TY - BOOK
T1 - Overview of data mining for customer behavior modeling
T2 - LOUHI. Version 0.2-1
AU - Bounsaythip, Catherine
AU - Rinta-Runsala, Esa
PY - 2001
Y1 - 2001
N2 - This report examines the problems of customer
relationship management
(CRM) particularly customer segmentation and customer
profiling, and how
data mining tools are used to support the decision
making. We first describe
the steps towards predicting customer's behavior, such as
collecting and
preparing data, segmentation and profile modeling. Then,
we present a
general overview of most used data mining methods
including cluster
discovery, decision trees, neural networks, association
rule and sequential
pattern discovery. The report also covers a discussion
about Web mining
which is treated as a separate section due to its current
popularity in electronic
commerce. A guideline to choose a data mining software
package is also
given in the last section.
AB - This report examines the problems of customer
relationship management
(CRM) particularly customer segmentation and customer
profiling, and how
data mining tools are used to support the decision
making. We first describe
the steps towards predicting customer's behavior, such as
collecting and
preparing data, segmentation and profile modeling. Then,
we present a
general overview of most used data mining methods
including cluster
discovery, decision trees, neural networks, association
rule and sequential
pattern discovery. The report also covers a discussion
about Web mining
which is treated as a separate section due to its current
popularity in electronic
commerce. A guideline to choose a data mining software
package is also
given in the last section.
KW - data mining
KW - customer segmentation
KW - customer profiling
KW - web mining
KW - CRM
M3 - Report
T3 - VTT Research Report
BT - Overview of data mining for customer behavior modeling
PB - VTT Technical Research Centre of Finland
CY - Espoo
ER -