Results 171 to 180 of about 9,240 (196)

Customer Churn Prediction by Hybrid Model

2006
In order to improve the performance of a data mining model, many researchers have employed a hybrid model approach in solving a problem. There are two types of approach to build a hybrid model, i.e., the whole data approach and the segmented data approach.
Jae Sik Lee, Jin Chun Lee
openaire   +1 more source

Customer Churn Prediction in B2B Contexts

2019
While business-to-customer (B2C) companies, in the telecom sector for instance, have been making use of customer churn prediction for many years, churn prediction in the business-to-business (B2B) domain receives much less attention in existing literature.
Iris Figalist, Christoph Elsner, Jan Bosch, Helena Holmström Olsson   +3 more
openaire   +1 more source

Adoption of Churn Recognition System to Predict Customer Churn

2023
In the cutthroat competitive arena, it is a very challenging task for any enterprise to make a balance between retaining its existing loyal customers and attracting new customers. It is a tedious task to find the right segment of active customers and understand the reason behind churn numbers. It is said that it is five times more costly to attract new
Yuvraj Sharma, Rajender Gurram, Naveen Saharan   +2 more
openaire   +1 more source

Predicting Probability of Customer Churn in Insurance

2016
We focus on a real case of the motor insurance sector. We propose four different methods to predict lapsing from a portfolio of policies. We present a comparative analysis between three different performance measures in order to assess the predictive power of each model. Our comparison analyses the outcomes of a logistic regression, a conditional tree,
Catalina Bolancé, Montserrat Guillen, Alemar E. Padilla-Barreto   +2 more
openaire   +1 more source

Customer churn prediction by hybrid neural networks

Expert Systems with Applications, 2009
As churn management is a major task for companies to retain valuable customers, the ability to predict customer churn is necessary. In literature, neural networks have shown their applicability to churn prediction. On the other hand, hybrid data mining techniques by combining two or more techniques have been proved to provide better performances than ...
Chih-Fong Tsai, Yu-Hsin Lu
openaire   +1 more source

Customer churn prediction for retention analysis

Abstract This abstract provides a comprehensive overview of the research on Customer Churn Prediction for Retention Analysis. In today's corporate context, understanding and mitigating customer churn has become critical for long-term success.
Rajesh Saturi, Siripothula Rahul, Zuha Siddiqui, Rachamalla Nikhitha   +3 more
openaire   +1 more source

Predicting Customer Churn in Electronic Banking

2019
The following paper is an outline of the current author’s research on the churn prediction in electronic banking. The research is based on real anonymised data of 4 million clients from one of the biggest Polish banks. Access to real data in such scale is a substantial strength of the study, as many researchers often do use only small data sample from ...
openaire   +1 more source

Customer churn prediction for web browsers

Expert Systems with Applications, 2022
Xing Wu 0001, Pan Li, Ming Zhao, Ying Liu, Rubén González Crespo, Enrique Herrera-Viedma   +5 more
openaire   +1 more source

Proactive customer retention management in a non-contractual B2B setting based on churn prediction with random forests

Industrial Marketing Management, 2022
Theresa Gattermann-Itschert, Ulrich W Thonemann   +1 more
exaly  

Leveraging unstructured call log data for customer churn prediction

Knowledge-Based Systems, 2021
Shaowu Liu, Xitong Li, Guangdong Xu
exaly