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Journals / İşletme Araştırmaları Dergisi / 2018 / Cilt: 10 - Sayı: 4

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

Damla ASLAN
METEHAN TOLON
Pages
887–900
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The successful clusters are obtained by k-means application.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Customer segmentation is an essential activity for marketing executives.
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Key Findings & Data:To penetrate to target market, they should analyze their clients very well.
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Conclusion & Impact:The successful clusters are obtained by k-means application.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

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.

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Cite This Article

ASLAN, D., TOLON, M. (2018). Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. İşletme Araştırmaları Dergisi, Cilt: 10 - Sayı: 4, 887–900. https://ajindex.com/articles/269470

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References (15)

  1. 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.
  2. Baş, M., Tolon, M., Aktepe, C., (2015). “Müşteri İlişkileri Yönetimi”, 3rd Edition,
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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).
  11. Regression Models and Life-Tables, Journal of the Royal Statistical Society. Series B (Methodological), 34(2), 187-220.
  12. Çalhan, H., Çakıcı, A. C., Karamustafa, K., (2012).
  13. Müşteri Değeri, Müşteri Sermayesi ve Otel Performansı İlişkisi Üzerine Kavramsal Bir Değerlendirme, Sosyal Bilimler Enstitüsü Dergisi, 33(2), 87-120.
  14. Dwyer, F. R., (1989). Customer Lifetime Valuation to Support Marketing Decision Making, Journal of Direct Marketing, 3(4), 8-15.
  15. Glady, N., Baesens, B., Croux, C