Identifying & Segmenting Key Customers for Prioritizing them Based on Lifetime Value using RFM Model (Case study: Internet customer of Qom Telecommunications Company)

Document Type : Research Paper

Authors

1 Faculty Member of Semnan University

2 Faculty of Economics, Management & Administrative Sciences, Department of Management

3 Master of Management Sciences, Semnan University

Abstract

By the emerge of competitive markets and continuous changes, organizations have found that they are not faced with growing economy and markets, so each customer has its own special value. Therefore, they are trying to maintain and increase customer loyalty to increase their competitive advantages. In this regard, the present study aims to identify and prioritize key customers from about 37,187 customers in Internet segment in Telecom Qom province. The process is performed after determining RFM (Regency, Frequency, and Monitory) and the weight of each of these parameters was defined based on analytic hierarchy process and clients were based on a two-step clustering. The results of the analysis of characteristics of customers in 4 major portion of the clusters shows that cluster number 2 with the least number of customers and the most life time value has been known as key customers, and then its prioritization has been conducted. In the end of the research, some suggestions were presented to improve the relationship between customers and the companies.

Keywords

Main Subjects


Abbasi, R. & Turkamani, M. (2010). The theoretical model to implement customer relationship management (CRM). Business Studies, 8(41):19-34. (in Persian)
Abdolvand, N. & Al-Badawi, A. (2012). Providing a holistic model based on customer lifetime value to manage performance in geographically distributed service industries. Journal of Business Researches, (64): 43 -90. (in Persian)
Afsar, A., Hoshdar Mahjoub, R. & Minaie, B. (2013). Credit clustering of customers to provide appropriate facilities. Management researches in Iran. 17(4): 1- 24. (in Persian)
Albadvi, A., Norozo, A., Sepehri. M. M., Amin Naseri, M.R. (2014). Combination of Pareto/NBD & fuzzy weighted RFM for Customer segmentation in unconventional relationships. Journal of Business Management, 6(3): 417-440.(in Persian)
Baradaran, V. & Biglari, M. (2015). Customer segmentation of manufacturing and distribution industry of flowing goods based on Improved model RFM (Case Study: Golestan Company). Journal of Business Management, 7(1): 23-42.(in Persian)
Ehsan, N., Khan, A., Mirza, E. & Sarwar, S. Z. (2012). Integration between Customer Relationship Management (CRM) and Data Warehousing. Procedia Technology, 1: 239- 249.
Haghighi Kaffash, M., Akbari, M. & Lilian Poor, N. (2010). Effective ingredient on loyalty of insured, Case Study: Iran Insurance. The insurance industry journal, 25 (1): 75-95. (in Persian)
Hoseini, S. Y., Bahraini Zadeh, M. & Ziaee Bide, A. R. (2012). Analysis of performance importance of service features based on customer segmentation using Data Mining method (Research in the mobile services market in Yazd province). Information Technology Management, 4 (13): 45- 70. (in Persian)
Hoseinzadeh, S. M., Karami, M. & Mehrabani, M. (2015). Segmentation of customers in the supply chain restaurants on style food (Case study: fast food chain restaurants in Tehran. Journal of Business Management, 7(1): 83-99.(in Persian)
Hu, Y. H. & Yeh, T. W. (2014). Discovering valuable frequent patterns based on RFM analysis without customer identification information. Knowledge-Based Systems, 61: 76-88.
Kaffashpoor, A. & Alizadeh Zvarm, A. (2012). The use of AHP Fuzzy Delphi Analytic Hierarchy Process (FDAHP) and hierarchical cluster analysis (HCA) in RFM model to determine customer lifetime value. Journal of Scientific- Research of modern marketing, 2 (3): 51-68. (in Persian)
Kaffashpoor, A., Tavakoli, A. & Alizadeh Zvarm, A. (2012). Segmentation of customer based on their lifetime value using data mining based on RFM model. Public management researches, 5(15): 63-84. (in Persian)
Khajevand, S., Taghavi Fard, M. T. & Najafi, I. (2012). Segmentation of customers of Iran Saderat bank using data mining. Journal of Scientific- Research
of Management Studies (improvement and evolution)
, 22(67): 179 -200.
(in Persian)
Lopez, J. J., Aguado, J. A., Martin, F. M., Rodrigues, A. & Ruiz, J. E. (2011). Hopfield–K-Means clustering algorithm: A proposal for the segmentation of electricity customers. Electric Power Systems Research, 81(2): 716–724.
Mehrabi, J., Babai Ahari, M. & Taati, M. (2010). Providing a implementation integrated model of customer relationship management (CRM) in the bank. Developed and evolution management, 2(4): 61- 71. (in Persian)
Mohammadi, E. & Sheikh, R. (2015). Customer classification and prioritization of them at the center of decision Rough set theory and the theory of numbers D approach (case study: Sony Ericsson mobile phone). Journal of Business Management, 7(1): 163-185. (in Persian)
Mohammadi, R., Bidabad, B., Nourasteh, T. & Sherafati, M. (2014). Credit Ranking of Bank Customers (An Integrated Model of RFM, FAHP and K-means). European Online Journal of Natural and Social Sciences, 3(3): 564- 571.
Mosanneni, M. (2009). Customers segmentation using customer lifetime value. Tarbiat Modarres University, Tehran. (in Persian(
Noorbakhsh, S. K. & Pashang, L. (2012). The checking of effective factors on relationship marketing in full relations between buyer- seller (case study: Bahman dizel company). Journal of marketing management, 6 (13): 95- 114. (in Persian)
Razmi, J. & Ghanbari, A. (2009). A new model for calculating customer lifetime value. Journal of Information and Technology, 1(2): 35-50. (in Persian)
Rožek, J. & Karlíček, M. (2014). Customer lifetime value as the 21st century marketing strategy approach. Central European business review, 3(2): 28-35.
Sohrabi, B. & Khanlari, A. (2008). Causal model of improvement and ascendency in relevance to organization customer. Journal of Management Science, 3(11): 131- 148. (in Persian)
Sohrabi, B., Khanlari, A. & Ajorloo, N. (2011). a model for determining the value of customer life cycle (CLV) in the banking industry. Management Researches in iran, 15(1): 223-239. (in Persian)
Tsai, H. P. & Chang, H. C. (2011). Group RFM analysis as a novel framework to discover better customer consumption behavior. Expert Systems with Applications, 38(12):14499-14513.
Tsoukatos, E. & Rand, G. K. (2006). Path analysis of perceived service quality, satisfaction and loyalty in Greek insurance. Managing Service Quality, 16(5): 501-519.
Vegholm, F.(2011). Relationship marketing and the management of corporate image in the bank-SME relationship. Management Research Review, (34): 325-336.
Wu, H.H., Chang, E.C. & Lo, C.F. (2009). Applying RFM model and K-means method in customer value analysis of an outfitter. International Conference on Concurrent Engineering, New York. DOI: 10.1007/978-1-84882-762-2_63.
Zalaghi, Z. & Abbasnejad,V. Y. (2014). Measuring customer loyalty using an extended RFM and clustering technique. Management Science Letters, 4(5): 905- 912.
Zivyar, F. Ziaee, M. S. & Nargesian, J. (2012). Examine the effective factors on customer satisfaction using SERVQUAL model, Journal of Scientific- Research of modern marketing, 2 (3): 186 -173. (in Persian)