... that, on a technical level, the datamining effort is working and
the data is reasonably accurate. This can be quite comforting. If the data and
the dataminingtechniques applied to it are powerful ... this ideal, but the corporate data warehouse is still the most important
source of datafor analytic customerrelationship management.
The Role of DataMining
The data warehouse provides the ... What Is Data Mining? 1
Analytic CustomerRelationshipManagement 2
The Role of Transaction Processing Systems 3
The Role of Data Warehousing 4
The Role of DataMining 5
The Role of the Customer...
... level
data, 96
publications
Building the Data Warehouse (Bill
Inmon), 474
Business Modeling and DataMining
(Dorian Pyle), 60
Data Preparation forDataMining
(Dorian Pyle), 75
The Data ... 89–90
metadata repository, 484, 491
methodologies
data correction, 72–74
data exploration, 64–68
data mining process, 54–55
data selection, 60–64
data transformation, 74–76
data translation, ... dumping data, 594
forced attrition, 118
forecasting
EBCF (existing base churn
forecast), 469
NSF (new start forecast), 469
survival analysis, 415–416
former customers, customer
relationships,...
... analyzing data
on the information.
can provide value.
into actionable information
using datamining techniques.
Identify
Transform data
1 2 3 4 5 6 7 8 9 10
Measure the results
of the efforts ... of datamining in practice. Figure 2.1
shows the four stages:
1. Identifying the business problem.
2. Miningdata to transform the data into actionable information.
3. Acting on the information. ... for the first
time. These parallel database server platforms provide an excellent environ-
ment for large-scale data mining.
Interest in CustomerRelationshipManagement Is Strong
Across a wide...
...
before. The newly discovered relationships suggest new hypotheses to test
and the datamining process begins all over again.
Lessons Learned
Data mining comes in two forms. Directed datamining ... independent of the data
470643 c04.qxd 3/8/04 11:10 AM Page 87
Data Mining Applications in
Marketing and Customer
Relationship Management
4
CHAPTER
Some people find dataminingtechniques interesting ... California based on data that excludes calls to Los Angeles.
Step Six: Transform Data to Bring
Information to the Surface
Once the data has been assembled and major data problems fixed, the data...
... channel B customer a figure that is as valuable as the cost-
per-response measures often used to rate channels.
Data MiningforCustomerRelationship
Management
Customer relationshipmanagement ... Page 109
Data Mining Applications 109
Start Tracking Customers before
They Become Customers
It is a good idea to start recording information about prospects even before
they become customers. ... customer
data by beginning to track customers from their first response, even before they
become customers, and gathering and storing additional information when
customers are acquired.
Once customers...
... else for the
champion.
■■ Use the 5 percent lowest and 5 percent highest value customers for the
challenger, and everyone else for the champion.
■■ Use the 10 percent most recent customers for ... in several areas:
■■ Data miners tend to ignore measurement error in raw data.
■■ Data miners assume that there is more than enough data and process-
ing power.
■■ Datamining assumes dependency ... 11:11 AM Page 159
The Lure of Statistics: DataMining Using Familiar Tools 159
statisticians use similar techniques to solve similar problems, the datamining
approach differs from the standard...
... test set to see how well it performs.
7. Apply the model generated by the network to predict outcomes for
unknown inputs.
Fortunately, datamining software now performs most of these steps auto-
matically. ... subset of customers who
receive all three offers but are only allowed to respond to one of them. It
intends to use this information to build a model for predicting customer affin-
ity for each ... and learn from data
mimics, in some sense, our own ability to learn from experience. This ability is
useful fordata mining, and it also makes neural networks an exciting area for
research,...
... applied to data. These patterns can be turned into new features of the data,
for use in conjunction with other directed datamining techniques.
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Automatic Cluster ... Islands of Simplicity
In Chapter 1, where dataminingtechniques are classified as directed or undi-
rected, automatic cluster detection is described as a tool for undirected knowl-
edge discovery. ... activity because
clusters are sought for some business purpose. In marketing, clusters formed
for a business purpose are usually called “segments,” and customer segmen-
tation is a popular application...
... censoring. When looking at customerdatafor
hazard calculations, both the tenure and the censoring flag are needed. For the
customers in Figure 12.7, Table 12.2 shows this data.
It is instructive ...
are forced to discontinue their relationships due to unpaid bills? If such a
customer were forced to stop on day 100, then that customer did not stop vol-
untarily on days 1–99. This information ... cus-
tomer databases often contain data on millions of customers and former
customers. Much of the statistical background of survival analysis is focused
on extracting every last bit of information...
... cho-
sen. However, some kinds of data pose particular problems for some data min-
ing techniques.
Data Type
Categorical variables are especially problematic fordataminingtechniques
that use the ... introduction of datamining requires using
data miningtechniques to address a real business challenge. For companies
that are just getting started with analytical customerrelationship manage-
ment, ... the production datamining environment
■■ A business case for investing in datamining and customer analytics
Even when the decision has already been made to invest in data mining, the
proof-of-concept...
... of real data to use for training sets. Consequently, they spent
much time and effort trying to coax the last few drops of information from
their impoverished datasets—a problem that data miners ... Trees as a Data Exploration Tool
During the data exploration phase of a datamining project, decision trees are a
useful tool for picking the variables that are likely to be important for predict-
ing ... binomial formula was posthu-
mously published. So there are well-known formulas for determining what it
means to have observed E occurrences of some event in N trials.
In particular, there is a formula...
... significant improvement.
The Data
Cellular telephone data is similar to the call detail data seen in the previous case
study for finding fax machines. There is a record for each call that includes ... Study: Segmenting Cellular
Telephone Customers
This case study applies link analysis to cellular telephone calls for the purpose
of segmenting existing customers for selling new services.
1
Analyses ... from dedicated or data lines, we
assumed that any number that calls information—411 or 555-1212 (directory
assistance services)—is used for voice communications, and is therefore a
voice line...