Raymond Chandler, an American author, once said, "Such is the brutalization of
commercial ethics in this country that no one can feel anything more delicate than the velvet
touch of a soft buck". Some may say that "business ethics" is an oxymoron. In the
business where competition is fierce and a "survival of the fittest" mentality seems to rule the
jungle, ethics is a controversy that will forever be debatable. And as technology continues to
change at an astounding rate, survival is not only de
pendant on the wisdom and prudence of our
business leaders, but also the code of ethics in which they choose to adopt. All areas of business
seem to have ethical issues that are debated over, not excluding data mining.
According to Laudon and Traver, auth
ors of E
commerce, data mining is "a set of
different analytical techniques that look for patterns in the data of a database or data warehouse,
or seek to model the behavior of customers" (370). The gathering, utilization, and analysis of
data to better u
nderstand consumers has been common practice for many years. However, with
the progression of technology, methods such as data mining have evolved in the attempt to make
the analysis of consumer and consumer behavior more precise. Just as data mining tak
warehousing one step further, web mining takes data mining one step further. Web mining can
use the same definition as data mining, except that web mining is conducted within the realm of
the internet and world wide web. This paper will explore t
he purpose, methods, and ethical
issues of web mining. Although, data mining and web mining are so similar in nature that the
two terms could be treated synonymously, for the purpose of this paper, web mining and data
mining will be used to differentiate
between internet data mining and traditional data mining,
Why do companies use data mining techniques? One of the buzz words that has existed
in the business world for years and still does today is competitive advantage. A competiti
advantage is what a firm has that they do better than any one else. An example would be
producing a high quality product or providing a high quality service at price lower than any of
their competitors. Some consider the ability to recognize strengths
, weaknesses, opportunities,
and threats, which is termed the SWOT analysis, better than competitors a competitive
advantage. SWOT analysis is also referred to as visibility. One of the determinants of good
visibility is an organization's measurement sys
tem and practices; it is the information that gets
noticed, captured, analyzed, and acted upon (Hendrix 41). Visibility and the competitive
advantage that it offers an organization can be applied not only to the firm's overall strategic
plan, but also to
areas within the strategic plan, such as their marketing strategy.
Marketing strategies have in past been focused on gaining market share, which is a
measure of the number of customers. This philosophy that the higher number of customers that a
firm can a
cquire, the higher the market share, which results in higher profits has shifted to a
philosophy based on customer share and not market share. The customer
demonstrates that a firm becomes more profitable when they focus their attention o
share of a customer's business and not the number of customers they acquire (Danna 377). This
philosophy is the foundation behind customer relationship management. It is argued that
business and business
consumer enterprises hav
e to build better and more
profitable relationships with their customers in a customer
centric economy" (Danna 374).
Customer relationship management is basically getting to know each customer.
Typically this is done by creating a profile on every custome
r. A customer profile can contain
data regarding product and usage, demographics, psychographics, profitability measures, history
of contacts with the customer, and marketing and sales information based on customer responses
(Laudon and Traver 375). It s
eems like a lot of time and money could be spent on creating this
kind of profile on every single customer, which compared to the benefit may not be cost
effective. Arguably for some organizations the benefits may outweigh the costs, but for others
areto Principle may be the approach in sifting through customers and deciding which
customers to target. The Pareto Principle, applied to customer relationship management, simply
states that eighty percent of a firm's profit results from twenty percent of
their customers. So, if
a firm is able to identify the most profitable twenty percent of their customers and create a
customer profile on each in order to engage in one
one dialogue with each of those
customers, the firm would be considered as having
an effective customer relationship
management system (Danna 377).
This notion of gathering data on customers in order to engage with them one
the tenet behind the marketing strategy of personalization. Personalization segments the market
groups of customers, but segments the market by individual customers. The goal of
personalization is to provide customers "with what they want or need without requiring them to
ask for it explicitly" (Mulvenna, Anand, and Buchner 122). Personalization is
a system of
learning the patterns, habits, and preferences of customers. In order to achieve personalization
within a customer relationship management system, the techniques of data mining and web
mining are utilized.
The number of companies using data m
ining techniques in order to personalize their
marketing strategy is growing at a fast pace. Only two years ago in 2001, over half of Fortune's
top 1000 companies had plans to utilize data mining technology (Danna 375). Data mining and
web mining involve
not only gathering information, but also extracting predictive information
from databases looking for patterns, as well as the cause of those patterns. This process requires
sophisticated and complex analytical tools, but more importantly this process re
who have advanced skills in data analysis and business knowledge. The analytical tools
necessary to perform such complex analysis can be obtained through companies specializing in
personalization software and as the popularity of data mining
and web mining increases, so does
the simplicity of software (Brandel 68).
What methods are used to gather the vast amounts of information used in data mining and
web mining? In discussing methods used for mining data, it is useful to differentia
data mining and web mining. Another way to look at the difference in methods is to think of the
methods as offline and online. Data mining methods have been used for years to better enable
organizations to segment their customers. Some of tho
se offline methods include call centers,
product registration cards, point
sale transactions, and mail
in surveys. In traditional data
mining techniques the information gathered from these offline methods was used to segment
customers into groups. As
discussed earlier, marketing strategies are moving away from
segmenting customers into groups and moving towards segmenting customers into individuals.
Although the offline methods are still utilized, the Internet has provided a new resource for
Web mining collects data through transaction and navigational activities performed on
the internet. Users often browse web sites to comparison shop, to gather information for
research purposes, to get current news and financial information, and for a
variety of other
reasons. The navigation that occurs during a users browsing is documented through an online
method called click
stream records mouse clicks of users and records what users
do while viewing a web site. The information gathe
red from click
stream becomes the
psychographic part of the customer profile. It is the online version of behavioral observation.
Another method of web mining is in the form of cookies. Cookies are stored on a user's
computer that helps to identify the
user and the user's preferences. A user can easily deleted
cookies stored in their directory, but many users don't even know they exist. A form of cookies
that is used by many researchers are data
augmented URL strings or Web bugs. The URLs
formation such as passwords, personal information, and survey information. The
difference between Web bugs and cookies, which is an advantage to researchers, is where the
data is stored. Cookies are stored on the users computer, whereas Web bugs are stor
ed on the
researchers server. (Miller and Dickson 153)
As technology changes so will the methods of gathering information used in web mining
technology. One of the emerging technologies are wireless devices. Wireless technologies are
being utilized to em
bed sensors in products and processes in order to gain new insights in
consumer patterns, behaviors, and preferences. It is predicted that sensors will be embedded in
virtually all products including vehicles, vending machines, clothing, and food products
With all these existing and emerging technologies designed to gather information on
consumers, the prominent question that is debated is "are these methods of gathering the
information and the way in which the information is u
sed ethical?" Ethics have been debated
over for centuries and business ethics for decades. So, when new technologies are introduced to
the business world, a debate of ethics is bound to be not far behind. Business ethics have many
subdivisions. The eth
ics that this paper is concerned with are marketing ethics. There are said to
be three tenets behind marketing ethics. They include 1) both the buyer and seller must agree to
and be adequately informed of what is being purchased and how much the purchase
price is, 2)
neither buyer nor seller is impaired through coercion, severely restricted alternatives, or other
constraints on their ability to choose, and 3) both buyer and seller are capable of making a
rational decision concerning the transaction (Stoll
122). These tenets will be used as a premise
for this discussion regarding ethics in data mining. A summation of this idea is give by Mary
Lyn Stoll in her article "The Ethics of Marketing Good Corporate Conduct". She says that in the
evaluation of the
ethical character of a person or organization "it is of the utmost importance that
deception, and non
coercion are maintained (Stoll 126). Another approach to the
concept of marketing ethics is to ensure that the value of right conduct does
secondary to the generation of profit. Considerations of more than the impact on the bottom line,
is a recommendation given to those who bear responsibility in designing and implementing a
marketing strategy (Danna 386).
The third tenet of mark
eting ethics regarding the ability to make a rational decision seems
to the most controversial of the three tenets. Some researchers argue that rationality is not
compromised by marketing tactics as long as the individual is consciously aware that their
esires are being fostered by those tactics. On the other hand, some argue that an individual's
rational is defined by their beliefs, desires, and attitudes. So, when these beliefs, desires, and
attitudes are impacted by marketing tactics, an individual's
ability to make rational decisions is
suppressed. (Stoll 122
123) The core of this debate seems to be focused on the degree of
influence marketing tactics have on individuals and to what degree their rationality is impacted.
Because the Internet has bec
ome a part of so many aspects of our lives it is not hard to determine
that web mining activities used in personalization strategies are going to heavily impact our
lives. Whether or not our rational is impacted is a discussion outside the realm of this p
The concerns regarding ethical conduct in data mining and web mining techniques are
not confined within limits of the previously mentioned tenets, but also encompass issues
surrounding trust and privacy. Can consumers and internet users trust that 1
) they are aware of
the content of the information about them that is being mined and 2) is the information that is
gathered about them is being utilized by researchers and corporations in an ethical manner?
Some say that researchers and corporations cond
uct should at the very least inform consumers
and internet users of the type of information that is gathered about them and the ways in which
the information will be used (Danna 386). One suggested approach is to use the Kantian
standard of the "Golden Ru
le", which cautions us not to do anything that we would want to have
done to us. An excerpt from "On
line Market Research" summarizes the "Golden Rule" standard
by stating, "Whatever the research modality, market researcher have an obligation to conduct
esearch in a responsible manner, recruiting with respondent opt
in and opt
respondent confidentiality, being respectful of people's time, and protecting individual privacy"
(Miller and Dickson 152).
Assuming the approach to an ethical marke
ting code is the "Golden Rule" standard, some
of the questions to ask researchers and marketers would be are you willing to pay higher price
than your neighbor for purchasing the same product? Or, do you think it is fair that you are not
offered or given
the ability to purchase certain products because of the neighborhood you live in?
Often times consumers are forced to pay a higher price than their neighbor or are not given the
same purchasing opportunities as other based on their demographics. Although
some argue that
price and product discrimination is necessary to keep buyers from shifting, this type of market
discrimination is considered by some to be unethical (Danna 381). Price discrimination is not a
new concept and there are different levels of
discrimination. Ethical concerns may not be raised
when considering third
degree price discrimination, such as student or senior citizen discounts.
Ethical concerns may not even be an issue when considering second
degree price discrimination,
such as the
different prices airlines charge based on various fare restrictions. However, first
degree price discrimination, which requires a severe exploitation of price sensitivity between
consumers, is often considered unethical.
degree price discrimina
tion is made much easier the more advanced data mining
and web mining techniques become. The more personalized the consumer profiles become the
easier it will be for organizations to engage in first
degree price discrimination. The advocates
of price dis
crimination argue that versioning content and price of products is necessary in order
to maximize profitability. However, those who discourage price discrimination argue that it
would restrict access to high quality products so that lower income consumers
would have no
choice but to settle for low quality products (Danna 383).
Excluding consumers from a market all together is another way the data contained in
consumer profiles is used. Based on their profile, some consumers may not even have the option
purchase a good or service, regardless of the price. This kind of discrimination is referred to
as redlining. Whether the discrimination occurs in a physical location (redlining) or on a web
site (weblining), some consider the practice unethical because
it is not treating consumers as
individuals who are capable of making rational decisions in their own interest (Danna 384).
Some of the ethical concerns I have discussed so far are just barely touch the surface of
the ramifications of engaging in personal
ization marketing using data mining and web mining
techniques. However, based on the research presented some questions that may guide the ethical
conduct of market researchers, data miners, and organizations include:
Is honesty, non
deception, and non
rcion being maintained?
Has the value of right conduct become secondary to the generation of profit?
Is the rationality of consumers being compromised?
Are consumer and internet users being informed of the type of information that is gathered
about them an
d the ways in which the information will be used?
Is research conducted in a responsible manner, recruiting with respondent opt
in and opt
protecting respondent confidentiality, being respectful of people's time, and protecting
s the price sensitivity between consumers being severely exploited?
Are consumers being treated as individuals who are capable of making rational decisions in
their own interest?
Although these questions may be useful in evaluating ethical conduct and app
is also important to consider the voice of the consumer. Personalization Consortium is an
advocacy group formed to promote the responsible use of technology used in personalization and
customer relationship management. The consortium conducte
d a survey in March of 2000 to
identify the opinions of 4,500 Web users on personalization and online privacy. The survey
results indicate that "73 percent of consumers find it helpful and convenient when a Web site
"remembers" basic information about the
m." When developing a code of ethics, an organization
should also consider the general opinion of the average consumer.
With competition in today business world, it is understandable that companies find it
necessary to better utilize data minin
g and web mining techniques in order to personalize their
market strategy. Especially for those companies that have adopted a customer relationship
management approach to marketing. The technology that allows the personalization and one
approach is changing rapidly; faster than the laws can be developed to regulated
their application. So, it is often left to the discretion of the market researchers, data miners, and
organizations as to what type of information will be gathered on consume
rs and how that
information will be utilized. However, the consumer must take some responsibility as well.
Consumers are held responsible to read privacy statements, learn how to protect themselves, and
report violations. Technology will continue to gro
w and change; and ethics will ride along with
it. May we all conduct ourselves as if what we do today will determine our fate tomorrow.
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