Title
User Intent, Behaviour, and Perceived Satisfaction in Product Search.
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.
Year
DOI
Venue
2018
10.1145/3159652.3159714
WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining Marina Del Rey CA USA February, 2018
Field
DocType
ISBN
Search engine,Information retrieval,Computer science,User intent
Conference
978-1-4503-5581-0
Citations 
PageRank 
References 
9
0.47
27
Authors
5
Name
Order
Citations
PageRank
Ning Su1233.63
Jiyin He232926.45
Yiqun Liu31592136.51
Min Zhang41658134.93
Shaoping Ma51544126.00