OKCashbag (OCB), the largest coalition loyalty program in Korea, offers a number of benefits such as sharing customer data with participating firms and cross-selling. There is great value in utilizing information pertaining to coalition loyal patrons. However, the size of transaction data is huge. We propose how to create necessary summary information by reducing the dimension of coalition transaction data. This information is then utilized to develop a behavior-scoring model. We expect that our study results can contribute to big data analysis for coalition loyalty program.
Bibliographical noteFunding Information:
This work was financially supported by the Ministry of Knowledge Economy (MKE) and Korea Institute for Advancement in Technology (KIAT) through the Workforce Development Program in Strategic Technology.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence