Segmentation Applications in Telecommunications - Data Mining Techniques in CRM: Inside Customer Segmentation - page 313

IDENTIFYING, INTERPRETING, AND USING SEGMENTS

The generated components represented all the usage data dimensions of interest,
in a concise and comprehensible way, leaving no room for misunderstandings about
their business meaning. The next step included the use of the derived component
scores as inputs in a clustering model.
The clustering process involved the evaluation of different solutions obtained
by trying different clustering algorithms and different model settings. All these
trials resulted in overall similar, yet not identical, solutions, so it was up to the data
miners and the marketers involved to select the optimal solution for deployment.
The solution finally adopted was based on a TwoStep clustering model and was
chosen because it seemed to best address the marketing needs of the organization.
The model automatically detected five clusters which, after extensive profiling,
were assessed as meaningful and potentially useful for building the differentiated
marketing strategies.
The modeling options used for the development of the adopted segmentation
solution are summarized in Table 7.9.
The distribution of the derived clusters is shown in Table 7.10. These clusters
were not known in advance, nor imposed by users, but were uncovered after
analyzing the actual behavioral patterns recorded in the usage data.
Each revealed cluster corresponds to a distinct behavioral typology. This
typology had to be understood, named, and communicated to all the people in the
organization in a simple and concise way, before being used for tailored interactions
and targeted marketing activities. Therefore the next phase of the project included

Table 7.9 Modeling options used to produce the segmentation solution.

Data reduction

Modeling option Setting

Model Principal components (PCA)

Rotation Varimax

Criteria for the number of factors to
extract

Eigenvalues over 1. Resulting 12 compo-
nents

Clustering

Modeling option Setting

Model Two step

Input clustering fields 12 component scores derived from PCA

Number of clusters Automatically calculated

Exclude outliers option On

Standardize numeric fields option On