Analysis of churn prediction: a case study on telecommunication services in Macedonia
Date Issued
2016-11-22
Author(s)
Aleksandar Petkovski,
Risteska Stojkoska, Biljana
Abstract
Customer churn is one of the main problems in
the telecommunications industry. Several studies have shown
that attracting new customers is much more expensive than
retaining existing ones. Therefore, companies are focusing on
developing accurate and reliable predictive models to identify
potential customers that will churn in the near future. The
aim of this paper is investigating the main reasons for churn
in telecommunication sector in Macedonia. The proposed
methodology for analysis of churn prediction covers several
phases: understanding the business; selection, analysis and
data processing; implementing various algorithms for
classification; evaluation of the classifiers and choosing the
best one for prediction. The obtained results for the data
from a telecommunication company in Macedonia, should be
of great value for management and marketing departments
of other telecommunication companies in the country and
wider.
the telecommunications industry. Several studies have shown
that attracting new customers is much more expensive than
retaining existing ones. Therefore, companies are focusing on
developing accurate and reliable predictive models to identify
potential customers that will churn in the near future. The
aim of this paper is investigating the main reasons for churn
in telecommunication sector in Macedonia. The proposed
methodology for analysis of churn prediction covers several
phases: understanding the business; selection, analysis and
data processing; implementing various algorithms for
classification; evaluation of the classifiers and choosing the
best one for prediction. The obtained results for the data
from a telecommunication company in Macedonia, should be
of great value for management and marketing departments
of other telecommunication companies in the country and
wider.
Subjects
File(s)![Thumbnail Image]()
Loading...
Name
PID4554473-with-cover-page-v2.pdf
Size
654.18 KB
Format
Adobe PDF
Checksum
(MD5):f11092369e5995c8e686b3f5fcc1c499