A Clickstream Data Analysis of the Differences between Visiting Behaviors of Desktop and Mobile Users

Abstract

Mobile devices are gaining popularity among online shoppers whose behavior has been reshaped by the changes in screen size, interface, functionality, and context of use. This study, based on a log file from a cross-border E-commerce platform, conducted a clickstream data analysis to compare desktop and mobile users’ visiting behavior. The original 2,827,449 clickstream records generated over a 4-day period were cleaned and analyzed according to an established analysis framework at the footprint level. Differences are found between desktop and mobile users in the distribution of footprints, core footprints, and footprint depth. As the results show, online shoppers preferred to explore various products on mobile devices and read product details on desktops. The E-commerce mobile application (app) presented higher interactivity than the desktop and mobile websites, thus increasing both user involvement and product visibility. It enabled users to engage in the intended activities more effectively on the corresponding pages. Mobile users were further divided into iOS and Android users whose visiting behaviors were basically similar to each other, though the latter might experience slower response speed.

Mobile vs desktop user search behaviours of the 1300K site, a Korean shopping search engine

“…The detailed description of sessions, queries and browsing activities are provided in the "Results" section. Data collection periods of previous studies were referenced for comparison purposes (Baeza-Yates et al, 2007;Bai and Cambazoglu, 2019;Jiang et al, 2018;Kamvar et al, 2009;Li et al, 2009;Song et al, 2013). Compared to the time range of data sets from previous studies, it seemed that the present study with three months' of log session data could provide a substantially large and comprehensive data set.…”

“…A few studies (Jiang et al, 2018;Song et al, 2013) investigated user click behaviours. Jiang et al (2018) analysed users' click behaviours of a Chinese e-commerce site and found that average page viewing duration of desktop users is longer than that of mobile users.…”

“…A few studies (Jiang et al, 2018;Song et al, 2013) investigated user click behaviours. Jiang et al (2018) analysed users' click behaviours of a Chinese e-commerce site and found that average page viewing duration of desktop users is longer than that of mobile users. Their study also found that users mainly viewed products through desktops, including browsing product details and providing comments, whereas users primarily used mobile devices to discover and explore products.…”

“…In particular, this research uses transaction log analyses and examines information-seeking behaviours by users of the 1300K site, a major Korean shopping search engine. This study analyses user behaviours at a shopping search engine, as "shopping" is one of the most popular topics searched on the Web (Jiang et al, 2018;Mokryn et al, 2019;Park et al, 2015;Wu et al, 2019), and the online shopping industry is growing rapidly. Online shopping may be the primary mode used by individuals during restrictive times and it becomes important to understand search behaviours using desktop or mobile devices to facilitate this experience by making it compatible with user behaviours which can be indicative of individuals' preferences.…”

“…Users of Web search engines, especially shopping search engines, are often involved with various activities, such as query searching, directory browsing, clicking search results, ordering, adding products to the shopping cart, adding products to the wish list and recommending particular products. Most previous studies of user behaviour focused on either users' query searching behaviours or click behaviours (Baeza-Yates et al, 2007;Bai and Cambazoglu, 2019;Jiang et al, 2018;Kamvar et al, 2009;Li et al, 2009;Song et al, 2013;Wu and Bi, 2017). This study differs from most previous studies in that it investigates various user behaviours, such as query searching behaviours, directory browsing behaviours and click behaviours.…”