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F. Dwyer (1997)
Customer lifetime valuation to support marketing decision makingJournal of Direct Marketing, 11
M. Bhatt (2011)
Service Management and Marketing
P. Pfeifer, R. Carraway (2000)
Modeling customer relationships as Markov chainsJournal of Interactive Marketing, 14
V. Kumar, B. Rajan (2009)
Profitable Customer Management: Measuring and Maximizing Customer Lifetime ValueManagement Accounting Quarterly, 10
M. Haenlein, A. Kaplan, Anemone Beeser (2007)
A Model to Determine Customer Lifetime Value in a Retail Banking ContextEuropean Management Journal, 25
C. Gurau, A. Ranchhod
How to calculate the value of a customer – measuring customer satisfaction: a platform for calculating, predicting and increasing customer profitability
A. Labbi, Cesar Berrospi (2007)
Optimizing marketing planning and budgeting using Markov decision processes: An airline case studyIBM J. Res. Dev., 51
R. Minhas, E. Jacobs (1996)
Benefit segmentation by factor analysis: an improved method of targeting customers for financial servicesInternational Journal of Bank Marketing, 14
D. Jain, Siddharth Singh (2002)
Customer lifetime value research in marketing: A review and future directionsJournal of Interactive Marketing, 16
D. Peppers, M. Rogers
One to One Manager: An Executive's Guide to Custom Relationship Management
M. Roberts, P. Berger (1989)
Direct Marketing Management
Katja Gelbrich, Reza Nakhaeizadeh (2000)
Value Miner: A Data Mining Environment for the Calculation of the Customer Lifetime Value with Application to the Automotive Industry
P. Berger, Ruth Bolton, D. Bowman, Elten Briggs, Vikas Kumar, A. Parasuraman, Creed Terry (2002)
Marketing Actions and the Value of Customer AssetsJournal of Service Research, 5
K. Storbacka, T. Strandvik, C. Grönroos (1994)
Managing Customer Relationships for Profit: The Dynamics of Relationship QualityInternational Journal of Service Industry Management, 5
B. Liu, N. Petruzzi, D. Sudharshan (2007)
A service effort allocation model for assessing customer lifetime value in service marketingJournal of Services Marketing, 21
Russell Haley (1968)
Benefit Segmentation: A Decision-oriented Research ToolJournal of Marketing, 32
Sharad Borle, Siddharth Singh, D. Jain (2008)
Customer Lifetime Value MeasurementManag. Sci., 54
Harsha Aeron, T. Bhaskar, R. Sundararajan, Ashwani Kumar, Janakiraman Moorthy (2008)
A metric for customer lifetime value of credit card customersJournal of Database Marketing & Customer Strategy Management, 15
F. Mulhern (1999)
Customer Profitability Analysis: Measurement, Concentration, and Research DirectionsJournal of Interactive Marketing, 13
Ching-Hsue Cheng, You-Shyang Chen (2009)
Classifying the segmentation of customer value via RFM model and RS theoryExpert Syst. Appl., 36
Wendell Smith (1956)
Product Differentiation and Market Segmentation as Alternative Marketing StrategiesJournal of Marketing, 21
Ruth Bolton, P. Kannan, Matthew Bramlett (2000)
Implications of loyalty program membership and service experiences for customer retention and valueJournal of the Academy of Marketing Science, 28
J. Bult, T. Wansbeek (1995)
Optimal Selection for Direct MailMarketing Science, 14
E. Malthouse, Robert Blattberg (2005)
Can we predict customer lifetime valueJournal of Interactive Marketing, 19
V. Kumar, B. Rajan
Profitable management: measuring and maximizing customer lifetime value
P. Verhoef, B. Donkers
Erim Report Series Research in Management Predicting Customer Potential Value an Application in the Insurance Industry Bibliographic Data and Classifications
Dries Benoit, D. Poel (2009)
Benefits of quantile regression for the analysis of customer lifetime value in a contractual setting: An application in financial servicesExpert Syst. Appl., 36
Øyvind Helgesen (2006)
Are Loyal Customers Profitable? Customer Satisfaction, Customer (Action) Loyalty and Customer Profitability at the Individual LevelJournal of Marketing Management, 22
W. Ching, M. Ng, Karen Wong, E. Altman (2004)
Customer lifetime value: stochastic optimization approachJournal of the Operational Research Society, 55
R. Hecht-Nielsen (1989)
Theory of the backpropagation neural networkInternational 1989 Joint Conference on Neural Networks
P.D. Berger, R.N. Bolton, D. Bowman, E. Briggs, V. Kumar, A. Parasuraman, C. Terry
Marketing actions and the value of customer assets: a framework for customer asset management
L. Alfansi, A. Sargeant (2000)
Market segmentation in the Indonesian banking sector: the relationship between demographics and desired customer benefitsInternational Journal of Bank Marketing, 18
Prof Kumar, Girish Ramani, Timothy Bohling (2004)
Customer lifetime value approaches and best practice applicationsJournal of Interactive Marketing, 18
S. Chan, Andrew Ip, V. Cho (2010)
A model for predicting customer value from perspectives of product attractiveness and marketing strategyExpert Syst. Appl., 37
(2002)
Joint optimization of customer segmentation and marketing policy to maximize long-term profitability
B. Donkers, P. Verhoef, M. Jong (2007)
Modeling CLV: A test of competing models in the insurance industryQuantitative Marketing and Economics, 5
B. Stone (1975)
Successful Direct Marketing Methods
C. Gurau, A. Ranchhod (2002)
Measuring customer satisfaction: A platform for calculating, predicting and increasing customer profitabilityJournal of Targeting, Measurement and Analysis for Marketing, 10
P. Berger, Nada Bechwati (2001)
The allocation of promotion budget to maximize customer equityOmega-international Journal of Management Science, 29
G. Hartfeil
Bank One measures profitability of customers, not just products
S.S. Singh
Customer lifetime value analysis
Su-yeon Kim, Taesoo Jung, E. Suh, Hyunseok Hwang (2006)
Customer segmentation and strategy development based on customer lifetime value: A case studyExpert Syst. Appl., 31
Robert Blattberg, John Deighton (1996)
Manage marketing by the customer equity test.Harvard business review, 74 4
L. Ryals, S. Knox (2005)
Measuring risk‐adjusted customer lifetime value and its impact on relationship marketing strategies and shareholder valueEuropean Journal of Marketing, 39
Sunil Gupta, Dominique Hanssens, Bruce Hardie, Wiliam Kahn, Viveka Kumar, N. Lin, N. Ravishanker, S. Sriram (2006)
Modeling Customer Lifetime ValueJournal of Service Research, 9
Barry Howcroft, R. Hamilton, P. Hewer (2007)
Customer involvement and interaction in retail banking: an examination of risk and confidence in the purchase of financial productsJournal of Services Marketing, 21
A. Hughes (2005)
Strategic database marketing
B. Donkers, P.C. Verhoef
Predicting customer potential value: an application in the insurance industry
R. Venkatesan, V. Kumar, Timothy Bohling (2007)
Optimal Customer Relationship Management Using Bayesian Decision Theory: An Application for Customer SelectionJournal of Marketing Research, 44
Cindy Claycomb, Charles Martin (2001)
Building customer relationships: an inventory of service providers’ objectives and practicesJournal of Services Marketing
Hyunseok Hwang, Taesoo Jung, E. Suh (2004)
An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industryExpert Syst. Appl., 26
D. Morrison, Richard Chen, S. Karpis, Kathryn Britney (1982)
Modelling Retail Customer Behavior at Merrill LynchMarketing Science, 1
Ya-Yueh Shih, Chungui Liu (2003)
A method for customer lifetime value ranking — Combining the analytic hierarchy process and clustering analysisJournal of Database Marketing & Customer Strategy Management, 11
J. Nielsen (2002)
Internet technology and customer linking in Nordic bankingInternational Journal of Service Industry Management, 13
Teck-Hua Ho, Young-Hoon Park, Yong-Pin Zhou (2006)
Incorporating Satisfaction into Customer Value Analysis: Optimal Investment in Lifetime ValueSocial Science Research Network
Ya-Yueh Shih, Duen-Ren Liu (2008)
Product recommendation approaches: Collaborative filtering via customer lifetime value and customer demandsExpert Syst. Appl., 35
Purpose – The aim of this study is to develop an applicable and detailed model for customer lifetime value (CLV) and to highlight the most important indicators relevant for a specific industry – namely the banking sector. Design/methodology/approach – This study compares the results of the least square estimation (LSE) and artificial neural network (ANN) in order to select the best performing forecasting tool to predict the potential CLV. The performances of the models are compared by the hit ratio, which is calculated by grouping the customers as “top 20 per cent” and “bottom 80 per cent” profitable. Findings – Due to its higher performance; LSE based linear regression model is selected. The results are found to be highly competitive compared with the previous studies. This study shows that, beside the indicators mostly used in the literature in measuring CLV, two additional groups, namely monetary value and risk of certain bank services, as well as product/service ownership‐related indicators, are also significant factors. Practical implications – Organisations in the banking sector have to persuade their customers to use certain routine risk‐bearing transaction‐based services. In addition, the product development strategy has a crucial role to increase the CLV of customers because some of the product‐related variables directly increase the value of customers. Originality/value – The proposed model predicts potential value of current customers rather than measuring current value considered in the majority of previous studies. It eliminates the limitations and drawbacks of the majority of models in the literature through simple and industry‐specific method which is based on easily measurable and objective indicators.
European Journal of Marketing – Emerald Publishing
Published: Apr 8, 2014
Keywords: Artificial neural network; Least squares estimation; Customer lifetime value; Linear regression; Marketing decision
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