Thematische Bibliographien / Customer churning

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Auswahl der wissenschaftlichen Literatur zum Thema „Customer churning“

Autor: Grafiati

Veröffentlicht am 30. Juni 2021

Zuletzt aktualisiert am 2. Februar 2022

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Zeitschriftenartikel zum Thema "Customer churning"

Ascarza, Eva. „Retention Futility: Targeting High-Risk Customers Might be Ineffective“. Journal of Marketing Research 55, Nr. 1 (Februar 2018): 80–98. http://dx.doi.org/10.1509/jmr.16.0163.

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Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models that identify customers at the highest risk of churning, no research has investigated whether it is indeed optimal to target those individuals. Combining two field experiments with machine learning techniques, the author demonstrates that customers identified as having the highest risk of churning are not necessarily the best targets for proactive churn programs. This finding is not only contrary to common wisdom but also suggests that retention programs are sometimes futile not because firms offer the wrong incentives but because they do not apply the right targeting rules. Accordingly, firms should focus their modeling efforts on identifying the observed heterogeneity in response to the intervention and to target customers on the basis of their sensitivity to the intervention, regardless of their risk of churning. This approach is empirically demonstrated to be significantly more effective than the standard practice of targeting customers with the highest risk of churning. More broadly, the author encourages firms and researchers using randomized trials (or A/B tests) to look beyond the average effect of interventions and leverage the observed heterogeneity in customers' response to select customer targets.

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Kim, Myung-Joong, Juil Kim und Sun-Young Park. „Understanding IPTV churning behaviors: focus on users in South Korea“. Asia Pacific Journal of Innovation and Entrepreneurship 11, Nr. 2 (07.08.2017): 190–213. http://dx.doi.org/10.1108/apjie-08-2017-026.

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PurposeThis study aims to investigate customers’ churning out of Internet Protocol Television (IPTV) service, one of the most prevalent forms of IT convergence. Design/methodology/approachBased on the review of current literature, a research model is introduced to depict the effects of select independent variables on customer churning behavior. First of all, the two groups are compared in terms of predictor variables, including switching barriers, voice of customer (VOC), membership period and degree of contents usage. Then, a curvilinear regression was applied to understand the association relationship between the level of IPTV contents usage and variables of switching barriers, VOC and membership period. Third, a logit regression was performed to predict customer churning through the variables of switching barriers, VOC, membership period and level of IPTV contents usage. FindingsThrough the empirical analysis, this study analyzed the factors affecting customer churning behavior of IPTV service providers based on switching barriers, VOC and contents usage. Originality/valueAlthough several studies on IPTV have been undertaken globally, they have largely depended on self-reporting surveys to examine dynamics between antecedent variables and IPTV performance in terms of customer satisfaction, usage intension and customer retention. This empirical study is performed to understand influential factors of IPTV service defection through the weblog analysis of 3,906 service users, who represented both service defectors and non-defectors during a specific month.

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Kabue, Hellen W. „Creating Customer Value for Enhanced Customer Satisfaction and Retention“. Research in Economics and Management 5, Nr. 3 (11.06.2020): p7. http://dx.doi.org/10.22158/rem.v5n3p7.

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Customers are increasingly becoming sophisticated due to forces such as advancement in technology, changing social roles and globalization. As a result, customer churning is today a common reality that most companies have to deal with in order to satisfy and retain their customers. Creating customer value has emerged as one of the winning strategic tools that firms could use to gain competitive advantage in the contemporary marketing environment. This paper is an empirical study that presents a comprehensive analysis of the relationship between customer value, customer satisfaction and customer retention. Data was obtained through a survey involving clients of Commercial Banks in Kenya; the survey yielded a total of 385 responses. A self administered questionnaire was used for the customers’ survey while interviews were conducted for Management. Descriptive statistics and regression data analysis methods were employed utilizing SPSS software. The findings of the study revealed that customer value has a positive statistically significant relationship with both customer satisfaction and customer retention.

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Makinde, Ayodeji Samuel, Abayomi O. Agbeyangi und Wilson Nwankwo. „Predicting Mobile Portability Across Telecommunication Networks Using the Integrated-KLR“. International Journal of Intelligent Information Technologies 17, Nr. 3 (Juli 2021): 50–62. http://dx.doi.org/10.4018/ijiit.2021070104.

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Mobile number portability (MNP) across telecommunication networks entails the movement of a customer from one mobile service provider to another. This, often, is as a result of seeking better service delivery or personal choice. Churning prediction techniques seek to predict customers tending to churn and allow for improved customer sustenance campaigns and the cost therein through an improved service efficiency to customer. In this paper, MNP predicting model using integrated kernel logistic regression (integrated-KLR) is proposed. The Integrated-KLR is a combination of kernel logistic regression and expectation-maximization clustering which helps in proactively detecting potential customers before defection. The proposed approach was evaluated with five others, mostly used algorithms: SOM, MLP, Naïve Bayes, RF, J48. The proposed iKLR outperforms the other algorithms with ROC and PRC of 0.856 and 0.650, respectively.

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Zhao, Xue. „Research on E-Commerce Customer Churning Modeling and Prediction“. Open Cybernetics & Systemics Journal 8, Nr. 1 (31.12.2014): 800–804. http://dx.doi.org/10.2174/1874110x01408010800.

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Rachid, Ait Daoud, Amine Abdellah, Bouikhalene Belaid und Lbibb Rachid. „Clustering Prediction Techniques in Defining and Predicting Customers Defection: The Case of E-Commerce Context“. International Journal of Electrical and Computer Engineering (IJECE) 8, Nr. 4 (01.08.2018): 2367. http://dx.doi.org/10.11591/ijece.v8i4.pp2367-2383.

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<p><span>With the growth of the e-commerce sector, customers have more choices, a fact which encourages them to divide their purchases amongst several e-commerce sites and compare their competitors’ products, yet this increases high risks of churning. A review of the literature on customer churning models reveals that no prior research had considered both partial and total defection in non-contractual online environments. Instead, they focused either on a total or partial defect. This study proposes a customer churn prediction model in an e-commerce context, wherein a clustering phase is based on the integration of the k-means method and the Length-Recency-Frequency-Monetary (LRFM) model. This phase is employed to define churn followed by a multi-class prediction phase based on three classification techniques: Simple decision tree, Artificial neural networks and Decision tree ensemble, in which the dependent variable classifies a particular customer into a customer continuing loyal buying patterns (Non-churned), a partial defector (Partially-churned), and a total defector (Totally-churned). Macro-averaging measures including average accuracy, macro-average of Precision, Recall, and F-1 are used to evaluate classifiers’ performance on 10-fold cross validation. Using real data from an online store, the results show the efficiency of decision tree ensemble model over the other models in identifying both future partial and total defection.</span></p>

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Chouiekh, Alae, und El Hassane Ibn El Haj. „Deep Convolutional Neural Networks for Customer Churn Prediction Analysis“. International Journal of Cognitive Informatics and Natural Intelligence 14, Nr. 1 (Januar 2020): 1–16. http://dx.doi.org/10.4018/ijcini.2020010101.

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Several machine learning models have been proposed to address customer churn problems. In this work, the authors used a novel method by applying deep convolutional neural networks on a labeled dataset of 18,000 prepaid subscribers to classify/identify customer churn. The learning technique was based on call detail records (CDR) describing customers activity during two-month traffic from a real telecommunication provider. The authors use this method to identify new business use case by considering each subscriber as a single input image describing the churning state. Different experiments were performed to evaluate the performance of the method. The authors found that deep convolutional neural networks (DCNN) outperformed other traditional machine learning algorithms (support vector machines, random forest, and gradient boosting classifier) with F1 score of 91%. Thus, the use of this approach can reduce the cost related to customer loss and fits better the churn prediction business use case.

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Sreeejesh, S. „Cellular Customer Churns Due to Mobile Number Portability“. International Journal of Interdisciplinary Telecommunications and Networking 5, Nr. 1 (Januar 2013): 43–57. http://dx.doi.org/10.4018/jitn.2013010104.

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Retaining existing customer has been considered to be one of the most critical challenges for telecommunication service providers than for attracting new ones. In telecommunication, the service offered is different from that of a general commodity sale as in the former case the service is considered to be a continuous process, wherein the service provider can offer the differentiated services throughout the customer’s tenure. This differentiation in service offered creates a demarcation from the competitors and hence establishes competitive advantage for that service provider for attracting new customers and retaining the existing ones, which ultimately determines the profitability. In this paper, the author captures this differentiation factor by investigating customer switching behavior under Mobile Number Portability (MNP) in Indian telecommunication market. It is shown that only limited attention has been paid to the customer churn under MNP and none of the existing studies incorporated psychological constructs as the determinants of customer churn. In this context, the study used discriminant analysis to understand the factors that best discriminate between switchers and non-switchers and predict (develop a churn prediction model) the customer churn behavior through incorporating psychological constructs. The findings indicate that service quality, customer satisfaction, attachment, commitment and switching costs are the major factors differentiating the switching and non-switching decisions. Service quality of the service provider found to be as the differentiating factor in churning decision. The results of the study have implications for both academicians and relationship mangers; they are using psychological constructs to predict customer switching behavior.

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Mishachandar, B., und Kakelli Anil Kumar. „Predicting customer churn using targeted proactive retention“. International Journal of Engineering & Technology 7, Nr. 2.27 (02.08.2018): 69. http://dx.doi.org/10.14419/ijet.v7i2.27.10180.

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With the advent of innovative technologies and fierce competition, the choices for customers to choose from have increased tremendously in number. Especially in the case of a telecommunication industry, where deregulation is at its peak. Every year a new company springs up offering fitter options for its customers. This has turned the concentration of the business doers on churn prediction and business management models to sustain their places. Businesses approach churn in two ways, one is through targeted customer retention and through cause identification strategy. The literature of this paper provides a comprehensible understanding of the so far employed techniques in predicting customer churn. From that, it is quite evident that less attention has been given to the accuracy and the intuitiveness of churn models developed. Therefore, a novel approach of combining the models of Machine Learning and Big Data Analytics tools was proposed to deal churn prediction effectively. The purpose of this proposed work is to apply a novel retention technique called the targeted proactive retention to predict customer churning behavior in advance and help in their retention. This proposed work will help telecom companies to comprehend the risk associated with customer churn by predicting the possibility and the time of occurrence.

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Karuppaiah, Sivasankar, und N. P. Gopalan. „Enhanced Churn Prediction Using Stacked Heuristic Incorporated Ensemble Model“. Journal of Information Technology Research 14, Nr. 2 (April 2021): 174–86. http://dx.doi.org/10.4018/jitr.2021040109.

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In a rapidly growing industry like telecommunications, customer churn prediction is a crucial challenge affecting the sustainability of the business as a whole. The fact that retaining a customer is more profitable than acquiring new customers is important to predict potential churners and present them with offers to prevent them from churning. This work presents a stacked CLV-based heuristic incorporated ensemble (SCHIE) to enable identification of potential churners so as to provide them with offers that can eventually aid in retaining them. The proposed model is composed of two levels of prediction followed by a recommendation to reduce customer churn. The first level involves identifying effective models to predict potential churners. This is followed by result segregation, CLV-based prediction, and user shortlisting for offers. Experimental results indicate high efficiencies in predicting potential churners and non-churners. The proposed model is found to reduce the overall loss by up to 50% in comparison to state-of-the-art models.

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Dissertationen zum Thema "Customer churning"

Osman, Yasin, und Benjamin Ghaffari. „Customer churn prediction using machine learning : A study in the B2B subscription based service context“. Thesis, Blekinge Tekniska Högskola, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-21872.

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The rapid growth of technological infrastructure has changed the way companies do business. Subscription based services are one of the outcomes of the ongoing digitalization, and with more and more products and services to choose from, customer churning has become a major problem and a threat to all firms. We propose a machine learning based churn prediction model for a subscription based service provider, within the domain of financial administration in the business-to-business (B2B) context. The aim of our study is to contribute knowledge within the field of churn prediction. For the proposed model, we compare two ensemble learners, XGBoost and Random Forest, with a single base learner, Naïve Bayes. The study follows the guidelines of the design science methodology, where we used the machine learning process to iteratively build and evaluate the generated model, using the metrics, accuracy, precision, recall, and F1- score. The data has been collected from a subscription-based service provider, within the financial administration sector. Since the used dataset is imbalanced with a majority of non- churners, we evaluated three different sampling methods, that is, SMOTE, SMOTEENN and RandomUnderSampler, in order to balance the dataset. From the results of our study, we conclude that machine learning is a useful approach for prediction of customer churning. In addition, our results show that ensemble learners perform better than single base learners and that a balanced training dataset is expected to improve the performance of the classifiers.

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Wang, Shu-Ching, und 王淑靜. „Customer Churning Factors in Broadband ISP Industry“. Thesis, 2004. http://ndltd.ncl.edu.tw/handle/42354065901116516315.

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碩士
國立臺北科技大學
商業自動化與管理研究所
92
In Taiwan, the broadband Internet access market has reached the saturation stage, with a penetration rate of 46.6% in April 2004. In addition, the lack of product differentiation was unable to create customer loyalty. As a result, high acquisition costs often cannot be recovered, as customers are frequently lured away by competitors’ attractive promotional packages or gifts. Of all the issues facing Broadband Internet Service Providers (BISP), they need to focus on sales and marketing, customer churn, content, and servicing policies. Therefore, how to offere differentiated and multiple services that meet customer needs and foster long-term customer relationship to reduce churn rate and enhance long-term profitability, has become a critical issue facing BISP’s. This thesis will focus the discussion on the causes of customer churn. Utilizing Discriminant Analysis, Factor Analysis, and 1-Way ANOVA, and description statistical analysis to provide hypotheses and answers to the following two questions: the cause of customer churn, and customer behavior before and after churn, in order to provide guidance for developing retention and loyalty programs for the BISP. The analyses revealed that there isn’t significant co-relation between churn pattern and population changes. The main causes of customer churn are service oriented or price oriented. For customers contemplating switching service providers, the main considerations are service oriented, price/package oriented, and product quality oriented. Varying emphasis of these three factors will affect the final selection of service provider.

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Ko, Hung-Chieh, und 柯宏杰. „Determinants of The Customer Churning Behavior: the US wireless telecommunication industry“. Thesis, 2005. http://ndltd.ncl.edu.tw/handle/08833281652812401620.

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碩士
國立交通大學
經營管理研究所
93
The US wireless communication industry has been one of the fastest-growing businesses in recent years. As the market gradually saturates and the competition is intensified, the enterprise faces the problem of customer churn seriously. Under such fierce competition, the customer retention has become the major concern.The goal of this study is to understand the customer churning behavior. For the enterprise, if it can effectively reduce the customer churning behavior, it not only enhances the enterprise profit, but also helps to save the cost of expenditure. It is the key in managing the company for the long-term. Based on the binominal logit model in discrete choice theory, the paper develop a churn behavior model which estimates the probability of customer churn associated with service variable、economic variables、use variables and customer demographics. The study results in some generalized outcomes which can be applied to wireless service providers in forming strategies of customer churn management and customer retention

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蕭大立. „The study of customer churning factors - An example of a construction products supplier“. Thesis, 2009. http://ndltd.ncl.edu.tw/handle/32963529488635922024.

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碩士
國立政治大學
商管專業學院碩士學位學程(AMBA)
98
A great deal of effort has been made on the causes of customer churn in the consumer products industry. What seems to be lacking, however, is this subject in the industrial products industry. This study will focus the discussion on the causes of customer churn and customer switching behavior in the construction products supplier, in order to provide guidance for developing retention and loyalty programs. This study can be divided into five parts; the first part reviews the literature on this subject. The second part introduces the methodology to be utilized throughout the study, first with structural diagram of study followed by study methods, and object in study. The third part utilizes using SPSS for Windows as the tool to conduct statistical analysis, including description statistical analysis, reliability test, Discriminant Analysis, Factor Analysis, and One-way ANOVA. The fourth part discusses the experimental result of this study, and compares it with customer switching behavior in the consumer products industry. The last part is a conclusion of the thesis. The results of this study show as follows. 1. The main causes of customer churn are product and service oriented or price oriented. The main causes of customer switch are service and brand strategy, product strategy or price strategy. 2. Customer switching behavior includes decreasing purchased frequency and transferring to a new service provider. 3. Customer switching behavioral model in the service industry is different from the model in the construction products supplier. 4. The customers who have longer purchasing duration have higher recognition of importance for deliver time. Purchasing frequency and product price are not the best variables to predict if the customers would churn or not.

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Liao, Tzu-Yi, und 廖子逸. „Determinants of Customer Churning Behavior in Mobile Communications- A Case Study of Operator in Taiwan“. Thesis, 2015. http://ndltd.ncl.edu.tw/handle/xj5kmj.

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碩士
國立交通大學
管理學院經營管理學程
103
In retrospect the telecommunication operation in Taiwan, government has implemented liberal policy in the telecommunications service industry in 1997. The decision has opened the door for private telecommunication firms and the telecommunications market changed to the condition of fierce competition. As of today, there are 9 operators running 2G, 3G, 4G, PHS and WiMAX system in Taiwan. With the growth of the mobile penetration and the Number Portability policy’s opening, the NP policy intensifies the market competition develops well. According to National Communications Commission’s data, the total effective cellphone numbers in Taiwan reached 28 millions in Dec. 2014. Because churn management has became a fundamental concern since the Taiwan mobile communication market is on the verge of saturation, companies’ strategies to handle churn issue have been directed to survive or maintain an advantage in such a competitive marketplace. This study constructs questionnaire by phone interviewing with mobile users and using data mining methodology. This study examines the key factors for customer churn rate and builds up the churn rate prediction model to help mobile operators to identify the possible NP threat.

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Buchteile zum Thema "Customer churning"

Hur, Yeon, und Sehun Lim. „Customer Churning Prediction Using Support Vector Machines in Online Auto Insurance Service“. In Advances in Neural Networks – ISNN 2005, 928–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11427445_149.

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Dalmia, Hemlata, Ch V. S. S. Nikil und Sandeep Kumar. „Churning of Bank Customers Using Supervised Learning“. In Lecture Notes in Networks and Systems, 681–91. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3172-9_64.

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Kazienko, Przemyslaw, und Dymitr Ruta. „The Impact of Customer Churn on Social Value Dynamics“. In Networking and Telecommunications, 1149–59. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-986-1.ch074.

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Modern telecommunication service providers implicitly create interactive social networks of individuals that both depend on and influence each other through complex social relationships grown on friendship, shared interests, locality, and so forth. While delivering services on the individual basis, the network effects exerted from customer-to-customer interactions remain virtually unexplored and unexploited. The focus of this article is on customer churn, where social network effects are widely ignored yet may play a vital role in revenue protection. The key assumption made is that a value loss of a churning customer extends beyond his revenue stream and directly affects interaction within local neighborhoods. The direction and strength of this impact are evaluated experimentally by direct measurements of the total neighborhood value of the churning customer along with other standard social network measures taken before and after the churn event.

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Krishna, Addepalli V. N., Shriansh Pandey und Raghav Sarda. „A Secured Predictive Analytics Using Genetic Algorithm and Evolution Strategies“. In Handbook of Research on Intelligent Data Processing and Information Security Systems, 199–226. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1290-6.ch009.

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In the banking sector, the major challenge will be retaining customers. Different banks will be offering various schemes to attract new customers and retain existing customers. The details about the customers will be provided by various features like account number, credit score, balance, credit card usage, salary deposited, and so on. Thus, in this work an attempt is made to identify the churning rate of the possible customers leaving the organization by using genetic algorithm. The outcome of the work may be used by the banks to take measures to reduce churning rates of the possible customers in leaving the respective bank. Modern cyber security attacks have surely played with the effects of the users. Cryptography is one such technique to create certainty, authentication, integrity, availability, confidentiality, and identification of user data can be maintained and security and privacy of data can be provided to the user. The detailed study on identity-based encryption removes the need for certificates.

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Krishna, Addepalli V. N., Shriansh Pandey und Raghav Sarda. „A Secured Predictive Analytics Using Genetic Algorithm and Evolution Strategies“. In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, 969–96. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8048-6.ch049.

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Karna, Amit, Ramendra Singh und Sanjay Verma. „Knowledge Management for an Effective Sales and Marketing Function“. In Knowledge Management Strategies for Business Development, 324–37. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-348-7.ch015.

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In the last decade, knowledge management has been receiving managerial attention particularly in the post-Internet era. With advancements in information and communications technologies, the incentives to manage knowledge have far surpassed the costs associated with it. The sales and marketing (S&M) function is one of the important functions in an organization with a unique blend of internal and external stakeholders to cater to. Another unique feature of knowledge management in the S&M function is that it lies on the interface of the organization with its customers. Therefore, information that comes into the organization through sales and marketing employees is often collected, filtered, and assimilated in different forms and with time lags. This chapter is aimed at familiarizing the readers with the importance of managing a continuously churning ocean of knowledge in the S&M function. We address various knowledge management issues and opportunities in the context of S&M and recommend a set of guidelines to enable managers increase the effectiveness of the S&M function by using appropriate knowledge management tools and strategies.

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Konferenzberichte zum Thema "Customer churning"

Nakano, Satoshi, Akiya Inoue, Kiyotaka Otsuka, Takeshi Kurosawa, Motoi Iwashita und Ken Nishimatsu. „Mobile-Carrier Churning Behavior Modeling Based on Customer Satisfaction“. In 2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel & Distributed Computing (SNPD). IEEE, 2012. http://dx.doi.org/10.1109/snpd.2012.70.

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Ali, Muhammad, Aziz Ur Rehman, Shamaz Hafeez und Muhammad Usman Ashraf. „Prediction of Churning Behavior of Customers in Telecom Sector Using Supervised Learning Techniques“. In 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE). IEEE, 2018. http://dx.doi.org/10.1109/iccceee.2018.8515857.

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Ali, Muhammad, Aziz Ur Rehman und Shamaz Hafeez. „Prediction of Churning Behavior of Customers in Telecom Sector Using Supervised Learning Techniques“. In 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS). IEEE, 2018. http://dx.doi.org/10.1109/cccs.2018.8586836.

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