Document Type: Original Article

Authors

Department of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran.

Abstract

The present study attempts to establish a new framework to speculate customer lifetime value by a stochastic approach. In this research the customer lifetime value is considered as combination of customer’s present and future value. At first step of our desired model, it is essential to define customer groups based on their behavior similarities, and in second step a mechanism to count current value, and at the end estimate the future value of customers. Having a structure in modeling customer churn is also important to have complete customer lifetime value computation. Clustering as one of data mining techniques is practiced to help us analyze the different groups of customers, and extract mathematical model to count the customers value. Thereafter by using Markov chain model as stochastic approach, we predict future behavior of the customer and as a result, estimate future value of different customers. The proposed model is demonstrated by the customer demographic data and historical transaction data in a composite manufacturing company in Iran. 

Keywords

Abrahamsson, S., (2015). “Determination of potential value drivers by identifing customer expectations and percieved value. Lappeenranta university of technology.

Aeron, H. et al., (2008). “A metric for customer lifetime value of credit card customers”, Database Marketing & Customer Strategy Management, Vol. 15, No. 3, pp.153–168.

Bagheri, F. and Tarokh, M.J., (2014). “Customer Behavior mining based on RFM model to improve the customer relationship management”, Journal of Industrial Engineering and Management Studies, Vol. 1, No. 1, pp.43–57.

Berger, P.D. and Nasr, N.I., (1998). "Customer lifetime value: Marketing models and applications", Journal of Interactive Marketing, Vol. 12, No. 1, pp.17–30.

Chan, S.L., Ip, W.H. and Cho, V., (2010). "Expert Systems with Applications A model for predicting customer value from perspectives of product attractiveness and marketing strategy", Expert Systems with Applications, Vol. 37, pp.1207–1215.

Chen, Z. and Fan, Z., (2013). "Knowledge-Based Systems Dynamic customer lifetime value prediction using longitudinal data : An improved multiple kernel SVR approach", Knowledge-Based Systems, Vol. 43, pp.123–134.

Cheng, C. et al., (2012). "Customer lifetime value prediction by a Markov chain based data mining model : Application to an auto repair and maintenance company in Taiwan", Scientia Iranica, Vol. 19, No. 3, pp.849–855.

Ching, W.-K., Michael, N. and Wong, K., (2004). "Customer Lifetime Value: Stochastic Optimisation Approah", Journal of Operational Research Society.

Clempner, J.B. and Poznyak, A.S., (2014). "SIMPLE COMPUTING OF THE CUSTOMER LIFETIME VALUE : A FIXED LOCAL-OPTIMAL POLICY APPROACH", Journal of Systems Science and Systems Engineering, Vol. 23, No. 4, pp.439–459.

Danaee, H. et al., (2013). "Classifying and Designing Customer ’ s Strategy Pyramid by Customer Life Time Value ( CLV ) ( Case study : Shargh Cement Company )", Journal of Basec Applied Science Research, Vol. 3, No. 7, pp.473–483.

Drea, J.T., Marlow, L. and Lauren, K., (2017). "Applying Customer Lifetime Value to Major League Baseball Season Tickets', Journal of Applied Sport Management2, Vol. 9, No. 2, pp.37–49.

Dwyer, F.R., (1997). "Customer Lifetime Valuation to Support Marketing Decision Making", Journal of Direct Marketing, 11(4), pp.6–13.

Ekinci, Y., Ülengin, F., et al., (2014). "Analysis of customer lifetime value and marketing expenditure decisions through a Markovian-based model", European Journal of Operational Research, Vol. 237, No. 1, pp.278–288.

Ekinci, Y., Ulengin, F. and Uray, N., (2014). "Using customer lifetime value to plan optimal promotions", The Service Industries Journal, Vol. 34, No. 2, pp.103–122.

Ekinci, Y., Uray, N. and Ulengin, F., (2014). "A customer lifetime value model for the banking industry : a guide to marketing actions", European Journal of Marketing, Vol. 48, pp.761–784.

EsmaeiliGookeh, M. and Tarokh, M., (2013). "Customer Lifetime Value Models: A literature survey", International Journal of Industrial Engineering and Production Management, Vol. 24, No. 4, pp.317–336.

Esmaeiligookeh, M. and Tarokh, M.J., (2017). "A Novel Customer Churn Model by Markov Chain", In Electrical & Computer Engineering. pp. 1–11.

Estrella-ramón, A., Sánchez-pérez, M. and Swinnen, G., (2016). "Estimating Customer Potential Value using panel data of a Spanish bank", Journal of Business Economics and Management, Vol. 17, No. 4, pp.580–597.

Fader, P.S., Hardie, B.G.S. and Lee, K.L., (2005). "?Counting Your Customers? the Easy Way: An Alternative to the Pareto/NBD Model", Marketing Science, Vol. 24, No. 2, pp.275–284.

Farzanfar, E. and Delafrooz, N., 2016. "Determining the Customer Lifetime Value based on the Benefit Clustering in the Insurance Industry', Indian Journal of Science and Technology, Vol. 9, No. 1, pp.1–8.

Gupta, S. et al., (2006). "Modeling Customer Lifetime Value", Journal of Service Research, Vol. 9, No. 2, pp.139–155.

Haenlein, M., Kaplan, A.M. and Beeser, A.J., (2007). "A Model to Determine Customer Lifetime Value in a Retail Banking Context", European Management Journal, Vol. 25, No. 3, pp.221–234. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0263237307000163 [Accessed August 19, 2013].

Hamdi, K. and Zamiri, A., (2016). "Identifying and Segmenting Customers of Pasargad Insurance Company Through RFM Model (RFM)". International Business Management, Vol. 10, No. 18, pp.4209–4214.

Ho, T., Park, Y. and Zhou, Y., (2005). "Incorporating Satisfaction into Customer Value Analysis : Optimal Investment in Lifetime Value".

Holm, M., Kumar, V. and Rohde, C., (2012). "Measuring customer profitability in complex environments : an interdisciplinary contingency framework", Journal of Academic Marketing Science, Vol. 40, pp.387–401.

Horák, P., (2017). "Customer Lifetime Value in B2B Markets : Theory and Practice in the Czech Republic", International Journal of Business and Management, Vol. 12, No. 2, pp.47–55.

Hu, H. et al., (2018). "Strategies for new product di ff usion : Whom and how to target ?", Journal of Business Research, Vol. 83, pp.111–119.

Hwang, H., (2015). "A Dynamic Model for Valuing Customers : A Case Study", Advanced Science and Technology Letters, Vol. 120, pp.56–61.

Hwang, H., (2016). "A Stochastic Approach for Valuing Customers : A Case Study", International Journal of Software Engineering and Its applications, Vol. 10, No. 3, pp.67–82.

Khajvand, M. and Jafar, M., (2011). "Estimating customer future value of different customer segments based on adapted RFM model in retail banking context", Procedia Computer Science, Vol. 3, pp.1327–1332.

Koopaei, M., (2009). "A New Method for Ranking Changes in Customer ’ s Behavioral Patterns in Department Stores", In ICEC ’09. pp. 317–322.

Kumar, V. and George, M., (2007). "Measuring and maximizing customer equity: a critical analysis", Journal of the Academy of Marketing Science, 35(2), pp.157–171.

Lin, H. et al., (2017). "Predicting customer lifetime value for hypermarket private label products", Journal of Business Economics and Management, Vol. 18, No. 4, pp.619–635.

Liu, D.-R. and Shih, Y.-Y., (2005). "Integrating AHP and data mining for product recommendation based on customer lifetime value", Information & Management, Vol. 42, No. 3, pp.387–400. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0378720604000394 [Accessed August 19, 2013].

Miguéis, V.L. et al., (2012). "Modeling partial customer churn: On the value of first product-category purchase sequences", Expert Systems with Applications, Vol. 39, No. 12, pp.11250–11256.

Nikkhahan, B. et al., (2011). "Customer lifetime value model in an online toy store", Journal of engineering international, Vol. 7, No 12, pp.19–31.

Pachidi, S., Spruit, M. and Weerd, I. Van De, (2014). "Computers in Human Behavior Understanding users ’ behavior with software operation data mining", Computers in Human Behavior, Vol. 30, pp.583–594.

Peker, S., Kocyigit, A. and Eren, P.E., (2017). "LRFMP model for customer segmentation in the grocery retail industry: a case study", Marketing Intelligence & Planning, Vol. 35, No. 4, pp.544–559.

Pfeifer, P.E. and Carraway, R.L., (2000). "Modeling customer relationships as Markov chains", Journal of Interactive Marketing, Vol. 14, No. 2, pp.43–55. Available at: http://linkinghub.elsevier.com/retrieve/pii/S1094996800702052..

Ryals, L.J. and Knox, S., (2005). "Measuring Risk-adjusted Customer Lifetime Value and its Impact on Relationship Marketing Strategies and Shareholder Value", European Journal of Marketing, Vol. 39, No. 5, pp.456–472.

Safari, F., Safari, N. and Montazer, G.A., (2016). "Customer lifetime value determination based on RFM model", Marketing Intelligence & Planning, Vol. 34, No. 4, pp.446–461.

Safari, M. et al., (2014). "Analyzing the applications of customer lifetime value ( CLV ) based on benefit segmentation for the banking sector". Procedia - Social and Behavioral Sciences, Vol. 109, pp.590–594. Available at: http://dx.doi.org/10.1016/j.sbspro.2013.12.511.

Samizadeh, R., (2015). "A New Model for the Calculation of Customer Life-time Value in Iranian Telecommunication Companies", International Journal of Management, Accounting and Economics, Vol. 2, No. 5, pp.394–403.

Segarra-moliner, J.R. and Moliner-tena, M.Á., (2016). "Customer equity and CLV in Spanish telecommunication services", Journal of Business Research, Vol. 69, No. 10, pp.4694–4705. Available at: http://dx.doi.org/10.1016/j.jbusres.2016.04.017.

Sunder, S., (2015). Measuring the Lifetime Value of a Customer in the Consumer Packaged Goods ( CPG ) industry.

Tseng, F. and Wang, C., (2013). "Computers in Human Behavior Why do not satisfied consumers show reuse behavior ? The context of online games", Computers in Human Behavior, Vol. 29, No. 3, pp.1012–1022. Available at: http://dx.doi.org/10.1016/j.chb.2012.12.011.

Wang, J. and Huang, R., (2016). "Can You Get a Ticket ? Adaptive Railway Booking Strategies by Customer Value", Journal of Public Transportation, Vol. 19, No. 4, pp.1–17.

Yeh, I.-C., Yang, K.-J. and Ting, T.-M., (2009). "Knowledge discovery on RFM model using Bernoulli sequence", Expert Systems with Applications, Vol. 36, No. 3, pp.5866–5871.

 Zhang, H., Liang, X. and Wang, S., (2016). "Customer value anticipation , product innovativeness , and customer lifetime value : The moderating role of advertising strategy", Journal of Business Research, Vol. 69, No. 9, pp.3725–3730.

Zhang, Z. et al., (2015). "Profit Maximization Analysis Based on Data Mining and the Exponential Retention Model Assumption with Respect to Customer Churn Problems", In IEEE International Conference on Data Mining Workshop (ICDMW). pp. 1093–1097.