published: 02 February 2018 Publication History

Abstract

As online shopping becomes increasingly popular, users perform more product search to purchase items. Previous studies have investigated people's online shopping behaviours and ways to predict online purchases. However, from a user perspective, there still lacks an in-depth understanding of why users search, how they interact with, and perceive the product search results. In this paper, we conduct both a user study and a log analysis to we address the following three questions: (1) what are the intents of users underlying their search activities? (2) do users behave differently under different search intents? and (3) how does user perceived satisfaction relate to their search behaviour as well as search intents, and can we predict product search satisfaction with interaction signals? Based on an online survey and search logs collected from a major commercial product search engine, we show that user intents in product search fall into three categories: Target Finding (TF), Decision Making (DM) and Exploration (EP). Through a log analysis and a user study, we observe different user interaction patterns as well as perceived satisfaction under these three intents. Using a series of user interaction features, we demonstrate that we can effectively predict user satisfaction, especially for TF and DM intents.

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Cited By

Vidal-Sepúlveda MOlivares-Rodríguez C(2024)Mediación algorítmica: sesgos en la búsqueda de información en estudiantes universitariosEuropean Public & Social Innovation Review10.31637/epsir-2024-3979(1-18)Online publication date: 19-Jul-2024
https://doi.org/10.31637/epsir-2024-397
Zhang JXie RHou YZhao XLin LWen J(2024)Recommendation as Instruction Following: A Large Language Model Empowered Recommendation ApproachACM Transactions on Information Systems10.1145/3708882Online publication date: 20-Dec-2024
https://dl.acm.org/doi/10.1145/3708882
Nam DMacvean AMyers BVasilescu B(2024)Understanding Documentation Use Through Log Analysis: A Case Study of Four Cloud ServicesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642721(1-17)Online publication date: 11-May-2024
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Index Terms

User Intent, Behaviour, and Perceived Satisfaction in Product Search
1. Applied computing
  1. Electronic commerce
    1. Online shopping
2. Information systems
  1. Information retrieval
    1. Information retrieval query processing
      1. Query intent
      2. Query log analysis

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cover image ACM Conferences

WSDM '18: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining

February 2018

821 pages

ISBN:9781450355810

DOI:10.1145/3159652

General Chairs:
Yi Chang
Jilin University, Huawei Inc.
,
Chengxiang Zhai
University of Illinois Urbana-Champaign
,
Program Chairs:
Yan Liu
University of Southern California
,
Yoelle Maarek
Amazon

Copyright © 2018 ACM.

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Published: 02 February 2018

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National Key Basic Research Program
Natural Science Foundation of China
the Netherlands Organisation for Scientific Research (NWO)

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WSDM 2018

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WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining

February 5 - 9, 2018

CA, Marina Del Rey, USA

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WSDM '18 Paper Acceptance Rate 81 of 514 submissions, 16%;

Overall Acceptance Rate 498 of 2,863 submissions, 17%

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https://doi.org/10.31637/epsir-2024-397
Zhang JXie RHou YZhao XLin LWen J(2024)Recommendation as Instruction Following: A Large Language Model Empowered Recommendation ApproachACM Transactions on Information Systems10.1145/3708882Online publication date: 20-Dec-2024
https://dl.acm.org/doi/10.1145/3708882
Nam DMacvean AMyers BVasilescu B(2024)Understanding Documentation Use Through Log Analysis: A Case Study of Four Cloud ServicesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642721(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642721
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