Web Systems Design and Online Consumer Behavior [Electronic resources] نسخه متنی

Background: Personalization Systems

Most of the technologies and tools that companies use to manage their relationship with their
customers usually fall under the banner of Customer Relationship Management (CRM) System. Even
though personalization is just one piece of the CRM pie, it is a very crucial piece as effective
personalization significantly enhances the ability of the organization to initiate a discourse with
its customers to the point where any and all of these dialogues are seamlessly integrated with the
database’s historical and transactional information. Based on the data stored in these databases
and recent history (the pages customers viewed in the last session), Web sites automatically
attempt to improve their organization and presentation of content. These Web sites, armed with a
host of appropriate tools — including intelligent agents, recommendation engines and the like —
attempt to anticipate the context of the interaction with their customers and personalize each
customer’s shopping experience (Andre & Rist, 2002; Billsus, Brunk, Evans, Gladish, &
Pazzani, 2002).

Personalization is a process of providing special treatment to a repeat visitor to a Web site
by providing relevant information and services based on the visitor’s interests and the context of
the interaction (Chiu, 2000; Cingil, Dogac, & Azgin, 2000). Personalization is needed to
successfully manage customer relationships, promote the right product the customer is interested
in, and manage content. Most of the advanced personalization might require sophisticated data
mining techniques and the ability to display dynamic content without seriously compromising system
resources (dynamic display of content will usually mean increased download time).

There are a few well-known techniques for personalization. Rules-based personalization
modifies the content of a page based on specific set of business rules. Cross-selling is a classic
example of this type of personalization. The key limitation of this technique is that these rules
must be specified in advance. Personalization that uses simple filtering techniques determines the
content that would be displayed based on predefined groups or classes of visitors and is very
similar to personalization based on rules-based techniques. Personalization based on content-based
filtering analyzes the “contents of the objects to form a representation of the visitor’s interest”
(Chiu, 2000). This would work well for products with a set of key attributes. For example, a Web
site can identify the key attributes of movies (VHS, DVD) such as drama, humor, violence, etc., and
can recommend movies to its visitors based on similar content. Personalization based on
collaborative filtering offers recommendations to a user based on the preferences of like-minded
peers. To determine the set of users who have similar tastes, this method collects users’ opinion
on a set of products using either explicit or implicit ratings (Chiu, 2000). Please see
Figure
8-1 for an illustration of how a Web site could use all three personalization methods to
best serve the customer.

Figure 8-1: Overview of
personalization techniques