Customer Churn Prediction in Telecommunication Industry Using Data Certainty

Rasheed Ahammed Azad

16 citations0/0 files storedInternational Journal of Scientific Research in Science Engineering and Technology

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Customer churn and segmentation Customer Service Quality and Loyalty Data Mining and Machine Learning Applications

Abstract

Customer churn is a major problem affecting large companies, especially in telecommunication field. So the telecom industries have to take the necessary steps to retain their customers, to maintain their market value. So companies are seeking to develop methods that predict potential churned customers. We have to find out the factors that increase customer churn for making necessary actions to reduce churn. In the past, different data mining techniques have been used for predicting the churners. Here the most popular machine learning algorithms used for churn predicting are analysed. The conclusions are stated with the help of suitable tables.

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References

2019A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector 2011Customer churn prediction in telecommunications 2018Customer churn prediction in telecommunication industry using data certainty 2014Improved churn prediction in telecommunication industry using data mining techniques 2015A Multi-Layer Perceptron Approach for Customer Churn Prediction 2013CHURN PREDICTION IN THE TELECOMMUNICATIONS SECTOR USING SUPPORT VECTOR MACHINES 2018Customer Churn Prediction Modelling Based on Behavioural Patterns Analysis using Deep Learning 2019Features Weight Estimation Using a Genetic Algorithm for Customer Churn Prediction in the Telecom Sector

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2021Predicting Customer Churn using ensemble learning: Case Study of a Fixed Broadband Company

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