Abstract
Using the customer relationship management perspective to investigate customer behavior, this study differentiates between customers through customer segmentation, tracks customer shifts from segment to segment over time, discovers customer segment knowledge to build an individual transition path and a dominant transition path, and then predicts customer segment behavior patterns. By using real-world data, this study evaluates the accuracy of predictive models. The concluding remarks discuss future research in this area.
| Original language | English |
|---|---|
| Pages (from-to) | 293-301 |
| Number of pages | 9 |
| Journal | Advanced Engineering Informatics |
| Volume | 21 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jul 2007 |
Keywords
- Customer analysis
- Customer relationship management
- Data mining
- Knowledge engineering
- Segmentation
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