A CLV-Based Framework to Prioritize Promotion Marketing Strategies: A Case Study of Telecom Industry

Document Type: Research Paper

Authors

1 Department of Industrial Management, Faculty of Economics and Management, University of Mazandaran, Mazandaran, Iran

2 Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran

3 Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran

4 Department of Industrial Engineering, University of Science and Culture, Tehran, Iran

Abstract

Telecommunications is the todays’ leading industry. Value Added Services (VAS) is considered as one of the most money making segments of Telecom services. The purpose of this paper is to allocate promotional marketing strategies to customer segments. Therefore, a four-phase practical framework is developed to prioritize marketing strategies based on Customer Lifetime Value (CLV). The first phase focuses on information gathering. Consequently, the CLV of each customer is calculated. Then, the customers are clustered into separated segments based on their CLV scores, using Fuzzy C-Mean. Finally, the appropriate marketing strategy is prioritized for each segment, using Fuzzy TOPSIS technique.

Keywords

Main Subjects


Article Title [Persian]

ارائه یک چارچوب مفهومی جهت اولویت‌بندی استراتژی‌های بازاریابی برمبنای ارزش دوره عمر مشتری - مطالعه موردی صنعت ارتباطات سیار

Authors [Persian]

  • یاسر نعمتی 1
  • علی محقر 2
  • محمد حسین علوی دوست 3
  • حسین بابازاده 4
1 گروه مدیریت صنعتی، دانشکده مدیریت و علوم اقتصاد، دانشگاه مازندران، مازندران، ایران
2 گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران
3 دپارتمان مهندسی صنایع، دانشگاه صنعتی امیرکبیر، تهران، ایران
4 دپارتمان مهندسی صنایع، دانشگاه علم و فرهنگ، تهران، ایران
Abstract [Persian]

صنعت ارتباطات سیار یکی از پیشروترین صنایع دنیاست. در سالهای اخیر، سرویس های ارزش افزوده  با هدف ایجاد تنوع در ارائه خدمات مورد توجه قرار گرفته است. به جهت نوظهور بودن ارائه این سرویس در ایران، بهره‌گیری از مفاهیمی چون مدیریت ارتباط با مشتریان نه بعنوان یک مزیتی رقابتی بلکه بعنوان یک الزام رقابتی بیش از پیش مورد نیاز می­باشد. لازمه این أمر، استفاده از یک شاخص برتر به نام ارزش دوره عمر مشتری است که امروزه به عنوان یک شاخص بازاریابی معتبر در سطح جهان مورد استفاده قرار می­گیرد. ما در این تحقیق، یک چارچوب کاربردی شامل چهار فاز را برای پیاده سازی استراتژی های بازاریابی بر مبنای ارزش دوره عمر مشتری، پیشنهاد کردیم. در فاز اول، اطلاعات مشتریان را بر اساس تعریف ارزش دوره عمر مشتری استخراج نمودیم. در گام دوم، شاخص ارزش دوره عمر را بر اساس سه رویکرد ارزش جاری، ارزش قراردادی و وفاداری مشتری برای تمامی مشتریان محاسبه کردیم. در فاز سوم، مشتریان را بر مبنای ارزش دوره عمرشان با استفاده از تکنیک میانگین C فازی خوشه بندی نمودیم. و در نهایت در فاز چهار، استراتژی بازاریابی متناسب با هر خوشه از مشتریان را با استفاده از روش تاپسیس فازی اولویت بندی نمودیم.

Keywords [Persian]

  • مدیریت ارتباط با مشتریان
  • ارزش دوره عمر مشتری
  • خوشه بندی مشتریان
  • میانگین c فازی
  • تاپسیس فازی
Abdolvand, N., Albadvi, A., & Koosha, H. (2014). Customer lifetime value: Literature scoping map, and an agenda for future research. International Journal of Management Perspective, 1(3).

Alavidoost, M., Zarandi, M. F., Tarimoradi, M., & Nemati, Y. (2014). Modified genetic algorithm for simple straight and U-shaped assembly line balancing with fuzzy processing times. Journal of Intelligent Manufacturing, 1-24.

Amin, A., Anwar, S., Adnan, A., Nawaz, M., Alawfi, K., Hussain, A., & Huang, K. (2017). Customer churn prediction in the telecommunication sector using a rough set approach. Neurocomputing, 237(Supplement C), 242-254. doi: https://doi.org/10.1016/j.neucom.2016.12.009

Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), B-141-B-164.

Berger, P. D., & Nasr, N. I. (1998). Customer lifetime value: Marketing models and applications. Journal of interactive marketing, 12(1), 17-30.

Castéran, H., Meyer-Waarden, L., & Reinartz, W. (2017). Modeling customer lifetime value, retention, and churn. Handbook of Market Research, 1-33.

Chen, C.-H., Khoo, L. P., & Yan, W. (2002). A strategy for acquiring customer requirement patterns using laddering technique and ART2 neural network. Advanced Engineering Informatics, 16(3), 229-240.

Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1-9.

Chen, S. J., & Hwang, C. L. (1992). Fuzzy multiple attribute decision making methods: Fuzzy multiple attribute decision making.  Springer, 289-486.

Chen, Y., & Hu, H. (2010). How determinant attributes of service quality influence customer-perceived value: an empirical investigation of the Australian coffee outlet industry. International Journal of Contemporary Hospitality Management, 22(4), 535-551.

Chu, T.-C., & Lin, Y.-C. (2003). A fuzzy TOPSIS method for robot selection. The International Journal of Advanced Manufacturing Technology, 21(4), 284-290.

Chu, T. (2002). Facility location selection using fuzzy TOPSIS under group decisions. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(06), 687-701.

Chu, T., & Lin, Y. (2003). A fuzzy TOPSIS method for robot selection. The International Journal of Advanced Manufacturing Technology, 21(4), 284-290.

Coussement, K., Lessmann, S., & Verstraeten, G. (2017). A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry. Decision Support Systems, 95(Supplement C), 27-36. doi: https://doi.org/10.1016/j.dss.2016.11.007

Ekinci, Y., Ülengin, F., Uray, N., & Ülengin, B. (2014). Analysis of customer lifetime value and marketing expenditure decisions through a Markovian-based model. European Journal of Operational Research, 237(1), 278-288.

Farris, P. W., Bendle, N., Pfeifer, P., & Reibstein, D. (2010). Marketing metrics: The definitive guide to measuring marketing performance. Upper Saddle River, USA: Pearson Education.

Gruen, T. W., & Shah, R. H. (2000). Determinants and outcomes of plan objectivity and implementation in category management relationships. Journal of Retailing, 76(4), 483-510.

Gupta, S. (2009). Customer-based valuation. Journal of Interactive Marketing, 23(2), 169-178.

Gupta, S., Hanssens, D., Hardie, B., Kahn, W., Kumar, V., Lin, N., . . . Sriram, S. (2006). Modeling customer lifetime value. Journal of Service Research, 9(2), 139-155.

Gupta, S., & Lehmann, D. R. (2003). Customers as assets. Journal of Interactive Marketing, 17(1), 9-24.

Hruschka, H. (1986). Market definition and segmentation using fuzzy clustering methods. International Journal of Research in Marketing, 3(2), 117-134.

Hwang, H., Jung, T., & Suh, E. (2004). An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry. Expert Systems with Applications, 26(2), 181-188.

Kaushik, M. (2013). Platforms used in mobile value added services. International Journal of Engineering Innovations and Research, 2(3), 229.

Kim, H.-S., & Kwon, N. (2003). The advantage of network size in acquiring new subscribers: a conditional logit analysis of the Korean mobile telephony market. Information Economics and Policy, 15(1), 17-33.

Kim, S., Jung, T., Suh, E., & Hwang, H. (2006). Customer segmentation and strategy development based on customer lifetime value: A case study. Expert Systems with Applications, 31(1), 101-107.

Kotler, P. (1996). Principles of Marketing (7Th ed.).Englewood Cliffs, New-Jersey: Prenlice-Hall, 323.

Kotler, P. (2000). Marketing management millenium edition. Marketing Management, 23(6), 188-193.

Kumar, V., & Shah, D. (2015). Handbook of research on customer equity in marketing. Edward Elgar Publishing.

Libai, B., Narayandas, D., & Humby, C. (2002). Toward an individual customer profitability model: A segment-based approach. Journal of service Research, 5(1), 69-76.

Liu, R., Zhang, J., & Liu, R. (2008). Fuzzy c-means clustering algorithm. Journal of Chongqing Institute of Technology (Natural Science Edition), 2, 036.

Liu, Y., Li, G., Gao, K., Du, Y., Zhang, Q., Niu, X., & Sun, W. (2003). Fundamental frame to draft guid for condition maintenance of electric power equipment. Power System Technology, 6, 160 - 168.

Macrae, C., & Uncles, M. D. (1997). Rethinking brand management: the role of “brand chartering. Journal of Product & Brand Management, 6(1), 64-77.

Nemati, Y., & Alavidoost, M. H. (2018). A fuzzy bi-objective MILP approach to integrate sales, production, distribution and procurement planning in a FMCG supply chain. Soft Computing. doi: 10.1007/s00500-018-3146-5

Nemati, Y., Khalafi, A. H., & Sarabi, N. (2012). Integrated analytical approach to select the most appropriate Six Sigma project in mobile communication companies, using ANP and FCM. Proceedings from the European Business Research Conference, Rome.

Nemati, Y., Madhoshi, M., & Ghadikolaei, A. S. (2017). The effect of Sales and Operations Planning (S&OP) on supply chain’s total performance: A case study in an Iranian dairy company. Computers & Chemical Engineering, 104, 323-338.

Nemati, Y., Madhoushi, M., & Safaei Ghadikolaei, A. (2017). Towards supply chain planning integration: Uncertainty analysis using fuzzy mathematical programming approach in a plastic forming company. Iranian Journal of Management Studies, 10(2), 335-364.

Pearce, J. M., & Hanlon, J. T. (2007). Energy conservation from systematic tire pressure regulation. Energy Policy, 35(4), 2673-2677.

Rahimi, R., & Kozak, M. (2017). Impact of customer relationship management on customer satisfaction: The case of a budget hotel chain. Journal of Travel & Tourism Marketing, 34(1), 40-51.

Razmi, J., & Ghanbari, A. (2009). Introducing a novel model to determine CLV. Journal of Information Technology Management, 1( 2), 35-50.

Reinartz, W., Thomas, J. S., & Kumar, V. (2005). Balancing acquisition and retention resources to maximize customer profitability. Journal of Marketing, 69(1), 63-79.

Rostami, A., Noroozi, A., Mokhtari, H., & Nemati, Y. (2016). modeling and Solution of a Multi-Objective Portfolio Selection by using a Simulated Annealing. Journal of Modeling in Engineering, 14(45), 99-109.

Segarra Moliner, J. R., & Moliner Tena, M. Á. (2016). Customer equity and CLV in Spanish telecommunication services. Journal of Business Research, 69(10), 4694-4705.

Sublaban, C. S. Y., & Aranha, F. (2009). Estimating cellphone providers' customer equity. Journal of Business Research, 62(9), 891-898.

Tsaur, S.-H., Chang, T.-Y., & Yen, C.-H. (2002). The evaluation of airline service quality by fuzzy MCDM. Tourism Management, 23(2), 107-115.

Verhoef, P. C., & Donkers, B. (2001). Predicting customer potential value an application in the insurance industry. Decision Support Systems, 32(2), 189-199.

Wang, W., & Zhang, Y. (2007). On fuzzy cluster validity indices. Fuzzy Sets and Systems, 158(19), 2095-2117.

Wang, Y., & Feng, H. (2012). Customer relationship management capabilities: Measurement, antecedents and consequences. Management Decision, 50(1), 115-129.

Wilson, J. A., & Hollensen, S. (2013). Assessing the implications on performance when aligning customer lifetime value calculations with religious faith groups and after lifetime values–a Socratic elenchus approach. International Journal of Business Performance Management, 14(1), 67-94.