To read this content please select one of the options below:

Modeling user preferences in online stores based on user mouse behavior on page elements

Saeid SadighZadeh (Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran)
Marjan Kaedi (Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran)

Journal of Systems and Information Technology

ISSN: 1328-7265

Article publication date: 25 January 2022

Issue publication date: 11 April 2022




Online businesses require a deep understanding of their customers’ interests to innovate and develop new products and services. Users, on the other hand, rarely express their interests explicitly. The purpose of this study is to predict users’ implicit interest in products of an online store based on their mouse behavior through various product page elements.


First, user mouse behavior data is collected throughout an online store website. Next, several mouse behavioral features on the product pages elements are extracted and finally, several models are extracted using machine learning techniques to predict a user’s interest in a product.


The results indicate that focusing on mouse behavior on various page elements improves user preference prediction accuracy compared to other available methods.

Research limitations/implications

User mouse behavior was used to predict consumer preferences in this study, therefore gathering additional data on user demography, personality dimensions and emotions may significantly aid in accurate prediction.


Mouse behavior is the most repeated behavior during Web page browsing through personal computers and laptops. It has been referred to as implicit feedback in some studies and an effective way to ascertain user preference. In these studies, mouse behavior is only assessed throughout the entire Web page, lacking a focus on different page elements. It is assumed that in online stores, user interaction with key elements of a product page, such as an image gallery, user reviews, a description and features and specifications, can be highly informative and aid in determining the user’s interest in that product.



The authors would like to express their deepest appreciation to the “Cognitive Science and Technologies Council of Iran” for the financial support provided through research grant no. 5943.


SadighZadeh, S. and Kaedi, M. (2022), "Modeling user preferences in online stores based on user mouse behavior on page elements", Journal of Systems and Information Technology, Vol. 24 No. 2, pp. 112-130.



Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

Related articles