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Monitoring Human Website Interactions for Online
Stores
Tomasz Zdziebko 1 and Piotr Sulikowski 2
1 University of Szczecin, Faculty of Economics and Management, ul. Mickiewicza 64,
71-101 Szczecin
tomasz.zdziebko@wneiz.pl
2 West Pomeranian University of Technology, Faculty of Information Technology and
Computer Science, ul. Zolnierska 49, 71-210 Szczecin
psulikowski@wi.zut.edu.pl
Abstract. The convenience of online shopping is an attractive benefit for cus-
tomers. At the same time, online purchase process is often complicated. As a
result, some customers have difficulty with or even fail to complete the process.
This article presents a tool for detailed monitoring users' interaction with shop-
ping websites. Data collected can be used for many purposes, including interface
and content adaptation. By means of personalization, a website can automatically
adapt to suit the needs of a particular user, thus vastly improving human media
interaction and its efficiency. In this article the human-website interaction moni-
toring tool ECPM is presented and sample results based on selected B2C stores
are discussed.
Keywords: human website interaction, e-commerce, preference modeling.
1
Introduction
Online shopping has been developing rapidly in recent years. However, besides many
advantages, this kind of shopping presents some difficulties. One of them is that it
often proves difficult for online shopping novices to use certain ecommerce sites and
immerse in the online world without assistance. For some people the process of pur-
chasing goods online may be perceived as too complicated. Recently user experience
(UX) and usability factors have started to play the main role in website design - to
meet the needs of real users. There are a few possible ways of determining those
needs, including asking the users explicitly, or observing the interaction implicitly.
Unfortunately explicit questioning of online shoppers disrupts their normal reading
and browsing behaviours [1,2]. Implicit measures are generally less accurate than
explicit ones [1], but they are usually available in large quantities and can potentially
be acquired without any extra time or effort from the user. Moreover, inobtrusive
implicit user monitoring allows them to focus normally on tasks performed and does
not require special motivation to continuously provide explicit ratings [3,4,5], even
when the possible benefits are clear, e.g. personalized interface in the future. Implicit
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