Applying data mining with a new model on customer relationship management systems: a case of airline industry in Taiwan

Abstract

The purpose of this research is to mine high-value family travelers for CRM systems of online airlines and travel agencies. This research uses the data mining technologies to analyze the online travel market, which consists of clustering, decision tree, and analytic hierarchy process (AHP) procedure with a proposed model. In the research, the market of online air travel (ticket or package) shoppers is divided into six markets. The markets can be ranked via AHP procedure. The study also applies the C5·0 decision tree algorithm on the discovered ranked markets, transactional variables, and socioeconomic variables to create four useful classification rules. The discovered rules can be employed in web-based customer relationship management (CRM) marketing systems for airlines and online air travel agencies for enhancing the travelers’ growth rates and customer values.

Keywords:

• Data mining
• AHP procedure
• C5·0 decision tree
• CRM marketing systems

Notes

1 Juniper Research: mobile research specialists, providing market intelligence, consulting, market data and forecasting to the mobile telecoms industry. Data source: www.juniperresearch.com/