Name
Title | ||
|---|---|---|
Divide and Prosper: Comparing Models of Customer Behavior From Populations to Individuals |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICDM.2004.10013 | ICDM |
Keywords | Field | DocType |
low-volume customer,aggregate approach,experimental setting,customer segmentation,aggregate marketing approach,best segmentation technique,customer behavior,segmentation technique,multiple segmentation level,marketing datasets,consumer behaviour,comparative modeling | Data mining,Market segmentation,Consumer behaviour,Computer science,Pattern clustering,Segmentation,Variables,Artificial intelligence,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2142-8 | 1 | 0.39 |
References | Authors | |
11 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianyi Jiang | 1 | 79 | 6.50 |
| Alexander Tuzhilin | 2 | 6901 | 489.00 |