Mardekian 1
Table of Contents
Abstract
Gone Surfin’
Virtual Markets
Personalizing Personalization
Discussion Goals
Defining Personalization
Types of Personalization
Personalization Packages
Personalized Technology
In the Beginning: Defining the users
Mentors
Filtering Techniques
Serving Personalized Content
Business’ View of Personalization
Considerations
Using Metrics
Misconceptions
User’s View of Personalization
Custom Tools
Seeking Something?
Privacy Please!
My Yahoo!: A case study
Personalizing the Future
Appendix I: Sample User Survey
References
Abstract
The World Wide Web is fast becoming the central location for goods, service, and information. The population of the Web is also increasing in diversity as well. No longer is this technology for military personal, college professors, and college students. Content personalization individualizes Web experiences; just as the online population is becoming more diverse, so too is the type of content that needs to be displayed. Responses to surveys and data collected while navigating through a website are compiled and analyzed to present content which exhibits the same (or similar) characteristics. The same content does not and cannot apply to everyone. Content personalization is also useful for helping businesses evaluate their website’s design. User preferences drive the content. Personalization is the key to future Web success.
Gone Surfin’
Need to do research for a term paper? Try an online information archive. Looking for a new outfit? Try one of the many online clothing merchants. Looking to finance or lease a new car? Visit the automakers at their official sites to customize a model, locate a dealer, and/or negotiate a price. Want to trade some stock? Want to buy a music CD? How about rent an apartment or get a second mortgage? Or how to get an Elvis impersonator to appear at the next company picnic? Find it all online.
World Wide Web technology is at the forefront of the burgeoning communication revolution. What once seemed reality only in science fiction has now become the focal point of today’s society. No longer is there an exclusive dependence upon POTS—plain old telephone service—to be the prevalent link to products, services, and the rest of the outside world. Many have migrated towards accessing such resources through the use of various electronic devices; among the most widely used are personal computers, cellular phones, and handheld personal data assistants. What needed to be accessed a few years ago via telephone from one’s residence can now be done from almost anywhere, anytime.
According to the 1999 State of the Internet Survey by USIC (United States Internet Council), “From 1992 until now, a year in the development of the Internet is likened to five to ten years of evolution of other media. The backbone of the Internet now doubles in capacity every 100 days (1).” According to a Network Wizards survey discussed in the same commentary, as of January 1999 the Internet has grown to over 43 million hosts worldwide; it is projected that the number of hosts can grow to 100 million by 2001 (Figure 1). A host is considered any computer that is reachable through the Internet; it cannot be behind a firewall. The host must have a unique address and have the capacity of providing information in addition to access (USIC 3).
As information becomes more and more abundantly available with the click of a mouse, it is becoming vital that site masters design content to reflect the users’ individual needs. No longer is the Web exclusively surfed by research scientists, military personnel, and college students.
The Web’s constituents have expanded to include senior citizens, at-home mothers, and many other age, ethnic, race, and economic classes. Figure 2 represents the breakdown of ethnic group use for the year 1999 with a projection for the year 2000. Such diversity in Web user demographics is case and point for the vast disparity in the range of tastes, comprehension, and/or level of computer proficiency. In many instances offering the same content to all visitors does not suffice. There is little guarantee that the information presented will meet everyone’s needs; although, this may have sufficed during the earliest days of the Internet when the users shared more similarities. Users, even the most casual, “need to be assured that the site has all the information they need, and that they are likely to retrieve that information. Users do not want to waste time hunting or wading through an ocean of material (Hysell 167).”
One cannot assume that the guests who take advantage of the Web’s resources today and tomorrow are able to properly navigate the site’s interface to find the information, products, or services
they are seeking. Chances strongly favor that a sampling of Web surfers are not well versed in any of these methods. A perceived loss of control may cause the user to resist the technology. Instead of Internet usage growth, there may be a regression in the use of available resources.
Virtual Markets
As US and worldwide use of the Internet continues to boom, it is also expected that electronic commerce activity will flourish. International Data Corp (IDC) estimates that the worldwide volume (in US dollars) of business-to-business (b-to-b) electronic commerce in 1998 registered $27.4 billion with volume growth projected at $978.4 billion for 2003. IDC also estimates that the worldwide volume (in US dollars) of business-to-consumer (b-to-c) sales will rocket to $177.7 billion by 2003. In 1998, $31 billion in b-to-c sales transactions occurred with $50.7 billion projected for the year 2000 (USIC 12-13). In order to sustain or exceed such projected levels of growth, there needs to be a method of insuring that consumers, whether they be other businesses or private patrons, are satisfied in their efforts to find such goods and services.
Personalizing Personalization
Discussion Goals
Content personalization may be the key to meeting the individual needs of those who currently surf the Web and attract those who have yet to catch its wave. Conceptually, accommodating the individuality of a site’s visitors seems trite. Give the visitors what they want and they are happy. Realistically, personalization is not child’s play. It is quite difficult to determine what it is that the individuals are seeking. Since there is a wide range of personal tastes that need to be considered, how can the content of a site address all of those differences? The ensuing discussion will discuss the following topics in effort to shed light on the many facets of content personalization and what it all means for the future of websites and their design:
Definition of personalization: What content personalization is and what it all means
Types of personalization: There are four types of personalization ranging in the most simple (name recognition) to the most complex (preference based) to implement.
Technology behind personalization: How does personalization do its thing?
Business aspects of personalization: What businesses need to consider.
User aspects of personalization: What users need to consider. Includes a discussion of privacy issues.
Real world examples of personalization: Some efforts to date.
Personalization’s future: Is there one? If so, what does it look like?
Defining Personalization
Determining an exact definition for personalization is a bit of a conundrum. Personalization tends to be defined according to how it is implemented by various organizations and individuals. Kramer et al write:
Personalization is a toolbox of technologies and application features used in the design of an end-user experience. Features classified as “personalization” are wide-ranging, from simple display of the end-user’s name on a Web page, to complex catalog navigation and product customization based on deep models of users’ needs and behaviors. (45).
Personalization.com, a website dedicated to creating “a clearinghouse of objective information about [Web] personalization,” offers the following definition:
As used on the Internet, the term Personalization [sic] has come to mean “person-specific content.” Personalized content may be advertising, items for sale, screen layout, menus, news articles, or anything else we see via the Internet.
Personalization is the result of technology integrated into a website that allows the server to modify what is presented to each viewer. With personalization technology working, two individuals accessing the same website simultaneously may see two completely different sets of information. (Personalization.com FAQs)
Many ponder whether or not there is indeed opportunity behind personalization’s hype. Riecken writes in “Personalized Views of Personalization”:
I suggest that personalization is not a silver bullet, but instead is part of the following prime directive for business: Give the customer a high-quality product or service they really need and can use at the “best” (lowest) price, and give the customer high-quality service with integrity. Do this and the result will be successful corporate branding and customer loyalty.
Simply stated from one point of view, personalization is about building customer loyalty by building a meaningful one-to-one relationship; by understanding the needs of each individual and helping satisfy a goal that efficiently and knowledgeably addresses each individual’s need in a given context. To extend this point, it is about the mapping and satisfying of a user’s/customer’s goal in a specific context with a service’s/business’s goal in its respective context. Clearly, this is a difficult problem. (27)
Belkin adds that personalization is an important method needed to help individuals find what they do not know. “When people engage in information-seeking behavior, it’s usually because they are hoping to resolve some problem, or achieve some goal, for which their current state of knowledge is inadequate (Belkin 60).”
Types of Personalization
There are four major forms in which content personalization can be found (as outlined by Personalization.com). These methods are not exclusive and can, and often do, coexist. Some are simpler to implement than others. In many cases the concepts of one are built upon and made more robust in another.
Name Recognition: When a user starts a session either by logging in to the site or by simply returning to a page that has been previously visited (through the use of session tracking technology, or cookies), they are addressed by the name that the system knows them as (e.g., login name, first name, etc.). Most people like to be acknowledged by name—it tends to give the notion that that individual is not just another number and that they are important. This is the simplest of all to implement.
Check-box: In this case, information is provided by the user. Questionnaires, surveys, registration forms, and other solicitation methods are used to gather information about the user’s likes, dislikes, and any other factors that can help paint a picture of that individual. For example, a registration form may ask a user from which vendor the item was purchased, where the item will be used (home, office, gift, etc.), and if the user has purchased this item as an upgrade or replacement. This information is used to custom tailor content based on the user’s responses.
Segmentation and Rules: Demographic, geographic, psychographic profiling, or other methods of information collection are used to divide or segment the entire user population into smaller groups, or pools. Data such as income level, geographic location, and buying history is aggregated and processed and the results divvy the users into appropriate groups. Content is then dished out according to “if this, then that” rules processing.
Preference-based (Affinity): This is perhaps the most complicated of the four forms to implement. The code behind the scenes of the site needs to be smart and adapt quickly and smoothly to changes in the population; thus these systems are usually updated in real time. Preference-based personalization attempts to comprehend a user’s affinity for certain items, goods, or services based on previous behavior of not only that user but also similar users. Complex statistical algorithms are needed in order to make the most accurate predictions as possible. Resulting is a profile of the user and a set of predictions matching what the user would (possibly) want to view or buy next.
Personalization Packages
Due to the complex nature of content personalization, in-house development of such software is not a normal occurrence. There are several personalization packages on the market; many are frameworks that require further customization for each environment in which they are employed. Such products include Allaire’s Cold Fusion (allaire.com), Black Pearl’s Knowledge Broker (blackpearl.com), Macromedia’s LikeMinds Personalization Server (macromedia.com), and NetPerception’s Recommendation Engine Suite (netperceptions.com). These products, as well as many others available on the market, encompass a wide range of functionality, expandability, and ease of use. Some are easier to implement than others and some come at a much cheaper price than others. The following discussion will outline concepts general to personalization’s technology. There is a wide range of capability that each of these products has to offer; many of these products are so complex that they are worthy of their own discussion. For many, the documentation consists of several volumes. Visit for descriptions of the various personalization products available and links to vendor’s sites.
Personalized Technology
In the Beginning: Defining the users
Websites “have become central repositories of information for many products and services around the world (Fuccella 69).” An issue that plagues site architects is how to serve the right content to users who have diverse sets of tastes, values, wants, and needs. Also to be considered is how to turn users into loyal followers of a site. Coaxing them to hit the site is not nearly as difficult as retaining them. It is difficult for site architects to predict the type of content the target audience(s) is seeking when there is little known about them (other than who they are). A designer is incapable of perceiving exactly what each individual is seeking when he or she visits a site.
“As with any disorganized assortment of tools—especially fascinating new tools—designers are often drawn into the trap of trying to find uses for the tools, and deploying the coolest new features, forgetting the primary focus should be on providing value to the end user (Kramer 45).” In order to implement the technology behind personalization the designers must develop a “crisp audience definition (Fuccella 69).” Marketing departments determine who the user group is, but it is the designers’ collective responsibility to paint the accurate picture of just who the real user group is and the characteristics they embody. This is difficult as the designers must figure out how to deliver the site’s content to the user and make sure that the organization achieves its goals. The way to do so is to compile profiles of the actual users who hit the site and learn about them from them. Thus it is necessary to constantly probe the user pool.
Typically individual user profiles contain both demographic and transaction data. Demographic data describes who the user is—gender, birth date, education, salary, type of music listened to, favorite stores, etc. (Adomavicius 377). Generally speaking, this includes anything that can outline an individual’s likes, dislikes, and values. Usually this data is collected using surveys, e.g., check boxes, fill-in. Often this data is collected with the initial visit/login to a particular site and becomes a permanent part of the user’s profile. Other demographic data may be collected as needed or inferred from the types of goods, services, or information that a user selects or purchases. Transaction data describes what the user has done while navigating through the site (Adomavicius 377). For example, clickstream data reflects a particular user’s travels around the site (i.e., what a user has selected or “clicked on” with his or her mouse). It gives an indication of what types of goods, services, or information a user decided to explore.
“One of the key technical issues in developing personalization applications is the problem of how to construct accurate and comprehensive profiles of individual[s] that provide the most important information describing who the customers are and how they behave (Adomavicius 377).” Task analysis methods are employed on the profiles “to learn the impetus for users’ actions . . ., methods of completing the tasks . . ., and the ultimate intention of the user . . . (Kramer 46).” Complex statistical algorithms are used to sift through the data compilations. Not only are these algorithms intended to classify the individual users, they are intended to compare and contrast behavior patterns of different users. The results depict what a typical, generic user prefers. These results serve a dual purpose. The results of the profiling effort are reused to determine what content the personalization engine will serve tot eh users. They are also reused by those who evaluate the site’s design and content to determine if and where changes need to be made.