Segmentation Applications in Telecommunications - Data Mining Techniques in CRM: Inside Customer Segmentation - page 315

Table 7.12 Cluster heat map designating statistically significant deviations from the
overall (marginal) means.
Clusters
Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5
VOICE OUT CALLS
VOICE IN CALLS
SMS OUT CALLS
PRC SMS OUT CALLS (%)
PRC OUT CALLS PEAK (%)
PRC OUT CALLS WORK (%)
OUT CALLS ROAMING
OUT CALLS INTERNATIONAL
MMS OUT CALLS
INTERNET CALLS
EVENTS CALLS
OUT COMMUNITY TOTAL
INC COMMUNITY TOTAL
DAYS OUT
DAYS IN
ACD OUT
t -tests with a significance level of 0.01 and Bonferroni adjustment for comparisons
across clusters) are illustrated in the heat map of Table 7.12. Cluster values larger
than the average of the total population are represented in dark gray, and values
lower than the total average in light gray.
Based on the information presented so far, the project team involved started
to outline a first rough profile of each cluster:
• Cluster 1 includes users with basic usage. They are characterized by increased
ACD and very low incoming and outgoing communities.
• Cluster 2 contains average voice users. They have medium SMS usage and a
relatively low percentage of traffic in work days/hours.
• Cluster 3mainly consists of SMS users who seem to have an additional inclination
toward technical services like MMS, Internet, and event calls. They also present
very low voice usage and ACD.