Study on the Dual Optimization of Service Marketing and Customer Churn Management

2008 ◽  
Author(s):  
Wang Qiwan ◽  
Zhou Min
Keyword(s):  
Service Marketing ◽  
Customer Churn ◽  
Churn Management

The Impact of Customer Churn Factors (CCF) on Customer's Loyalty

2019 ◽  
Vol 10 (1) ◽  
pp. 48-70
Author(s):  
Hussein Moselhy Syead Ahmed
Keyword(s):  
Customer Loyalty ◽  
Service Providers ◽  
Linear Regression Analysis ◽  
Telecommunication Service ◽  
Telecommunication Services ◽  
Customer Churn ◽  
Customer's Loyalty ◽  
Churn Management ◽  
The Impact ◽  
Descriptive Method

This article analyzes the impact of customer churn factors on improving the customer loyalty towards telecommunication service providers in Egypt. To accomplish this, a descriptive method is used. 1500 unique e-mails of customers of telecommunication service providers who have used telecommunication services of these providers were randomly selected. With a 25.6% response rate, the questionnaires were distributed through email and self-administered for data collection. Linear regression analysis was used on the responses. The results showed that there is a statistically significant relationship between customer churn factors and customer loyalty to improve factors and increase loyalty achievement to the telecommunication service providers in Egypt, The implications of the study are that the providers should better manage their relationships with the customers as a competitive policy in the telecommunication service marketplace. It can do that by customer churn management to decrease churn rate and increase customer loyalty.

scholarly journals Entropy Based Trees to Support Decision Making for Customer Churn Management

2016 ◽  
Vol 129 (5) ◽  
pp. 971-979 ◽  
Author(s):  
K. Gajowniczek ◽  
A. Orłowski ◽  
T. Ząbkowski
Keyword(s):  
Decision Making ◽  
Customer Churn ◽  
Churn Management ◽  
Support Decision Making

Computer assisted customer churn management: State-of-the-art and future trends

2007 ◽  
Vol 34 (10) ◽  
pp. 2902-2917 ◽  
Author(s):  
John Hadden ◽  
Ashutosh Tiwari ◽  
Rajkumar Roy ◽  
Dymitr Ruta
Keyword(s):  
State Of The Art ◽  
Computer Assisted ◽  
Future Trends ◽  
Customer Churn ◽  
Churn Management

scholarly journals A Hybrid Data Mining Method for Customer Churn Prediction

2018 ◽  
Vol 8 (3) ◽  
pp. 2991-2997
Author(s):  
E. Jamalian ◽  
R. Foukerdi
Keyword(s):  
Customer Retention ◽  
Real Data ◽  
Data Preparation ◽  
Churn Prediction ◽  
Weighted Voting ◽  
Customer Churn ◽  
Hybrid Data ◽  
Using Data ◽  
The Individual ◽  
Churn Management

The expenses for attracting new customers are much higher compared to the ones needed to maintain old customers due to the increasing competition and business saturation. So customer retention is one of the leading factors in companies’ marketing. Customer retention requires a churn management, and an effective management requires an exact and effective model for churn prediction. A variety of techniques and methodologies have been used for churn prediction, such as logistic regression, neural networks, genetic algorithm, decision tree etc.. In this article, a hybrid method is presented that predicts customers churn more accurately, using data fusion and feature extraction techniques. After data preparation and feature selection, two algorithms, LOLIMOT and C5.0, were trained with different size of features and performed on test data. Then the outputs of the individual classifiers were combined with weighted voting. The results of applying this method on real data of a telecommunication company proved the effectiveness of the method.

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