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A Survey on Customer Churn Prediction using Machine Learning Techniques

Saran Kumar, Chandrakala D.
2016 International Journal of Computer Applications  
This paper reviews the most popular machine learning algorithms used by researchers for churn predicting, not only in banking sector but also other sectors which highly depends on customer participation  ...  It is therefore essential for the service providers to prevent churn-a phenomenon which states that customer wishes to quit the service of the company.  ...  A support vector machine constructs a hyper-plane in a high-or infinitedimensional space, which can be used for classification.  ... 
doi:10.5120/ijca2016912237 fatcat:oyepwvi3prgk5n4ezwn2zpbiia

A Critical Examination of Different Models for Customer Churn Prediction using Data Mining

2019 International Journal of Engineering and Advanced Technology  
Researchers are also working on customer churn prediction in e-commerce using data mining and machine learning techniques.  ...  In this paper, a comprehensive review of various models to predict customer churn in e-commerce data mining and machine learning techniques has been presented.  ...  In this paper, a comprehensive review of various churn prediction models in order to predict customer churn in e-commerce using various techniques such as machine learning and data mining etc. has been  ... 
doi:10.35940/ijeat.f1164.0986s319 fatcat:4gqn6vusn5guvdd3xk74wgajca

Amalgamation of Customer Relationship Management and Data Analytics in Different Business Sectors—A Systematic Literature Review

Lewlisa Saha, Hrudaya Kumar Tripathy, Soumya Ranjan Nayak, Akash Kumar Bhoi, Paolo Barsocchi
2021 Sustainability  
Different IT and non-IT-based techniques are used in the analytical CRM area to achieve this target, and researchers have been actively involved in this domain.  ...  This whole process is known as customer relationship management (CRM). In this context, we extensively surveyed 138 papers published between 1996 and 2021 in the area of analytical CRM.  ...  Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/su13095279 fatcat:ollwazwvjvc4phtcn4vw2raqly

Digitalisation and Big Data Mining in Banking

Hossein Hassani, Xu Huang, Emmanuel Silva
2018 Big Data and Cognitive Computing  
of both DM and the banking sector along with a comprehensive one stop reference table.  ...  Since existing reviews only cover the applications until 2013, this paper aims to fill this research gap and presents the significant progressions and most recent DM implementations in banking post 2013  ...  In order to improve the customer credit card churning prediction for a Latin-American bank, the authors in [29] adopted improved DM techniques that are based on K-means clustering and support vector  ... 
doi:10.3390/bdcc2030018 fatcat:xlz5erzbrbd2ppfuzqdxnqrjxu

Building comprehensible customer churn prediction models with advanced rule induction techniques

Wouter Verbeke, David Martens, Christophe Mues, Bart Baesens
2011 Expert systems with applications  
ALBA on the other hand combines the high predictive accuracy of a non-linear support vector machine model with the comprehensibility of the rule-set format.  ...  This paper provides an extended overview of the literature on the use of data mining in customer churn prediction modeling.  ...  Acknowledgements We extend our gratitude to the Flemish Research Council for financial support (FWO postdoctoral research grant, Odysseus Grant B.0915.09), and the National Bank of Belgium (NBB/10/006)  ... 
doi:10.1016/j.eswa.2010.08.023 fatcat:zmi532jhqzchhkcimfap4rblxq

Customers Churn Prediction using Artificial Neural Networks (ANN) in Telecom Industry

Yasser Khan, Shahryar Shafiq, Abid Naeem, Sheeraz Ahmed, Nadeem Safwan, Sabir Hussain
2019 International Journal of Advanced Computer Science and Applications  
In contrast with other prediction techniques, the results from Artificial Neural Networks (ANN) based approach can predict the telecom churn with accuracy of 79% in Pakistan.  ...  Abstracts-To survive in the fierce competition of telecommunication industry and to retain the existing loyal customers, prediction of potential churn customer has become a crucial task for practitioners  ...  Predictive Analytics can divided into classifications and prediction which can further be sub divided into decision tree, logistic regression, neural network and support vector machine given in Fig. 1  ... 
doi:10.14569/ijacsa.2019.0100918 fatcat:aj7s5uh5s5b73ctbwxgns7asai

Unsupervised Learning Framework for Customer Requisition and Behavioral Pattern Classification

Udoinyang G. Inyang, Okure O. Obot, Moses E. Ekpenyong, Aliu M. Bolanle
2017 Modern Applied Science  
Discovered knowledge will guide effective allocation of resources to each customer cluster and other organizational decision support functions much required by CRM systems.  ...  An in-depth analysis of each sub-cluster was also performed and appropriate customer relationship management (CRM) strategies established for each sub-cluster.  ...  Acknowledgments This research was supported by the Tertiary Education Trust Fund (TETFund) grant.  ... 
doi:10.5539/mas.v11n9p151 fatcat:2j5uonahs5eelnilqluynugn2i

A Survey on Churn Analysis in Various Business Domains

Jaehuyn Ahn, Junsik Hwang, Doyoung Kim, HyukGeun Choi, Shinjin Kang
2020 IEEE Access  
Vector Machine ESVM Evolutionary Support Vector Machine DMEL Data Mining by Evolutionary Learning SOM Self-Organizing Maps RSM Random Subspace Method Logit Logistic Regression LR Linear Regression KNN  ...  Since then, in the architectural point of view, the CRM has evolved and become divided into operational CRM and analytical CRM.  ... 
doi:10.1109/access.2020.3042657 fatcat:2wtgqgsmnbcmxls36czeygvhyy

Application of data mining techniques in customer relationship management: A literature review and classification

E.W.T. Ngai, Li Xiu, D.C.K. Chau
2009 Expert systems with applications  
On the other hand, classification and association models are the two commonly used models for data mining in CRM.  ...  This is the first identifiable academic literature review of the application of data mining techniques to CRM.  ...  Acknowledgements This research was partly supported by The Hong Kong Polytechnic University (Project no.: G-YF20) and National Natural Science Foundation of China (NSFC, Project no.: 70671059).  ... 
doi:10.1016/j.eswa.2008.02.021 fatcat:nqlw5dkqjzfhpf2cldlmoxd25e

Predicting customer churn using targeted proactive retention

B Mishachandar, Kakelli Anil Kumar
2018 International Journal of Engineering & Technology  
Therefore, a novel approach of combining the models of Machine Learning and Big Data Analytics tools was proposed to deal churn prediction effectively.  ...  The literature of this paper provides a comprehensible understanding of the so far employed techniques in predicting customer churn.  ...  Manohar for his assistance and comments that greatly improved the manuscript and VIT, Vellore for providing us the required support to try and execute the various techniques and methodologies for the successful  ... 
doi:10.14419/ijet.v7i2.27.10180 fatcat:322vtcdjwnautnp2adswr6iyum

Improving Customer Value Index and Consumption Forecasts Using a Weighted RFM Model and Machine Learning Algorithms

Zongxiao Wu, Cong Zang, Chia-Huei Wu, Zilin Deng, Xuefeng Shao, Wei Liu
2022 Journal of Global Information Management  
Collecting and mining customer consumption data are crucial to assess customer value and predict customer consumption behaviors.  ...  This paper proposes a new procedure, based on an improved Random Forest Model by: adding a new indicator, joining the RFMS-based method to a K-means algorithm with the Entropy Weight Method applied in  ...  Support Vector Machines (SVM) Support Vector Machines (SVM) is a two-class model, whose basic principle is to solve for a separate hyperplane that correctly divides the training data set and maximizes  ... 
doi:10.4018/jgim.20220701.oa1 fatcat:zqbpg4hgnfhhhma266kszbvui4

Intelligent data analysis approaches to churn as a business problem: a survey

David L. García, Àngela Nebot, Alfredo Vellido
2016 Knowledge and Information Systems  
In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods.  ...  Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics.  ...  Farquad M, Ravi V, Raju S (2014) Churn prediction using comprehensible support vector machine: An analytical CRM application. Applied Soft Computing 19:31-40 25.  ... 
doi:10.1007/s10115-016-0995-z fatcat:2k3c3dnh75ggnesqkrif3w6cwm

Domain knowledge integration in data mining using decision tables: case studies in churn prediction

E Lima, C Mues, B Baesens
2009 Journal of the Operational Research Society  
Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques.  ...  accuracy of support vector machines.  ... 
doi:10.1057/jors.2008.161 fatcat:bqgkxdgz5fcp7lt2j26omlzpve

A Novel Model for Global Customer Retention Using Data Mining Technology [chapter]

Jie Lin, Xu Xu
2009 Data Mining and Knowledge Discovery in Real Life Applications  
Although CRM has become widely recognized as an important business strategy, there is no widely accepted definition of CRM.  ...  One-to-one marketing refers to personalized marketing campaigns which are supported by analyzing, detecting and predicting changes in customer behaviors.  ...  vector machines and boosting (Lemmens & Croux, 2003) .  ... 
doi:10.5772/6453 fatcat:5g5ix2bk7bh7je7zhxaegw7tgi

Beyond Customer Churn: Generating Personalized Actions to Retain Customers in a Retail Bank by a Recommender System Approach

Michele Gorgoglione, Umberto Panniello
2011 Journal of Intelligent Learning Systems and Applications  
embracing both the analytical prediction of customer churn and the generation of retention actions.  ...  From a scientific perspective, a comprehensive model of how to generate actions might be helpful to develop more effective data mining and statistical models to support CRM processes.  ...  Analytical models to predict customer churn have been developed in several areas and industries as well.  ... 
doi:10.4236/jilsa.2011.32011 fatcat:54shmz7i7beflhpqrmoz2smimu
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