Customer Classification Method for Household Appliances Industries with a Large Number of Incomplete Data

다수의 결측치가 존재하는 가전업 고객 데이터 활용을 위한 고객분류기법의 개발

  • Received : 20051000
  • Accepted : 20060200
  • Published : 2006.03.31

Abstract

Some customer data of manufacturing industries have a large number of incomplete data set due to the customer's infrequent purchasing behavior and the limitation of customer profile data gathered from sales representatives. So that, most sophisticated data analysis methods may not be applied directly. This paper proposes a heuristic data analysis method to classify customers in household appliances industries. The proposed PD (percent of difference) method can be used for the discriminant analysis of incomplete customer data with simple mathematical calculations. The method is composed of variable distribution estimation step, PD measure and cluster score evaluation steps, variable impact construction step, and segment assignment step. A real example is also presented.

Keywords

References

  1. Addison, W.(1996), Data Mining, Syllogic, USA
  2. Afifi, A. and Elashoff, R.(1966), Missing Observations in Multivariate Statistics I: Review of the Literature, Journal of American Statistical Association, 61, 595-604 https://doi.org/10.2307/2282773
  3. Athanassopoulos, A. D.(2000), Customer Satisfaction Cues to Support Market Segmentation and Explain Switching Behavior, Journal of Business Research, 47(3), 191-207 https://doi.org/10.1016/S0148-2963(98)00060-5
  4. Bart, B., Verstraeten, G., Poel, D.V.D., Egmont-Petersen, M., Kenhove, P.V. and Vanthienen, J.(2004), Bayesian Network Classifiers for Idenfying the Slope of the Customer Lifecycle of Long-lift Customers, European Journal of Operational Research, 156(2), 508-523 https://doi.org/10.1016/S0377-2217(03)00043-2
  5. Berry, M. J. A. and Linoff, G.(1997), Data Mining Techniques, John Wiley & Sons, NY, USA
  6. Dillon, W. R. and Goldstein, M.(1984), Multivariate Analysis, John Wiley & Sons, NY, USA
  7. Frederick, N.(2000), Loyalty.com, McGraw-Hill, USA
  8. Granger, E., Rubin, M. A., Grossberg, S. and Lavoie, P.(2001). Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network, Proc. IEEE International Joint Conference of Neural Networks, 6, 35-40
  9. Huang, X. and Zhu, Q.(2002), A Pseudo-nearest-neighbor Approach for Missing Data Recovery on Gaussian Random Data Sets, Pattern Recognition Letters, 23, 1613-1622 https://doi.org/10.1016/S0167-8655(02)00125-3
  10. Krishnamoorthy, K. and Maruthy, K.(1998), Some Simple Test Procedures for Normal Mean Vector with Incomplete Data, Annals of the Institute of Statistical Mathematics, 50(3), 531-542 https://doi.org/10.1023/A:1003581513299
  11. Lim, C. P., Leong, J. H. and Kuan, M. M.(2005), A Hybrid Neural Network System for Pattern Classification Tasks with Missing Features, IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(4), 648-653 https://doi.org/10.1109/TPAMI.2005.64
  12. Mozer, M. C., Wolniewicz, R., Grimes, D. B., Johnson, E. and Kaushansky. H.(2000), Predicting Subscriber Dissatisfaction and Improving Retention in the Wireless Telecommunications Industry, IEEE Transactions on Neural Networks, 11(3), 690-696 https://doi.org/10.1109/72.846740
  13. Nijman, M. J. and Kappen, H. J.(1997), Symmetry Breaking and Training from Incomplete Data with Radial Basis Boltzmann Machines, International Journal of Neural Systems, 8, 301-306 https://doi.org/10.1142/S0129065797000318
  14. Punj, G. and Stewart, D. W.(1983), Cluster analysis in Marketing Research Review and Suggestions for Application, Journal of Marketing Research, 20(2), 134-148 https://doi.org/10.2307/3151680
  15. Schafer, J. L.(1997), Analysis of Incomplete Multivariate Data, Chapman & Hall, London, UK
  16. Van den Poel, D. and Lariviere, B.(2004), Customer Attrition Analysis for Financial Services Using Proportional Hazard Models, European Journal of Operational Research, 157(1), 196-217 https://doi.org/10.1016/S0377-2217(03)00069-9
  17. Weerahandi, S. and Morita, S.(1995), Using Survey Data to Predict Adoption Switching for Services, Journal of Marketing Research, 32(1), 85-96 https://doi.org/10.2307/3152113
  18. Zeithaml, V. A., Berry, L. L. and Parasuraman, A.(1996), The Behaviora Consequences of Service Quality, Journal of Marketing, 60(2), 2105-2111