TY - JOUR
T1 - Optimal threshold analysis of segmentation methods for identifying target customers
AU - Mizuno, Makoto
AU - Saji, Akira
AU - Sumita, Ushio
AU - Suzuki, Hideo
N1 - Funding Information:
The authors wish to thank two anonymous referees for their many helpful comments which contributed to improve the original version of the paper substantially. The support by MEXT Grant-in-Aid for Fundamental Research (C) 17510114 is gratefully acknowledged.
PY - 2008/4/1
Y1 - 2008/4/1
N2 - In CRM (Customer Relationship Management), the importance of a segmentation method for identifying good customers has been increasing. For evaluation of different segmentation methods, Accuracy often plays a key role. This indicator, however, cannot distinguish two types of errors. The purpose of this paper is to overcome this pitfall by introducing two different indicators: Recall and Precision. Assuming that a promotion is addressed exclusively to the selected target customers, the financial effectiveness of the underlying segmentation method is expressed as a function of Recall and Precision. An optimization problem is then formulated so as to maximize the financial measure by finding the optimal threshold level in terms of the severeness for estimating the target set. By introducing a functional form which represents correctness and mistakes about the target set, the unique optimal solution is derived explicitly. The proposed approach is validated by using real customer purchase data.
AB - In CRM (Customer Relationship Management), the importance of a segmentation method for identifying good customers has been increasing. For evaluation of different segmentation methods, Accuracy often plays a key role. This indicator, however, cannot distinguish two types of errors. The purpose of this paper is to overcome this pitfall by introducing two different indicators: Recall and Precision. Assuming that a promotion is addressed exclusively to the selected target customers, the financial effectiveness of the underlying segmentation method is expressed as a function of Recall and Precision. An optimization problem is then formulated so as to maximize the financial measure by finding the optimal threshold level in terms of the severeness for estimating the target set. By introducing a functional form which represents correctness and mistakes about the target set, the unique optimal solution is derived explicitly. The proposed approach is validated by using real customer purchase data.
KW - Cost benefit analysis
KW - Identifying target customers
KW - Marketing
KW - Optimal threshold level
KW - Segmentation method
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U2 - 10.1016/j.ejor.2007.01.038
DO - 10.1016/j.ejor.2007.01.038
M3 - Article
AN - SCOPUS:35348951434
SN - 0377-2217
VL - 186
SP - 358
EP - 379
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 1
ER -