Using analytical CRM system to reduce churn in the telecom sector: A macine learning approach
Using analytical CRM system to reduce churn in the telecom sector: A macine learning approach
Date
2019-04
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Authors
Kilonzi, Faith Mueni
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Abstract
Customers are considered to be the most valuable assets of any business, and thus their loyalty
is key to profitability as they indulge in repeat purchases and attract their colleagues through
word-of-mouth. In competitive markets such as telecommunications, customers have a lot of
flexibility due to the variety of service providers available and the introduction of mobile
number portability (MNP) thus they can easily switch services and service providers. Customer
churn is, therefore, a major problem among telecommunication companies hence their quest to
reduce customer churn rate and retain an existing customer. Customer relationship management
systems have been used over the years to track patterns within the customer data, but this could
be improved notably with the technological advances hitting the universe on a daily basis. We
have moved past the age of innovations around steam engines, electricity, computers, mobile,
internet to the current technology trends in artificial intelligence and big data. We are at the
cusp of a new wave where enterprises have embraced the application of machine learning in
streamlining different business processes. Telecom companies have the advantage of mining
large customer datasets that can be leveraged on for predictive analysis using data science.
This project explores the use of analytical CRM system in reducing customer churn in the
telecom industry using machine learning algorithms to predict customer behavior in order to
retain them. Its goal is to analyze all relevant customer data and develop focused customer
retention programs. This is on the focus that if you could somehow predict in advance which
customers are at risk of leaving, you could develop focused customer retention programs to
reduce customer churn.
Description
Applied project submitted to the Department of Computer Science and Information Systems, Ashesi University, in partial fulfillment of Bachelor of Science degree in Computer Science, April 2019
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Applied project
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Keywords
customer behavior , telecommunications sector , churn , customer relationship management (CRM) system , data management