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IEEE transactions on consumer electronics
This study examines the issue of customer churn in the context of e-commerce businesses. Customer churn, or losing customers, poses a significant challenge for these businesses as they strive to retain a loyal customer base.
Qing Wei
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This study examines the issue of customer churn in the context of e-commerce businesses. Customer churn, or losing customers, poses a significant challenge for these businesses as they strive to retain a loyal customer base.
Qing Wei
semanticscholar +1 more source
Customer Churn Analysis and Prediction in Banking Industry using Machine Learning
2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC), 2020Customer Churning is also known as customer attrition. Nowadays, there are almost 1.5 million customers that are churning in a year that is rising every year. The Banking industry faces challenges to hold clients.
Ishpreet Kaur, Jasleen Kaur
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Integrating churn into the formal analysis of routing algorithms
2015 International Conference and Workshops on Networked Systems (NetSys), 2015Mathematical modeling and analysis of distributed systems, mostly applied with the goal of the correctness or asymptotic behavior of a system, rarely provides concrete results and often disregards or simplifies network dynamics. However, concrete performance bounds on a system under churn are highly useful both as a validation of empirical results and ...
Stefanie Roos +2 more
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Predictive churn analysis with machine learning methods
2018 26th Signal Processing and Communications Applications Conference (SIU), 2018In this study, we analyzed the well known machine learning algorithms which are mostly used in the past studies to design a new model to predict customer churn. In addition to logistic regression, Naive Bayes classifier, desicion trees, support vector machines and artificial neural Networks, we designed a new hybrid model and analze the initial results.
Melike Günay, Tolga Ensari
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Customer Churn Analysis and Prediction Using Data Mining Models in Banking Industry
International Workshop on Big Data and Information Security, 2019A new method for customer churn analysis and prediction has been proposed. The method uses data mining model in banking industries. This has been inspired by the fact that there are around 1,5 million churn customers in a year which is increasing every ...
Ketut Gde Manik Karvana +3 more
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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 +3 more
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Micro- and macro-level churn analysis of large-scale mobile games
Knowledge and Information Systems, 2019As mobile devices become more and more popular, mobile gaming has emerged as a promising market with billion-dollar revenue. A variety of mobile game platforms and services have been developed around the world.
Xi Liu +6 more
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OLAP analysis of churn in the telecom's role
2011 International Conference on Computer Science and Service System (CSSS), 2011The paper is based on the item that the supporting system of XX telecom company analysis as background, take the churn customer in telecom as study target, analysis the characteristic of churn customer fatherly. It is an important problem that the research object established and the data sample for analysis chose to the churn process multifactor ...
null Hai-fei Qin, null Jian-hua Hu
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Prediction of Customer Plan using Churn Analysis for Telecom Industry
, 2020In creating nations like India, there are in excess of 10 administrators giving versatile administration in each circle. With the presentation of number convenience portable client are progressively changing starting with one administrator then onto ...
A. P, S. A, Gomathi R.M., I. K.
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Churn analysis for an Iranian mobile operator
Telecommunications Policy, 2011Abstract To survive in the challenging environment of a global market, organizations must recognize and analyze customer attitudes. To be competitive, organizations must recognize and forecast customer preferences and behaviors to maximize customer retention before their rivals do so.
Abbas Keramati, Seyed M.S. Ardabili
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