Segmentation Applications in Telecommunications - Data Mining Techniques in CRM: Inside Customer Segmentation - page 316

Table 7.13 Behavioral versus value-based segments.

Clusters
Cluster Cluster Cluster Cluster Cluster Total
1 2 3 4 5

Value-based
segments

First class (PLATINUM
Top 1%)

0 1 0 4 1 1

Second class (GOLD
Top 4%)

0 4 3 3 7 4

Third class (SILVER
High 15%)

1 19 12 15 23 15

Fourth class (BRONZE
Medium 40%)

10 45 50 48 43 40

Fifth class (MASS Low
40%)

89 31 35 30 26 40

Total (%) 100 100 100 100 100 100

MARPU Mean MARPU 11 40 34 47 48 37

Percentage of MSISDNs 17 31 19 7 26 100

Percentage of MARPU 5 34 18 9 34 100

• Cluster 4 includes roamers and users with increased communication to inter-
national destinations. They are accustomed to Internet services and make most
of their calls during work days/hours. They also have the largest outgoing
communities.
• Cluster 5 contains heavy voice users with traffic peaks in work days/hours.
Furthermore, they have the largest voice incoming communities. Perhaps this
segment includes residential customers who use their phones for business
purposes (self-employed professionals).

This first rough profiling of the clusters was supplemented with complemen-
tary information concerning demographic characteristics and the relationship of
the derived clusters with MARPU and the value segments, already defined by the
relevant segmentation.
As indicated by Table 7.13, cluster 5 includes most of the high-value users
with an average MARPU of almost 48. This cluster contains about 26% of the users
who account for about 34% of the total MARPU. On the other hand, cluster 1
mainly consists of mass customers who contribute a poor 5% of the total MARPU.
Table 7.14 presents the age distribution of each cluster. Cluster 1 contains the
most aged part of the customer base. On the contrary, cluster 3 mainly consists of
younger users. What is interesting is the relatively increased percentage of persons
between 45 and 54 years old in this cluster. Perhaps this can be explained by the
fact that the demographic information refers to contract holders and not users.
Maybe the age data recorded upon contract registration refers to parents who