Academic literature on the topic 'Customer lifetime value (CLV)'

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Journal articles on the topic "Customer lifetime value (CLV)"

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Chang, Wen, Chen Chang, and Qianpin Li. "Customer Lifetime Value: A Review." Social Behavior and Personality: an international journal 40, no. 7 (2012): 1057–64. http://dx.doi.org/10.2224/sbp.2012.40.7.1057.

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The concept of regarding customers as assets that should be managed and whose value should be measured is now accepted and recognized by academics and practitioners. This focus on customer relationship management makes it extremely important to understand customer lifetime value (CLV) because CLV models are an efficient and effective way to evaluate a firm's relationship with its customers. Assessment of CLV is especially important for firms in implementing customer-oriented services. In this paper we provide a critical review of the literature on the development process and applications of CLV.
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Winkel, Susanne. "Customer Lifetime Value (CLV)." Controlling 22, no. 4-5 (2010): 275–76. http://dx.doi.org/10.15358/0935-0381-2010-4-5-275.

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Lohonauman, Hans. "IPTEKS PERHITUNGAN COSTUMER LIFETIME VALUE." Jurnal Ipteks Akuntansi Bagi Masyarakat 4, no. 1 (2020): 19. http://dx.doi.org/10.32400/jiam.4.1.2020.29236.

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Everyone has a goal to make high profitsin business,. Therefore, every entrepreneur requires value that need to be maintained. This value gives a good attitude to the customers to build a long-term relationship. One of the factors that determine the success of a business is the customers. Customer lifetime value should be noticed by the entrepreneur since it becomes a ways to measure customer's profitability, to analyze marketing, and it is also can be used to create a mindset in running a business. Customer Lifetime Value (CLV) also can create the customer loyalty which can impact for profitability.
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Hajipour, Bahman, and Molud Esfahani. "Delta model application for developing customer lifetime value." Marketing Intelligence & Planning 37, no. 3 (2019): 298–309. http://dx.doi.org/10.1108/mip-06-2018-0190.

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Purpose The purpose of this paper is to evaluate the relationship between strategy and customer lifetime value (CLV). A new model was proposed for defining customers’ values based on the RFM model and segmenting bank customers using the K-means algorithm. In addition, the authors combined a new category with the delta model in order to analyze the behavior of each cluster. Design/methodology/approach This case study was based on an applied method following its objectives and a descriptive-analytic method in terms of data collection. In this research, the AHP, data mining and K-means clustering methods, as well as the discriminant analysis were applied for computing the weights of the indices, examining the relationship between the identified variables, clustering the records and ensuring the clustering accuracy based on the RFM model, respectively. Findings The paper confirmed the relationship between the strategies and CLV. For a cluster whose strategy was the best product, customers had a minimal CLV. For a cluster whose strategy was based on total customer solutions, customers had a median CLV. For a cluster whose strategy was a lock-in system, customers had a maximal CLV. The results suggested that the delta model with these three strategies could act as the CLV developers in two stages: conversion of transient customers to attached customers and conversion of attached customers to locked-in customers. Research limitations/implications One of the limitations of this study was the lack of access to all the bank accounts and assessment of only the strategy type, while highlighting the exact association between every component of the strategies (e.g. structure, environment, etc.) and CLV as a dependent variable deemed to be of a great necessity. Hence, it is recommended that several studies on the relationships presented in this paper be performed to provide further insights into and guidelines on this issue in the future. Practical implications This study emphasized the relevance of strategy and CLV. Managers should differently treat customers in distinct CLV and loyalty levels. In other words, managers must segment their customers based on CLV and apply appropriate strategies for each segment. Originality/value This research tried to fulfill an identified need to study how strategy can be effect CLV through the application of the delta model with three strategic options.
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Sridhar, Ashok, and Michael Corbey. "Customer Profitability Analyses and Customer Lifetime Value." Maandblad Voor Accountancy en Bedrijfseconomie 89, no. 7/8 (2015): 265–73. http://dx.doi.org/10.5117/mab.89.31335.

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The main objective of this paper is to compare two key approaches in the !eld of Customer Accounting (CA), namely Customer Pro!tability Analysis (CPA) and Customer Lifetime Value (CLV). While CPA is a retrospective analysis of past accruals that represent the results of doing business with a customer over a certain, mostly single-period of time, CLV is a predictive measure of future customer-related cash "ows over a certain (multi-)period of time. This paper draws on the state-ofthe- art knowledge in the Customer Accounting (CA) literature to identify the impacts of CPA and CLV on managerial decision-making. It also offers recommendations as to the scenarios in which these metrics should be deployed in order to arrive at meaningful managerial decisions, and highlights their collective limitations.
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Kumar, V., R. Venkatesan, and B. Rajan. "Implementing profitability through a customer lifetime value management framework." GfK Marketing Intelligence Review 1, no. 2 (2009): 32–43. http://dx.doi.org/10.2478/gfkmir-2014-0076.

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Abstract Global CRM software spending was $7.8 billion in 2007 and is projected to reach $8.9 billion in 2008. Further, CRM software sales will touch $13.3 billion by 2012. These software and processes have made it possible for companies to gather and analyze large amounts of data on their existing and prospective customers. This article shows how customer-level data can lead to increased customer profitability through (a) selection of the right customers by using the Customer Lifetime Value (CLV) metric, (b) the nurturing of those right customers and, © re-allocation of resources to the profitable customers. Due to this approach profitable management of individual customers is the basis for growth in firm profitability. A case study will show how IBM used CLV as an indicator of customer profitability and allocated marketing resources based on CLV
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Safari, Fariba, Narges Safari, and Gholam Ali Montazer. "Customer lifetime value determination based on RFM model." Marketing Intelligence & Planning 34, no. 4 (2016): 446–61. http://dx.doi.org/10.1108/mip-03-2015-0060.

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Purpose – One of the salient challenges in customer-oriented organizations is to recognize, segment and rank customers. Customer segmentation is usually based on customer lifetime value (CLV) measured by three purchase variables: “Recency,” “Frequency” and “Monetary.” However, due to the ambiguity of these variables, using deterministic approach is not appropriate. For tackling this matter, the purpose of this paper is to propose a new method of customer segmentation and ranking by combining fuzzy clustering (as a segmentation method) and fuzzy AHP (as a ranking method). Design/methodology/approach – First, customers are classified based on purchase variables using fuzzy c-means clustering algorithm. Second, the variables are weighed applying an optimized version of AHP method. Considering the derived weights and customer groups, this paper follows to ranks segments based on CLV. The developed methodology has been implemented for a large IT company in Iran. Findings – The results show a tremendous capability to the company to evaluate his customers by dividing them into nine ranked segments. The validity of clusters has been submitted. Research limitations/implications – For researchers, this study provides a useful literature by combining FCM and an optimized version of fuzzy AHP in order to cover the limitations of previous methodologies. For organizations, this study clarifies the procedure of customer segmentation by which they can improve their marketing activities. Practical implications – Managers can consider the proposed CLV calculation methodology for selling the next best services/products to the group of customers that are more valuable, by calculating the entire lifetime value of the customers. Originality/value – This study contributes to the process of customer segmentation based on CLV, proposing a new method which covers the limitations of previous customer segmentation methods.
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Weng, Cheng-Hsiung, and Tony Cheng-Kui Huang. "Knowledge acquisition of association rules from the customer-lifetime-value perspective." Kybernetes 47, no. 3 (2018): 441–57. http://dx.doi.org/10.1108/k-03-2016-0042.

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Purpose Customer lifetime value (CLV) scoring is highly effective when applied to marketing databases. Some researchers have extended the traditional association rule problem by associating a weight with each item in a transaction. However, studies of association rule mining have considered the relative benefits or significance of “items” rather than “transactions” belonging to different customers. Because not all customers are financially attractive to firms, it is crucial that their profitability be determined and that transactions be weighted according to CLV. This study aims to discover association rules from the CLV perspective. Design/methodology/approach This study extended the traditional association rule problem by allowing the association of CLV weight with a transaction to reflect the interest and intensity of customer values. Furthermore, the authors proposed a new algorithm, frequent itemsets of CLV weight (FICLV), to discover frequent itemsets from CLV-weighted transactions. Findings Experimental results from the survey data indicate that the proposed FICLV algorithm can discover valuable frequent itemsets. Moreover, the frequent itemsets identified using the FICLV algorithm outperform those discovered through conventional approaches for predicting customer purchasing itemsets in the coming period. Originality/value This study is the first to introduce the optimum approach for discovering frequent itemsets from transactions through considering CLV.
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Kumar, V. "A Theory of Customer Valuation: Concepts, Metrics, Strategy, and Implementation." Journal of Marketing 82, no. 1 (2018): 1–19. http://dx.doi.org/10.1509/jm.17.0208.

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Customer value refers to the economic value of the customer's relationship with the firm. This study approaches the topic of customer value for measuring, managing, and maximizing customer contributions by proposing a customer valuation theory (CVT) based on economic principles that conceptualizes the generation of value from customers to firms. The author reviews the established economic theories for valuing investor assets (e.g., stocks) and draws a comparison to valuing customer contributions. Furthermore, the author recognizes the differences in the guiding principles between valuing stocks and valuing customers in proposing CVT. Using CVT, the author discusses the concept of customer lifetime value (CLV) as the metric that can provide a reliable, forward-looking estimate of direct customer value. In addition, economic models to estimate CLV, ways to manage CLV using portfolio management principles, and strategies to maximize CLV are discussed in detail. The author extends the customer value concept by discussing ways that a customer can add value to the firm indirectly through incentivized referrals, social media influence, and feedback. Finally, the benefits of CVT to multiple constituencies are offered.
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Nikkhahan, B., and M. J. Tarokh. "Citizen Lifetime Value in E-Government." International Journal of Customer Relationship Marketing and Management 2, no. 3 (2011): 26–41. http://dx.doi.org/10.4018/jcrmm.2011070102.

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Customer Lifetime Value (CLV) is one of the most important measures of valuing the customers in private sector. CLV calculates customer contribution in the profits of organization. In this paper Citizen Lifetime Value (CzLV) is introduced to measure the financial value of citizens for the government. CzLV evaluates citizen contribution in cost reduction of the organization. This measure can be calculated based on past behavior of citizens in using the service and cost reduction of using online services rather than offline ones. Logistic regression is employed as a data mining technique to predict future use of online services by citizens. A service of Tehran.ir called “137,” one of the most important portals of Iran’s E-government, is considered as a case study. CzLV for the citizens of this service is calculated and four citizen segments are specified. Then each segment is evaluated based on different characteristic of citizens, and suitable strategies are presented to build more financial values for the organization.
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Dissertations / Theses on the topic "Customer lifetime value (CLV)"

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Barreto, Iná Futino. "Resultados de marketing de relacionamento: proposição de modelo por meio de mapeamento cognitivo." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/12/12139/tde-01102015-152612/.

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Dada a crescente importância do relacionamento empresa-cliente e a pluralidade de modelos que discutam os elementos e resultados desse tipo de atividade, esta pesquisa buscou entender melhor a atividade de marketing de relacionamento e seus resultados por meio da análise de como os profissionais dessa área enxergam as relações entre os constructos relevantes, a fim de buscar desenvolver um modelo que expresse mais claramente como os profissionais da área entendem que os resultados de marketing de relacionamento são alcançados. O tema é tratado com base em uma revisão teórica que explora o conceito de marketing de relacionamento e seus principais elementos, o processo de modelagem, e o processo de mapeamento cognitivo. A partir da revisão teórica, foram listados onze constructos de marketing de relacionamento, que foram, então, analisados por 35 profissionais da área. Assim foram traçados 35 mapas cognitivos individuais que apontam como cada entrevistado entende as interações entre os elementos do marketing de relacionamento. Com base nas visões de cada indivíduo, foi traçado um mapa cognitivo agregado que aponta o entendimento médio dos entrevistados. A análise desse mapa permitiu identificar como, de acordo com a visão dos profissionais pesquisados, os elementos de marketing de relacionamento se influenciam mutuamente e quais elementos têm maior ou menor impacto no resultado final (aqui considerado como o custumer lifetime value - CLV). Por fim, foi feita análise de cluster para identificar a possível existência de algum tipo de agrupamento de respostas. Nenhum padrão significativo foi encontrado<br>Given the growing importance of activities related to the relationship between company and client, and the plurality of models to discuss the elements and results of this type of activity, better understanding the relationship marketing activity and it\'s results is important, in order to seek to develop a model that express more clearly how relationship marketing results are achieved. The theme is treated from a theoretical review based on the concept of relationship marketing and its key elements, the modeling process, and the process of cognitive mapping. Eleven contructos of relationship were listed from the theoretical review, and were then analyzed by 35 marketing professionals. Thus 35 individual maps which indicate how each respondent understands the interactions between the elements of relationship marketing have been traced. Based on the views of each individual, was plotted an aggregate map that shows the average understanding of the respondents. The analysis of this map has allowed us to identify, in accordance with the vision of
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Elinder, Zacharias, and Jonas Berglöf. "Med kunden i fokus? : En studie av hur kundklubbar påverkar verksamheten inom svenska företag." Thesis, Uppsala University, Department of Business Studies, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-107566.

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<p>Varje dag använder sig miljontals svenskar av någon form av medlems- eller kundklubbskort när de handlar i butik, kontaktar en kundtjäst eller loggar in på ett företags hemsida. Motiven till detta kan förstås vara olika - det kan vara smidigt, lönsamt eller nödvändigt för att överhuvudtaget få den hjälp och service man önskar. För företagen är denna registrering å andra sidan ett effektivt sätt att samla information om sina kunder som ett led i deras lojalitetsskapande arbete mot kund. Tidigare, internationella studier av CRM visar dock på att företagen inte utnyttjar den information de har om kunder för att verkligen styra verksamheten.</p><p>Syftet med denna uppsats är att studera om detta är ett aktuellt problem även bland svenska företag genom en enkätundersökning riktad till CRM- och kundklubbsansvariga vid svenska företag. Denna undersökning har utarbetats utifrån Cuthbertsons tre kriterier för att avgöra om en organisation är kundorienterade eller ej.</p><p>Resultat visar att de flesta företag som deltog i studien inte använder informationen man samlar in från kunderna i någon större utsträckning. Däremot visar resulataten att företag med äldre kundklubbar samt med höga medlemsantal generellt är bättre på att sprida och använda den kunskap som kundklubben samlar in. Skälen till att kundinformation inte används i större utsträckning beror enligt vår analys på frånvaron av fungerande intern infrastrauktur för att sprida inhämtad kunddata, kundklubben har för få medlemmar och låg ålder vilket påverkar dess interna status samt att kundklubben främst betraktas som ett register för riktad marknadsföring snarare än som ett redskap för att styra företagens verksamhet i stort.</p>
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Ljungehed, Jesper. "Predicting Customer Churn Using Recurrent Neural Networks." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210670.

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Churn prediction is used to identify customers that are becoming less loyal and is an important tool for companies that want to stay competitive in a rapidly growing market. In retail, a dynamic definition of churn is needed to identify churners correctly. Customer Lifetime Value (CLV) is the monetary value of a customer relationship. No change in CLV for a given customer indicates a decrease in loyalty. This thesis proposes a novel approach to churn prediction. The proposed model uses a Recurrent Neural Network to identify churners based on Customer Lifetime Value time series regression. The results show that the model performs better than random. This thesis also investigated the use of the K-means algorithm as a replacement to a rule-extraction algorithm. The K-means algorithm contributed to a more comprehensive analytical context regarding the churn prediction of the proposed model.<br>Illojalitet prediktering används för att identifiera kunder som är påväg att bli mindre lojala och är ett hjälpsamt verktyg för att ett företag ska kunna driva en konkurrenskraftig verksamhet. I detaljhandel behöves en dynamisk definition av illojalitet för att korrekt kunna identifera illojala kunder. Kundens livstidsvärde är ett mått på monetärt värde av en kundrelation. En avstannad förändring av detta värde indikerar en minskning av kundens lojalitet. Denna rapport föreslår en ny metod för att utföra illojalitet prediktering. Den föreslagna metoden består av ett återkommande neuralt nätverk som används för att identifiera illojalitet hos kunder genom att prediktera kunders livstidsvärde. Resultaten visar att den föreslagna modellen presterar bättre jämfört med slumpmässig metod. Rapporten undersöker också användningen av en k-medelvärdesalgoritm som ett substitut för en regelextraktionsalgoritm. K-medelsalgoritm bidrog till en mer omfattande analys av illojalitet predikteringen.
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Bellová, Simona. "Hodnota životního cyklu zákazníka." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2018. http://www.nusl.cz/ntk/nusl-371848.

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Diploma thesis is focusing on issues of a customer lifetime value in the construction company and in the companies in general. Theoretical part is focusing on the importance of customer value in the company and on various types of calculations of customer lifetime value. Practical part is describing specific calculations of customer lifetime value in the construction company, their analysis and evaluations.
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Marshan, Alaa. "Enhancing the human sensemaking process with the use of social network analysis and machine learning techniques." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/16399.

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Sensemaking is often associated with processing large or complex amount of data obtained from diverse and distributed sources. Sensemaking enables leaders to have a better grasp of what the data represents and what insights they can get from it. Thus, sensemaking is considered extremely important in mature markets where the competition is fierce. To-date, the research base on sensemaking has not moved far from the conceptual realm, however. In response, this research provides a conceptual framework that explains the core processes of sensemaking - noticing, interpretation and action - and examines how emerging technologies such as Social Network Analysis (SNA) and Machine Learning (ML) techniques help to enhance the human sensemaking process in generating valuable insights during data analysis. Design Science Research (DSR) is adopted as a research methodology in the context of financial transactional data analysis, aiming to make sense of the data while exploring conceptions of customer value for a mainstream commercial bank alongside the perceived need for banking products. Three analytical models are introduced, examining Connected Customer Lifetime Value (CCLV), Network Relationship Equity (NRE) and product purchasing frequency based on customer 'personas'. The former models employ SNA techniques in providing novelty, the latter combines the outcomes of SNA with ML clustering algorithms to provide a base on which product holdings and purchase frequency analysis are overlaid - providing a novel form of recommendation. Ongoing evaluation of the developed models is used to explore the nuances of the sensemaking process and the ability of such models to support that process (in the given domain).
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Madeira, Maria João da Costa. "Customer LifeTime Value." Master's thesis, FEUC, 2014. http://hdl.handle.net/10316/27594.

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Relatório de estágio do mestrado em Gestão, apresentado à Faculdade de Economia da Universidade de Coimbra, sob a orientação de Arnaldo Coelho, António Fery Antunes e António Oliveira Antunes.<br>Este relatório tem por objetivo traduzir o passado em quatro meses de trabalho, o período do meu estágio curricular. O tema escolhido foi o Customer LifeTime Value (CLV), um assunto atual, que tem dado origem a inúmeros estudos conceptuais e empíricos. Com este projeto pretendo mostrar que a empresa onde realizei o meu estágio, Banco Comercial Português, S.A. está cada vez mais preocupada em investir no relacionamento com os seus clientes. Hoje em dia é impossível para setor dos serviços sobreviver sem uma estratégia focada no marketing relacional, em particular pretendo comprovar esta reflexão na instituição onde decorreu o meu estágio. Tendo o próprio conceito de marketing como o ponto de partida, irei começar o meu trabalho explicando as origens do marketing de relacionamento, um conceito focado no cliente e na sua satisfação, com o intuito de o fidelizar. A ideia não é completamente nova, desde as primeiras trocas comerciais reconhecia-se que manter uma relação com um cliente, que não fosse apenas uma simples troca esporádica, seria benéfico para ambas as partes. Assim, os clientes podem beneficiar de eventuais facilidades de pagamento, descontos e acima de tudo, um conhecimento prévio da qualidade do produto, enquanto os comerciantes beneficiam de lucro imediato. Hoje em dia, existem algumas empresas pequenas que conseguiram sobreviver graças à relação que eles têm vindo a construir com seus clientes ao longo dos anos. Em seguida abordarei a temática da lealdade como vínculo inevitável desta área de estudo. Apenas o desenvolvimento de uma relação de proximidade com o cliente por si só não basta, deve existir um esforço da entidade para o conseguir fidelizar, impulsionando nele a lealdade para com a instituição e/ou a marca. Tudo isto serve de base ao tema central deste estudo, o CLV. Investir num relacionamento estável pode dar origem a retornos significativos, adicionalmente ter a capacidade de prever com precisão o valor dos clientes trará inevitavelmente um enorme impacto sobre a capacidade de tomar decisões inteligentes. Esta é a lógica seguida pela metodologia CLV que detalharei. Os resultados obtidos permitem-me dizer que esta é uma empresa bem consciente da importância da área em estudo CLV, uma vez que faz uso de fatores relacionais, implementa-os ativamente na sua formulação estratégica como fontes de vantagem competitiva.
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Wakabayashi, Muroya José Luis. "La Aplicación del Valor de Vida del Cliente en la Gestión de la Relación con el Distribuidor en Empresas de Consumo Masivo de Productos Empaquetados de Lima, Perú. Un Estudio de Casos Múltiple." Doctoral thesis, Universitat Ramon Llull, 2011. http://hdl.handle.net/10803/9185.

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La gestió de la relació amb el client (CRM) és el procés en què es creen relacions amb els clients i altres actors al llarg de les seves vides. Així, a la base d'aquest procés hi ha el concepte de CLV, conegut com el valor del cicle de vida del client (customer lifetime value), que permet calcular tant el valor net del client com la seva rendibilitat per a l'empresa. <br/><br/>Aquesta tesi destaca el fet que el màrqueting teòric ha desenvolupat diferents camps d'aplicació per afrontar el procés de CRM. Un d'aquests, que cada vegada és més important, és la gestió de la relació amb el canal de distribució. <br/><br/>Aquesta tesi és un intent per cobrir el buit que hi ha en la recerca de màrqueting sobre aquest tema i esbrinar el veritable paper del CLV en un context concret d'aplicació: les empreses de consum de masses de Lima i els seus distribuïdors. Aquest camp resta gairebé inexplorat i ha estat poc investigat, malgrat que el procés de CMR en el mercat de masses i la relació amb els distribuïdors constitueixen importants camps d'aplicació per al CLV. <br/><br/>A partir de l'anàlisi de casos de tres diferents empreses peruanes, mitjançant entrevistes i observacions realitzades al seu personal, aquesta tesi investiga l'aplicació del CLV com a concepte clau i com a eina de mesurament en els processos de gestió de la relació (CRM) amb els seus canals de distribució o intermediaris. <br/><br/>L'estudi s'ha dut a terme al Perú perquè aquest país té unes característiques similars als altres països llatinoamericans i la regió gairebé no disposa de cap recerca en CMR. Per això, aquest treball espera proporcionar informació significativa sobre l'aplicació del concepte dogmàtic de CMR. <br/><br/>La tesi argüeix que, malgrat que l'evolució cap a una aproximació relacional del màrqueting s'ha estès, la pràctica encara difereix de la teoria en molts mercats, com s'ha observat a les tres empreses estudiades. Per aquest motiu, aquest treball de recerca pot constituir un punt de partida per a investigacions més profundes en la matèria.<br>La gestión de la relación con el cliente (CRM) es el proceso en el que se crean relaciones con los clientes y otros actores a lo largo de sus vidas. Así, en la base de ese proceso se encuentra el concepto del CLV, conocido como valor de ciclo de vida del cliente (customer lifetime value), que permite calcular tanto el valor neto del cliente y su rentabilidad para la empresa. <br/> <br/>Esta tesis pone resalta el hecho de que el marketing teórico ha desarrollado diferentes campos de aplicación para encarar el proceso de CRM. Una de estas, y cada vez más importante, es la gestión de relación con el canal de distribución. Además, puesto que este tema constituye un vacío en la investigación de marketing, esta tesis constituye un intento para reducirlo y averiguar el verdadero papel del CLV en un contexto particular de aplicación: las empresas de consumo masivo de Lima y sus distribuidores. Este campo permanece casi inexplorado y cuenta con escasa investigación a pesar de que el proceso de CMR en el mercado masivo y la relación con los distribuidores constituyen importantes campos de aplicación para el CLV. <br/><br/>Mediante el análisis de casos de tres diferentes empresas peruanas, mediante entrevistas y observaciones realizadas al personal de las mismas, esta tesis investiga la aplicación del CLV como concepto clave y como herramienta de medición en los procesos de gestión de la relación (CRM) con sus canales de distribución o intermediarios. Este estudio se llevó a cabo en Perú porque este país comparte características similares con el resto de países latinoamericanos y esta región casi no cuenta con investigación en CMR. Por ello este trabajo espera brindar información significativa sobre la aplicación del concepto dogmatico de CMR. <br/><br/>Esta tesis arguye que a pesar de que la evolución hacia una aproximación relacional del marketing se ha extendido, todavía la práctica difiere de la teoría en muchos mercados, como se ha observado en las tres compañías estudiadas, por tal razón el presente trabajo de investigación puede constituir un punto de partida para investigaciones más profundas al respecto.<br>The customer relationship management (CRM) is the process where relationships with customers and other actors are created throughout their lifecycle. Therefore, in the very foundations of this process is CLV, a key concept known as well as customer lifetime value, that allows estimating not only the customer net value over a long period of time , but also his profitability for the company. <br/><br/>This dissertation remarks the fact that theoretical Marketing has developed different fields of application to face the complex process of CRM. One of them, in increasing importance, is the CRM with the distribution channel. Since this issue means a gap in marketing research, this dissertation constitutes an attempt to reduce it and find out the very role of CLV when CRM takes place in a particular context of application: massive consume companies from Lima and their distributors. This field is almost unexplored and has little research despite the fact that CRM process in the massive market and the relationship with distributors constitute important fields of application for the CLV. <br/><br/>Through an analysis of three cases of different Peruvian companies, by interviewing their staff, this dissertation investigates the application of CLV as a key concept and as a measuring tool for CRM process with the distribution channel or intermediaries. This study took place in Peru because this country has similar characteristics with the rest of Latin American countries and this region has almost no research in CRM process. That is why this dissertation expects to add significant information about the application of the dogmatic concept of CRM. <br/><br/>This dissertation argues that despite the fact that an evolutional shift to a Marketing relationship approach is extended around the world, theory and practice still differs each other in a number of markets, as it is observed in the companies selected to this research. Thus this study could be the starting point of more and deeper research about it.
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XU, Chen. "Customer lifetime value : an integrated data mining approach." Digital Commons @ Lingnan University, 2006. https://commons.ln.edu.hk/cds_etd/3.

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Customer Lifetime Value (CLV) ---which is a measure of the profit generating potential, or value, of a customer---is increasingly being considered a touchstone for customer relationship management. As the guide and benchmark for Customer Relationship Management (CRM) applications, CLV analysis has received increasing attention from both the marketing practitioners and researchers from different domains. Furthermore, the central challenge in predicting CLV is the precise calculation of customer’s length of service (LOS). There are several statistical approaches for this problem and several researchers have used these approaches to perform survival analysis in different domains. However, classical survival analysis techniques like Kaplan-Meier approach which offers a fully non-parametric estimate ignores the covariates completely and assumes stationary of churn behavior along time, which makes it less practical. Further, segments of customers, whose lifetimes and covariate effects can vary widely, are not necessarily easy to detect. Like many other applications, data mining is emerging as a compelling analysis tool for the CLV application recently. Comparatively, data mining methods offer an interesting alternative with the fact that they are less limited than the conventional statistical approaches. Customer databases contain histories of vital events such as the acquisition and cancellation of products and services. The historical data is used to build predictive models for customer retention, cross-selling, and other database marketing endeavors. In this research project we discuss and investigate the possibility of combining these statistical approaches with data mining methods to improve the performance for the CLV problem in a real business context. Part of the research effort is placed on the precise prediction of LOS of the customers in concentration of a real world business. Using the conventional statistical approaches and data mining methods in tandem, we demonstrate how data mining tools can be apt complements of the classical statistical models ---resulting in a CLV prediction model that is both accurate and understandable. We also evaluate the proposed integrated method to extract interesting business domain knowledge within the scope of CLV problem. In particular, several data mining methods are discussed and evaluated according to their accuracy of prediction and interpretability of results. The research findings will lead us to a data mining method combined with survival analysis approaches as a robust tool for modeling CLV and for assisting management decision-making. A calling plan strategy is designed based on the predicted survival time and calculated CLV for the telecommunication industry. The calling plan strategy further investigates potential business knowledge assisted by the CLV calculated.
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Harman, David M. "Stochastic process customer lifetime value models with time-varying covariates." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2221.

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Customer lifetime value (CLV) is a forecasted expectation of the future value of a customer to the firm. There are two customer behavioral components of CLV that represent a particular modeling challenge: 1) how many transactions we expect from a customer in the future, and 2) how likely it is the customer remains active. Existing CLV models like the Pareto/NBD are valuable managerial tools because they are able to provide forward-looking estimates of transaction patterns and customer churn when the event of a customer leaving is unobservable, which is typical for most noncontractual goods and services. The CLV model literature has for the most part maintained its original assumption that the number of customer transactions follows a stable transaction process. Yet there are many categories of noncontractual goods and services where the stable transaction rate assumption is violated, particularly seasonal purchase patterns. CLV model estimates are further biased when there is an excess of customers with no repeat transactions. To address these modeling challenges, within this thesis I develop a generalized CLV modeling framework that combines three elements necessary to reduce bias in model estimates: 1) the incorporation of time-varying covariates to model data with transaction rates that change over time, 2) a zero-inflated model specification for customers with no repeat transactions, and 3) generalizes to different transaction process distributions to better fit diverse customer transaction patterns. This CLV modeling framework provides firms better estimates of the future activity of their customers, a critical CRM application.
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Baraniaková, Júlia. "Metódy výpočtu Customer Lifetime Value a ich aplikácia v oblasti kozmetiky." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-193617.

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The main goal of the diploma thesis is the description and comparison of existing methods for calculating the customer lifetime value at a firm. Second, minor goal is based on the comparison to choose a suitable method of calculation for an application in a real business unit. The used methodology contains detailed research of available foreign academic literature. Building on that a comparison of the methods based on selected criteria is conducted. Results of a questionnaire survey are used in the last chapter to provide specific sugestions for the possible marketing applications of CLV approach and calculation in a specific business unit.
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Books on the topic "Customer lifetime value (CLV)"

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Hofmann, Markus, and Markus Mertiens, eds. Customer-Lifetime-Value-Management. Gabler Verlag, 2000. http://dx.doi.org/10.1007/978-3-322-90218-4.

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Rust, Roland T. Driving customer equity: Linking customer lifetime value to strategic marketing decisions. Marketing Science Institute, 2001.

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A, Zeithaml Valarie, and Lemon Katherine N, eds. Driving customer equity: How lifetime customer value is reshaping corporate strategy. Free Press, 2000.

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Bejou, David, Timothy L. Keningham, and Lerzan Aksoy, eds. Customer Lifetime Value. Routledge, 2013. http://dx.doi.org/10.4324/9780203062661.

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Hofmann, Markus, and Markus Mertiens. Customer- Lifetime- Value- Management. Dr. Th. Gabler Verlag, 2003.

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Kumar, V. Customer Lifetime Value: The Path to Profitability. Now Publishers Inc, 2008.

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Zeithaml, Valarie, Roland Rust, and Katherine Lemon. Driving Customer Equity : How Customer Lifetime Value is Reshaping Corporate Strategy. Free Press, 2000.

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(Editor), David Bejou, Timothy L. Keiningham (Editor), and Lerzan Aksoy (Editor), eds. Customer Lifetime Value: Reshaping the Way We Manage to Maximize Profits. Best Business Books, 2006.

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(Editor), David Bejou, Timothy L. Keiningham (Editor), and Lerzan Aksoy (Editor), eds. Customer Lifetime Value: Reshaping the Way We Manage to Maximize Profits. Best Business Books, 2006.

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Aksoy, Lerzan, David Bejou, and Timothy L. Keningham. Customer Lifetime Value: Reshaping the Way We Manage to Maximize Profits. Taylor & Francis Group, 2016.

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Book chapters on the topic "Customer lifetime value (CLV)"

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Zezelj, Gordana. "Das CLV-Management-Konzept." In Customer-Lifetime-Value-Management. Gabler Verlag, 2000. http://dx.doi.org/10.1007/978-3-322-90218-4_1.

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Bruhn, Manfred, Dominik Georgi, and Stephan Schusser. "Einsatz des Customer Lifetime Value (CLV) im Commitmentgeschäft." In Management von CRM-Projekten. Gabler Verlag, 2004. http://dx.doi.org/10.1007/978-3-663-10718-7_17.

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Andon, Paul, Jane Baxter, and Graham Bradley. "Calculating Customer Lifetime Value (CLV): Theory and Practice." In Kundenwert. Gabler Verlag, 2003. http://dx.doi.org/10.1007/978-3-322-99328-1_12.

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Andon, Paul, Jane Baxter, and Graham Bradley. "Calculating Customer Lifetime Value (CLV): Theory and Practice." In Kundenwert. Gabler Verlag, 2001. http://dx.doi.org/10.1007/978-3-322-94626-3_11.

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Balasooriya, Isuru, Jordi Conesa, Enric Mor, and M. Elena Rodríguez. "Student Engagement Value (SEV): Adapting Customer Lifetime Value (CLV) for a Learning Environment." In Advances on P2P, Parallel, Grid, Cloud and Internet Computing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69835-9_56.

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Beck, Johann, and Norbert Beck. "Warum ist der Kundenlebenswert CLV (Customer Lifetime Value) entscheidend? Es kommt nicht auf das Outfit an …" In Service ist sexy! Gabler Verlag, 2012. http://dx.doi.org/10.1007/978-3-8349-7166-1_20.

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Gierl, Heribert, and Julia Koncz. "Customer Lifetime Value." In Das Handbuch Direct Marketing & More. Gabler Verlag, 2002. http://dx.doi.org/10.1007/978-3-322-90220-7_52.

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Kumar, V., and Bharath Rajan. "Customer Lifetime Value." In The Routledge Companion to Strategic Marketing. Routledge, 2020. http://dx.doi.org/10.4324/9781351038669-33.

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Hofmann, Markus, and Oliver Baumann. "Kein Shareholder Value ohne Customer Value." In Customer-Lifetime-Value-Management. Gabler Verlag, 2000. http://dx.doi.org/10.1007/978-3-322-90218-4_2.

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Blattberg, Robert C., Byung-Do Kim, and Scott A. Neslin. "Customer Lifetime Value: Fundamentals." In Database Marketing. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-72579-6_5.

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Conference papers on the topic "Customer lifetime value (CLV)"

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Permana, Dony, Sapto Wahyu Indratno, and Udjianna S. Pasaribu. "Study of behavior and determination of customer lifetime value(CLV) using Markov chain model." In 4TH INTERNATIONAL CONFERENCE ON MATHEMATICS AND NATURAL SCIENCES (ICMNS 2012): Science for Health, Food and Sustainable Energy. AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4868842.

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Lihua Wu, Lu Liu, and Jing Li. "Evaluating customer lifetime value for customer recommendation." In Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005. IEEE, 2005. http://dx.doi.org/10.1109/icsssm.2005.1499450.

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Han Jieping, Li Jiying, and Fan Wenyan. "Customer lifetime value model based on customer satisfaction." In 2010 2nd International Conference on Information Science and Engineering (ICISE). IEEE, 2010. http://dx.doi.org/10.1109/icise.2010.5690873.

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Chamberlain, Benjamin Paul, Ângelo Cardoso, C. H. Bryan Liu, Roberto Pagliari, and Marc Peter Deisenroth. "Customer Lifetime Value Prediction Using Embeddings." In KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2017. http://dx.doi.org/10.1145/3097983.3098123.

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Yean, Lim Chia, and Vincent K. T. Khoo. "Customer Relationship Management: Lifecycle of Predicting Customer Lifetime Value." In 2010 Second International Conference on Computer Research and Development. IEEE, 2010. http://dx.doi.org/10.1109/iccrd.2010.24.

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Lin, Jiann-Horng, and Hui-Ling Hung. "System Dynamics Simulation for Customer Lifetime Value." In Annual International Academic Conference on Business Intelligence and Data Warehousing. Global Science and Technology Forum, 2010. http://dx.doi.org/10.5176/978-981-08-6308-1_41.

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Permana, Dony, Syafriandi, and Nonong Amalita. "Model of Customer Lifetime Value with Two Customer and a Former Customer State." In Proceedings of the 2nd International Conference on Mathematics and Mathematics Education 2018 (ICM2E 2018). Atlantis Press, 2018. http://dx.doi.org/10.2991/icm2e-18.2018.3.

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Yean, Lim Chia, and K. T. Vincent Khoo. "Customer relationship management: Computer-assisted tools for customer lifetime value prediction." In 2010 International Symposium on Information Technology (ITSim 2010). IEEE, 2010. http://dx.doi.org/10.1109/itsim.2010.5561487.

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Rosset, Saharon, Einat Neumann, Uri Eick, Nurit Vatnik, and Yizhak Idan. "Customer lifetime value modeling and its use for customer retention planning." In the eighth ACM SIGKDD international conference. ACM Press, 2002. http://dx.doi.org/10.1145/775047.775097.

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Win, Than Than, and Khin Sundee Bo. "Predicting Customer Class using Customer Lifetime Value with Random Forest Algorithm." In 2020 International Conference on Advanced Information Technologies (ICAIT). IEEE, 2020. http://dx.doi.org/10.1109/icait51105.2020.9261792.

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