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Trans. Planning Journal
| Title | Mining TRA’s Transaction Data for Loyalty Program Rules |
|---|---|
| Author | Jian-Fu Wang and Min-Yu Chen |
| Summary | Point-based customer loyalty program has been extensively adopted in many industries to maintain customer relationships, even to stimulate repeat purchases from customers and to obtain more profits for companies. Due to the need to continuously invest resources in loyalty programs, companies should only allow profitable customers to join the programs. This study evaluates the ticket reservation data of Taiwan Railways Administration with RFM and extended variables using clustering and decision tree techniques and loyalty matrix concepts to identify customer values. Through this research, we are able to provide 94% classification accuracy on our decision tree model employing three-month ticket reservation data. Also, high-value and potential high-value customers are identified via the classification rules for member-recruiting. In the end, lowering the thresholds of redeeming points, offering diversified rewards and using tier membership structure are suggested to enhance the functions of the loyalty program. |
| Vol. | 42 |
| No. | 3 |
| Page | 221 |
| Year | 2013 |
| Month | 9 |
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