Martin has a passion of using information technology to solve real life problems. He has worked as a software developer specialized in Business Intelligence and Analytics. He is currently working as an analytics developer and provides consultancy services for various IT domains. He graduated from JKUAT with a BSc in Information Technology.

Project Summary

Project  Title: Reducing Customer Churn in the Telecommunication Industry by use of Predictive Analytics

Research Supervisor: Dr. Evans Miriti

Abstract: Customer churn is a big problem in various businesses and especially so in the telecommunication industry. When a business loses its customers, it loses the revenue that was being generated from the customers and possibly revenue from potential customers who receive negative marketing from customers who churn. Managing customer churn in the Kenyan telecommunication industry has been largely ineffective due to the reactive approach where  churn is just a metric that is reported by the business after a certain period.The objective of this study was to show how we can use predictive analytics to proactively identify customers who are about to churn. By doing so businesses can take measures to prevent churn and therefore increase customer retention. This was done by identifying features that are most important in predicting churn, developing, implementing and testing churn prediction models. While there exist different approaches to solving the churn problem, machine learning was used to do the churn prediction based on various customer attributes such as age, usage, gender, etc. Since there exists multiple algorithms to do this kind of machine learning, this research implements four of them and does a comparison to see which one would be the most suited based on their performance. The final result shows which features can be used for churn prediction and their importance. The features were Registration Document, Age on Network, Subscriber age and Talk Time. The end result also showed how the different classification algorithms performed.