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

Wen‐Yu Chiang

21 citations0/0 files storedTransportation Letters

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Customer churn and segmentation Customer Service Quality and Loyalty Data Mining and Machine Learning Applications

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.

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References

1990How to make a decision: The analytic hierarchy process 2005Customer perceptions of e‐service quality in online shopping 2004Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management 2003Buying or browsing?2008Classifying the segmentation of customer value via RFM model and RS theory 1994Strategic database marketing 2017Business Research Method 2010Data Mining Techniques in CRM: Inside Customer Segmentation

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