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ventions. The company could have provided special incentives to agents to
keep customers who were at risk”a win-win situation for everyone involved.
In such agent-based relationships, data mining can be used not only to under­
stand customers but also to understand agents.
Indirection occurs in other areas as well. For instance, mutual fund compa­
nies sell retirement plans through employers. The first challenge is getting the
employer to include the funds in the plan. The second is getting employees to
sign up for the right funds. Ditto for many health care plans at large companies
in the United States.
Product manufacturers have a similar problem. Telephone handset manu­
facturers such as Motorola, Nokia, and Ericsson, would like to develop a loyal
customer base, so customers continue to return to them handset after handset.
Automobile manufacturers have similar goals. Pharmaceutical companies
have traditionally marketed to the doctors who prescribe drugs rather then the
people who use them, although drugs such as Viagra are now also being mar­
keted to consumers. Another good example of a campaign for a product sold
indirectly is the “Intel Inside” campaign on personal computers”a mark of
quality meant to build brand loyalty for a chip that few computer users ever
actually see. However, Intel has precious little information on the people and
companies whose desktops are adorned with their logo.

Customer Life Cycle
When thinking about customers, it is easy to think of them as static, unchang­
ing entities that compose “the market.” However, this is not really accurate.
Customers are people (or organizations of people), and they change over time.
Understanding these changes is an important part of the value of data mining.
These changes are called the customer life cycle. In fact, there are two cus­
tomer life cycles of interest, as shown in Figure 14.2. The first are life stages.
For an individual, this refers to life events, such as graduating from high
school, having kids, getting a job, and so on. For a business customer, the life
cycle often refers to the size or maturity of the business. The second customer
life cycle is the life cycle of the relationship itself. These two life cycles are
fairly independent of each other, and both are very important for business.
Data Mining throughout the Customer Life Cycle 455

) p

r e cl e
ti o

om fe C

cu r L
New Customer
of to m
se C u



Marriage Children Working Retired

Customer's Life Cycle
(phases in the lifetimes of customers)
Figure 14.2 There are two customer life cycles.

The Customer™s Life Cycle: Life Stages
The customer™s life cycle consists of events external to the customer relation­
ship that represent milestones in the life of each individual customer. These
milestones consist of events large and small, familiar to everyone.
The perspective of the customer™s life stages is useful because people”even
business people”understand these events and how they affect individual cus­
tomers. For instance, moving is a significant event. When people move, they
often purchase new furniture, subscribe to the local paper, open a new bank
account, and so on. Knowing who is moving is useful for targeting such indi­
viduals, especially for furniture dealers, newspapers, and banks (among
others). This is true for many other life events as well, from graduating from
high school and college, to getting married, having children, changing jobs,
retiring, and so on. Understanding these life stages enables companies to
define products and messages that resonate with particular groups of people.
For a small business, this is not a problem. A wedding gown shop special­
izes in wedding gowns; such a business grows not because women get mar­
ried more often, but through recommendations. Similarly, moving companies
do not need to encourage their recent customers to relocate; they need to bring
in new customers.
456 Chapter 14

Larger businesses, on the other hand, rarely have business plans that focus
exclusively on one life stage. They want to use life stage information to
develop products and enhance marketing messages, but there are some com­
plications. The first is that customers™ particular circumstances are usually not
readily available in corporate databases. One solution is to augment databases
with purchased information. Of course, such appended data elements are
never available for every customer, and, although such appended data is read­
ily available in the United States, it may not be available in jurisdictions with
different privacy laws. And, such external sources of data indicate events that
have occurred in the past, making the customer™s current life stage a matter of
Even when customers go out of their way to provide useful information,
companies often simply forget it. For instance, when customers move, they
provide the new address to replace the old. How many companies keep both
addresses? And how many of these companies then determine whether the
customer is moving up or moving down, by using appended demographics or
census data to measure the wealth of the neighborhood? The answer is very
few, if any.
Similarly, many women change their names when they get married and pro­
vide such information to the companies they do business with. At some point
after two people wed, the couple starts to combine their finances, for instance
by having one checking account instead of two. Most companies do not record
when a customer changes her name, losing the opportunity to provide tar­
geted messaging for changing financial circumstances.
In practice, managing customer relationships based on life stages is difficult:
It is difficult to identify events in a timely manner.

Many events are one-time, or very rare.

Life stage events are generally unpredictable and out of your control.

These shortcomings do not render them useless, by any means, because life
stages provide a critical understanding of how to reach customers with a par­
ticular message. Advertisers, for instance, are likely to include different mes­
sages, depending on the target audience of the medium. However, in the
interest of developing long-term relationships with customers, we want to ask
if there is a way to improve on the use of the customer™s life cycle.

Customer Life Cycle
The customer life cycle provides another dimension to understanding cus­
tomers. This focuses specifically on the business relationship, based on the
observation that the customer relationship evolves over time. Although each
Data Mining throughout the Customer Life Cycle 457

business is different, the customer relationship places customers into five
major phases, as shown in Figure 14.3:
Prospects are people in the target market who are not yet customers.

Responders are prospects who have exhibited some interest, for instance,

by filling out an application or registering on a Web site.
New customers are responders who have made a commitment, usually

an agreement to pay, such as having made a first purchase, having
signed a contract, or having registered at a site with some personal
Established customers are those new customers who return, for whom the

relationship is hopefully broadening or deepening.
Former customers are those who have left, either as a result of voluntary

attrition (because they have defected to a competitor or no longer see
value in the product), forced attrition (because they have not paid their
bills), or expected attrition (because they are no longer in the target
market, for instance, because they have moved).
The precise definition of the phases depends on each particular business.
For an e-media site, for instance, a prospect may be anyone on the Web; a
responder, someone who has visited the site; a new customer, someone who
has registered; and an established customer a repeat visitor. Former customers
are those who have not returned within some length of time that depends on
the nature of the site. For other businesses, the definitions might be quite dif­
ferent. Life insurance companies, for instance, have a target market. Respon­
ders are those who fill out an application”and then often have their blood
taken for blood tests. New customers are those applicants who are accepted,
and established customers are those who pay their premiums for insurance

Value Voluntary
Target New High
Responder Customer
Market Customer Potential

Low Value
Rest of Churn
Figure 14.3 The customer life cycle progresses through different stages.
458 Chapter 14

Subscription Relationships versus Event-Based
Another dimension of the customer life-cycle relationship is the commitment
inherent in a transaction. Consider the following ways of being a telephone
Making a call at a payphone

Purchasing a prepaid telephone card for a set number of minutes

Buying a prepaid mobile telephone

Choosing a long distance carrier

Buying a postpay mobile phone with no fixed term contract

Buying a mobile phone with a contract

The first three are examples of event-based relationships. The last three are
examples of subscription-based relationships. The next two sections explore
the characteristics of these relationships in more detail.

T I P An ongoing billing relationship is a good sign of an ongoing subscription
relationship. Such ongoing customer relationships offer the opportunity for

engaging in a dialog with customers in the course of business activities.

Event-Based Relationships
Event-based relationships are one-time commitments on the part of the cus­
tomer. The customer may or may not return. In the above examples, the tele­
phone company may not have much information at all about the customer,


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