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Published Articles >> Table of Contents >> Abstract
Fourth IEEE International Conference on Data Mining (ICDM'04)
pp. 419-422
Divide and Prosper: Comparing Models of Customer Behavior From Populations to Individuals
Tianyi Jiang, New York University
Alexander Tuzhilin, New York University
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2004.10013
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| Abstract |
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This paper compares customer segmentation, 1-to-1, and aggregate marketing approaches across a broad range of experimental settings, including multiple segmentation levels, marketing datasets, dependent variables, and different types of classifiers, segmentation techniques, and predictive measures. Our experimental results show that, overall, 1-to-1 modeling significantly outperforms the aggregate approach among high-volume customers and is never worse than aggregate approach among low-volume customers. Moreover, the best segmentation techniques tend to outperform 1-to-1 modeling among low-volume customers.
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Citation:
Tianyi Jiang, Alexander Tuzhilin,
"Divide and Prosper: Comparing Models of Customer Behavior From Populations to Individuals,"
icdm,
pp. 419-422,
Fourth IEEE International Conference on Data Mining (ICDM'04),
2004
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