Database Reference
In-Depth Information
Table 7.10
Distribution of the derived clusters.
Percentage of
MSISDNs
Clusters
Cluster 1
16.6
Cluster 2
31.0
Cluster 3
19.3
Cluster 4
6.6
Cluster 5
26.5
Total
100.0
Table 7.11
Usage KPIs by cluster.
Clusters
Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Total
VOICE OUT CALLS
32
157
35
212
235
137
VOICE IN CALLS
38
164
58
222
293
161
SMS OUT CALLS
1
21
50
15
6
19
PRC SMS OUT CALLS (%)
2
10
49
8
2
14
PRC OUT CALLS PEAK (%)
59
60
62
85
92
70
PRC OUT CALLS WORK (%)
67
70
72
88
91
77
OUT CALLS ROAMING
0.22
0.46
0.57
3.98
0.68
0.73
OUT CALLS INTERNATIONAL
0.23
0.93
0.89
2.52
0.75
0.86
MMS OUT CALLS
0.03
0.06
0.23
0.31
0.09
0.11
INTERNET CALLS
0.06
0.14
0.39
0.98
0.19
0.24
EVENTS CALLS
0.17
0.64
2.45
0.95
0.59
0.92
OUT COMMUNITY TOTAL
7
55
45
72
57
47
IN COMMUNITY TOTAL
8
52
47
56
86
53
DAYS OUT
8
25
26
27
27
23
DAYS IN
8
27
27
27
28
24
ACD OUT
1.75
1.33
0.69
2.26
0.85
1.21
the application of simple reporting techniques to profile each cluster and identify
what it stands for.
This ''recognize and label'' procedure started with an examination of the
clusters with respect to the component scores, providing a valuable first insight
into their structure, before moving on to their profiling in terms of the original
usage fields. The latter results are given in Table 7.11. This table summarizes the
means of the majority of the original clustering fields across the derived clusters.
Large deviations from the marginal mean characterize the respective cluster and
denote a behavior that differentiates the cluster from the typical behavior.
Inferential statistics have also been applied to flag statistically significant
differences from the overall population mean. These results (based on one-sample
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