Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study

Damla ASLAN, (Gazi University, Department of Management Information Systems, Ankara, Turkey)
Metehan TOLON (Ankara Hacı Bayram Veli University, Department of Business Administration, Ankara, Turkey)
İşletme Araştırmaları Dergisi
3 0
Yıl: 2018 Cilt: 10 Sayı: 4 Sayfa Aralığı: 887 - 900 Metin Dili: İngilizce DOI: 10.20491/isarder.2018.554 İndeks Tarihi: 11-09-2019

Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study

Öz:
Customer segmentation is an essential activity for marketing executives. To penetrate to target market, they should analyze their clients very well. Undoubtfully customer lifetime value (CLV) is a compact calculation method to understand customer behaviors and their values. Various models are presented for CLV interpretation in literature. Two of them are statistical hypothesis tests and k-means. This case study provides the comparison these methods for a B2B IT company. The methodology can easily be used for similar purposes in other organizations. The successful clusters are obtained by k-means application.
Anahtar Kelime:

Konular: İşletme İktisat
Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • Aksoy, L., Keiningham, T. L., Bejou, D., (2008). Objectives of Customer Centric Approaches in Relationship Marketing, Journal of Relationship Marketing, 6(3-4), 1-8.
  • Baş, M., Tolon, M., Aktepe, C., (2015). “Müşteri İlişkileri Yönetimi”, 3rd Edition, Detay Yayıncılık.
  • Benoit, D. F., Poel, D., (2009). Benefits of Quantile Regression for the Analysis of Customer Lifetime Value in a Contractual Setting: An Application in Financial Services, Expert Systems with Applications, 36, 10475-10484.
  • Berger, P. D., Nasr, N., (1998). Customer Lifetime Value: Marketing Models and Applications, Journal of Interactive Marketing, 12(1).
  • Berger, P. D., Nasr, N., (2001). The Allocation of Promotion Budget to Maximize Customer Equity, The International Journal of Management Science, Omega 29, 49-61.
  • Berger, P. D., Eechambadi, N., George, M., Lehmann, D. R., Rizley, R., Venkatesan, R., (2006). From Customer Lifetime Value to Shareholder Value, Journal of Service Research, 9(2), 156-167.
  • Blattberg, R. C., Malthouse, E. C., Neslin, S. A., (2009). Customer Lifetime Value: Empirical Generalizations and Some Conceptual Questions, Journal of Interactive Marketing, 23, 157-168.
  • Chan, S. L., Ip, W. H., Cho, V., (2010). A Model for Predicting Customer Value From Perspectives of Product Attractiveness and Marketing Strategy, Expert Systems with Applications, 37, 1207-1215.
  • Cheng, C. J., Chiu, S. W., Cheng, C. B., Wu, J. Y., (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 E, 19 (3), 849-855.
  • Chen, C., Chen, C., (2014). The Effect of Higher Education Brand Images on Satisfaction and Lifetime Value from Students’ Viewpoint, Anthropologist, 17(1), 137-145.
  • Clempner, J. B., Poznyak, A. S., (2014). Simple Computing of The Customer Lifetime Value: A Fixed Local-Optimal Policy Approach, J Syst Sci Syst Eng, , Systems Engineering Society of China and Springer, Verlag Berlin Heidelberg.
  • Cox, D. R., (1972). Regression Models and Life-Tables, Journal of the Royal Statistical Society. Series B (Methodological), 34(2), 187-220.
  • Çalhan, H., Çakıcı, A. C., Karamustafa, K., (2012). Müşteri Değeri, Müşteri Sermayesi ve Otel Performansı İlişkisi Üzerine Kavramsal Bir Değerlendirme, Sosyal Bilimler Enstitüsü Dergisi, 33(2), 87-120.
  • Dwyer, F. R., (1989). Customer Lifetime Valuation to Support Marketing Decision Making, Journal of Direct Marketing, 3(4), 8-15.
  • Glady, N., Baesens, B., Croux, C., (2009). A Modified Pareto/NBD Approach for Predicting Customer Lifetime Value, Expert Systems with Applications, 36, 2062-2071.
  • Glady, N., Baesens, B., Croux, C., (2009). Modeling Churn Using Customer Lifetime Value, Europian Journal of Operational Research, 197, 402-411.
  • Gloy, B. A., Akridge, J. T., Preckel, P. V., (1997). Customer Lifetime Value: An Application in the Rural Petroleum Market, Agribusiness, 13(3), 335-347.
  • Gupta, S., Hanssens, D., Hardie, B., Kahn, W., Kumar, V., Lin, N., Sriram, N. R. S., (2006). Modeling Customer Lifetime Value, Journal of Service Research, 9(2), 139-155.
  • Gupta, S., Lehmann, D. R., (2006). Customer Lifetime Value and Firm Valuation, Journal of Relationship Marketing, 5(2-3), 87-110.
  • Haenlein, M., Kaplan, A. M., Beeser, A. J., (2007). A Model to Determine Customer Lifetime Value in a Retail Banking Context, European Management Journal, 25(3), 221-234.
  • Hoekstra, J. C., Huizingh, E. K. R. E., (1999). The Lifetime Value Concept in Customer-Based Marketing, Journal of Market Focused Management, 3, 257-274.
  • 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, 181-188.
  • Kahreh, M. S., Tive, M., Babania, A., Hesan, M., (2014). Analyzing the Applications of Customer Lifetime Value (CLV) Based On Benefit Segmentation For the Banking Sector, Procedia-Social and Behavioral Sciences, 109, 590-594.
  • Keane, T. J., Wang, P., (1995). Applications for the Lifetime Value Model in Modern Newspaper Publishing, Journal of Direct Marketing, 9(2), Spring, John Wiley & Sons, Inc. and Direct Marketing Educational Foundation, Inc.
  • Khajvand, M., Zolfaghar, K., Ashoori, S., Alizadeh, S., (2011). Estimating Customer Lifetime Value Based on RFM Analysis of Customer Purchase Behavior: Case Study, Procedia Computer Science, 3, 57-63.
  • 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, 101-107.
  • Kotler, P., (2002). Marketing Management, Millenium Edition, Custom Edition for University of Phoenix, 10th Edition, Pearson Custom Publishing.
  • Kumar, V., (2010). A Customer Lifetime Value-Based Approach to Marketing in The Multichannel, Multimedia Retailing Environment, Journal of Interactive Marketing, 24, 71-85.
  • Liu, D., Shih, Y., (2005). Hybrid Approaches to Product Recommendation Based on Customer Lifetime Value and Purchase Preferences, The Journal of Systems and Software, 77, 181-191.
  • Liu, D., Shih, Y., (2005). Integrating AHP and Data Mining for Product Recommendation Based On Customer Lifetime Value, Information & Management, 42, 387-400.
  • Mani, D. R., Drew, J., Betz, A., Datta, P., (1999). Statistics and Data Mining Techniques for Lifetime Value Modeling, KDD-99, San Diego, CA, USA, ACM, 1-58113-143-7/99/08.
  • Nenonen, S., Storbacka, K., (2016). Driving Shareholder Value with Customer Asset Management: Moving Beyond Customer Lifetime Value, Industrial Marketing Management, 52, 140-150.
  • Paauwe, P., Putten, P., Wezel, M., (2007). DTMC: An Actionable e-Customer Lifetime Value Model Based on Markov Chains and Decision Trees, ICEC’07, August 19-22, Minneapolis, Minnesota, USA.
  • Rosset, S., Neumann, E., Eick, U., Vatnik, N., (2003). Customer Lifetime Value Models for Decision Support, Data Mining and Knowledge Discovery, 7, 321-339.
  • Shih, Y., Liu, D., (2008). Product Recommendation Approaches: Collaborative Filtering via Customer Lifetime Value and Customer Demands, Expert Systems with Applications, 35, 350-360.
  • Venkatesan, R., Kumar, V., (2004). A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy, Journal of Marketing, 68(4), 106-125.
  • Yapraklı, Ş., Keser, E., (2008). Serbest Muhasebecilik ve Serbest Muhasebeci Mali Müşavirlik Sektöründe Yaşam Boyu Değerinin Hesaplanması Üzerine Bir Saha Araştırması, Ankara Üniversitesi SBF Dergisi, 64-2, 185-212.
  • Yılmaz, S., Büyüklü, A. H., (2009). Yaşam Boyu Müşteri Değeri Modellemesi Üzerine Bir Örnek Uygulama, FBE İstatistik Anabilim Dalı İstatistik Programı, Master Thesis, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.
  • Zhang, H., Liang, X., Wang, S., (2016). Customer Value Anticipation, Product Innovativeness, and Customer Lifetime Value: The Moderating Role of Advertising Strategy, Journal of Business Research, 69, 3725-3730.
APA ASLAN D, Tolon M (2018). Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. , 887 - 900. 10.20491/isarder.2018.554
Chicago ASLAN DAMLA,Tolon Metehan Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. (2018): 887 - 900. 10.20491/isarder.2018.554
MLA ASLAN DAMLA,Tolon Metehan Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. , 2018, ss.887 - 900. 10.20491/isarder.2018.554
AMA ASLAN D,Tolon M Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. . 2018; 887 - 900. 10.20491/isarder.2018.554
Vancouver ASLAN D,Tolon M Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. . 2018; 887 - 900. 10.20491/isarder.2018.554
IEEE ASLAN D,Tolon M "Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study." , ss.887 - 900, 2018. 10.20491/isarder.2018.554
ISNAD ASLAN, DAMLA - Tolon, Metehan. "Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study". (2018), 887-900. https://doi.org/10.20491/isarder.2018.554
APA ASLAN D, Tolon M (2018). Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. İşletme Araştırmaları Dergisi, 10(4), 887 - 900. 10.20491/isarder.2018.554
Chicago ASLAN DAMLA,Tolon Metehan Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. İşletme Araştırmaları Dergisi 10, no.4 (2018): 887 - 900. 10.20491/isarder.2018.554
MLA ASLAN DAMLA,Tolon Metehan Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. İşletme Araştırmaları Dergisi, vol.10, no.4, 2018, ss.887 - 900. 10.20491/isarder.2018.554
AMA ASLAN D,Tolon M Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. İşletme Araştırmaları Dergisi. 2018; 10(4): 887 - 900. 10.20491/isarder.2018.554
Vancouver ASLAN D,Tolon M Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. İşletme Araştırmaları Dergisi. 2018; 10(4): 887 - 900. 10.20491/isarder.2018.554
IEEE ASLAN D,Tolon M "Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study." İşletme Araştırmaları Dergisi, 10, ss.887 - 900, 2018. 10.20491/isarder.2018.554
ISNAD ASLAN, DAMLA - Tolon, Metehan. "Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study". İşletme Araştırmaları Dergisi 10/4 (2018), 887-900. https://doi.org/10.20491/isarder.2018.554
Sayfa Oluşturulma Tarihi
23-04-2024 8:41

İLETİŞİM

TÜBİTAK ULAKBİM TR Dizin

Yüzüncüyıl, İşçi Blokları Mahallesi

Muhsin Yazıcıoğlu Caddesi No:51/C

06530 Çankaya / ANKARA +90 (312) 298 92 00

trdizin@tubitak.gov.tr

TÜBİTAK ULAKBİM Ulusal Akademik Ağ ve Bilgi Merkezi Cahit Arf Bilgi Merkezi © Tüm Hakları Saklıdır. Gizlilik Politikası Kullanım Şartları