Iranian Journal of Information Management

Customer Lifetime Value Estimation IT Cooperation

Document Type : Original Article

Authors

1 Professor, Faculty of Management, University of Tehran, Tehran, Iran

2 Master of Information Technology Management, Faculty of Management, University of Tehran, Tehran, Iran

Abstract

Customer lifetime value (CLV) is an invaluable metric which plays a pivotal role in assessing the future worth of the customers and the profitability of them. To elaborate upon, CLV is an index so as to evaluate the potential as well as the practical worth of a wide variety of customers. So, it seems obvious that estimation of this metric in different cooperation, especially IT ones, can cause the organizations to identify the behaving trend of their customers so that the organizations can forecast their future purchase as well as the customers’ loyalty to their cooperation. Therefore, in this paper, we present a model in order to estimate the CLV in an IT cooperation. Hence, in the first step, we explain the concept of CLV metric, and its role in today’s customer analysis. Then, the next step has to do with presenting the RFM method and its parameters for assessing the CLV index. Our proposed case study is included 182 data of customers in an IT cooperation, which we used ordered logistic regression so as to analyze. In the experimental results section, our proposed method applying to this specific cooperation data demonstrates a better performance both in accuracy and precision in comparison with the popular methods.

Keywords

حسینی، محمد، و محمدرضا غلامیان 1390. طراحی یک متدولوژی مبتنی بر RFM جهت سنجش وفاداری مشتری با استفاده از تکنیک‌های داده‌کاوی. نشریه بین‌المللی مهندسی صنایع و مدیریت تولید، 22(2)، 171-179.
صنیعی آباده، محمد، سینا محمودی، و محدثه طاهرپرور. 1394. داده­کاوی کاربردی. تهران: نیاز دانش.
گنجعلی، مجتبی، و زهرا رضایی. 1389. تحلیل چند متغیره گسسته در مطالعات مقطعی و طولی. تهران: پژوهشکده آمار ایران.
معینی، علی، نفیسه بهرادمهر، مهدی اهراری، شریعت خادم (1391). استخراج شاخص‌های ارزش‌گذاری و امتیازدهی مشتریان در بازاریابی خدمات بانکی. فصلنامه کسب‌وکار، 16(64)، 1-25.
Afolabi, I., O. Olufunke, W. Rowland. 2016. A Systematic Review of Consumer Behaviour Prediction Studies. Covenant Journal of Business & Social Sciences (CJBSS) 7(1).
Ahmadi, K., H. Taherdoost, S. Fakhravar, N. Jalaliyoon. 2011. A New Model for Evaluating Customer Lifetime Value in High Risk Markets. International Conference on Social Science and Humanity, Singapore: IPEDR 5, IACSIT Press.
Baradaran V., M. Biglari, M. 2014). Customer segmentation in fast moving consumer    goods (FMCG) industries by using developed RFM model in Golestan province. Quarterly Journal of Business Management, 7(1), 23-42.
Berger, Paul. D. & Nada Nasr, 1998. Customer lifetime value: Marketing Models and Applications. Journal of Interactive Marketing, 12(1), 17- 30.
Bobadilla, J., F. Ortega, A. Hernando, A. Gutiérrez, A. 2013. Recommender systems survey. Knowledge-Based Systems, 109–132.
Carrasco, A., M. Blasco, E. Viedma. 2015. A 2-tuple Fuzzy Linguistic RFM Model and Its Implementation. Procedia Computer Science, 55, 1340-1347.
Cheng, C.J., S.W. Chiu, C.B. Cheng, J.Y. Wu. 2011. Customer lifetime value prediction by a Markov chain-based data mining model: Application to an auto repair and maintenance company in Taiwan. Scientia Iranica, 19(3), 849-855.
Ching-Hsue, You-Shyang Chen. 2009. Classifying the segmentation of customer value via RFM model and RS theory. Expert Systems with Applications, 36 (3), 4176–4184.
Chiang, Wen-Yu. 2011. To mine association rules of customer values via a data mining procedure with improved model: An empirical case study. Expert Systems with Applications, 38(3), 1716–1722.
Chen, Y. L., M.H. Kuo, S.Y. Wub, K. Tang. 2009. Discovering recency, frequency, and monetary (RFM) sequential patterns from customers’ purchasing data. Electronic Commerce Research and Applications, 8(5), 241–251.
Cormen, T.H., C.E. Leiserson, R.L. Rivest, C. Stein. 2001. Greedy Algorithms. In Introduction to Algorithms. Available in: http://labs.xjtudlc.com/labs/wldmt/ reading%20list/books/Algorithms%20and%20optimization/Introduction%20to%20Algorithms.pdf .
Dullaghan, Cormac, Eleni Rozaki. 2017. Integration of machine learning techniques to evaluate dynamic customer segmentation analysis for mobile customers. International Journal of Data Mining & Knowledge Management Process (IJDKP), 7(1).
Dursun, Aslihan, Meltem Caber. 2016. Using data mining techniques for profiling profitable hotel customers: An application of RFM analysis. Tourism Management Perspectives, 18, 153–160.
Everhartz, J., K. Maiwald, J. Wieseke. 2014. Identifying and analyzing the customer situation: Drivers for purchasing industrial product service systems. Procedia CIRP, 16, 308–313.
Fader, P.S., B.C.S. Hardie, K.L Lee. 2005. RFM and CLV: using iso-value curves for   customer base analysis. Journal of Marketing Research, 42(4), 415-430.
Gomez-Arias, Tomas, J., Juan P. Montermoso. 2007. Initial reference customer selection for high technology products. Management Decision, 45(6), 982–990.
Gupta, Sunil, Donald R. Lehmann. 2003. Customers as Assets. Journal of Interactive Marketing, 17(1), 9-24.
Hwang, H., T. Jung, E. Suh. 2004. An LTV Model and Customer Segmentation Based on Customer Value: A Case Study on the Wireless Telecommunications Industry. Expert systems with applications, (26), 181-188.
Han, S. L., D.T. Wilson, S.P. Dant. (1993). Buyer-supplier relationships today. Industrial Marketing Management, 22(4), 331–338.
 Liu, Duen-Ren, Ya-Yueh Shih. 2005. Integrating AHP and data mining for product recommendation based on customer lifetime value. Information & Management, 42(3), 387-400.
Song, M., Z. Xuejun, E. Haihong, O. Zhonghong. 2017. Statistics-based CRM approach via time series segmenting RFM on large scale data. Knowledge-Based Systems, 132, 21-29.
Minami, Chieko, John Dawson. 2008. The CRM process in retail and service sector firms in Japan: Loyalty development and financial return. Journal of Retailing and Consumer Services, 15(5), 375–385.
Segarra-Moliner, Jose Ramon, Miguel Ángel Moliner-Tena. 2015. Customer equity and CLV in Spanish telecommunication services. Journal of Business Research, 69 (10) 4694–4705.
Nesma, T., S. Shaimaa, E. Doaa. 2017.  New Insight into Customer Value Analysis using Data Mining Techniques. International Journal of Computer Applications, 176(3).
Nicolajsen, Hanne Westh, Ada Scupola. 2011. Investigating issues and challenges for customer involvement in business services innovation. The Journal of Business and Industrial Marketing, 26(5), 368–376.
Pulles, N.J., H. Schiele, J. Veldman. 2016. The impact of customer attractiveness and supplier satisfaction on becoming a preferred customer. Industrial Marketing Management, 54, 129–140.
Ait Daoud, R., A. Amine, B. Bouikhalene, R. Lbibb. 2015. Combining RFM model and clustering techniques for customer value analysis of a company selling online. 12th International Conference of Computer Systems and Applications (AICCSA), Marrakech, pp. 1-6.
Schweidel, D. A., E. Bradlow, P. Fader. 2008. Modeling the Evolution of Customers'' Service Portfolios. at SSRN: https://ssrn.com/abstract=985639.
Chuang, Huan-Ming, Chia-Cheng Shen. 2009. A study on the applications of data mining techniques to enhance customer lifetime value. WSEAS Transactions on Information Science and Applications, 6(2), 319-328.
Sohrabi, Babak, Amir Khanlari. 2007. Customer Lifetime Value (CLV)    Measurement Based on RFM Model. Iranian Accounting & Auditing Review, 14 (47), 7- 20.
Tuli, K. R., A.K. Kohli, S.G. Bharadwaj. 2007. Rethinking customer solutions: From product bundles to relational processes. Journal of Marketing, 71, 1–17.
Wang, Chih-Hsuan. 2010. Apply robust segmentation to the service industry using kernel induced fuzzy clustering techniques. Expert Systems with Applications: An International Journal, 37(12), 8395-8400.
Yeh, I.C., Y.K. Yang, T. Ming Ting. (2009). Knowledge discovery on RFM model using Bernoulli   sequence. Expert Systems with applications, 36(3), 5866-5871.
Iranian Journal of Information Management
Volume 4, Issue 1 - Serial Number 6
September 2018
Pages 69-90
  • Receive Date: 24 April 2018
  • Revise Date: 11 July 2018
  • Accept Date: 13 August 2018