Identifying high-value airlines customers for strategies of online marketing systems

Identifying high-value airlines customers for strategies of online marketing systems PurposeThe purpose of this study is to discover valuable customers for enterprises. The international market of Taiwan airlines can be enhanced; thus, this study aims at Taiwan’s airline market as a research area.Design/methodology/approachThis research uses data mining technologies with a proposed model to analyse airline customer values for big data online marketing systems, such as customer relationship management (CRM) system. The research applied supervised apriori algorithm, socio-economic variables and a proposed model to discover the rules/markets.FindingsThe results show that eight markets were discovered and three association rules were established for business systems of airlines.Originality/valueThe valuable travellers/markets can be discovered by this research. By collecting shoppers’ transactional data, global online CRM and point of sales (POS) systems can be big data marketing systems. The research framework can be easily applied in online CRM/POS or big data marketing systems for international airlines; however, it is for other global businesses as well. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Identifying high-value airlines customers for strategies of online marketing systems

Kybernetes , Volume 47 (3): 14 – Mar 5, 2018

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Publisher
Emerald Group Publishing Limited
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0368-492X
D.O.I.
10.1108/K-12-2016-0348
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this study is to discover valuable customers for enterprises. The international market of Taiwan airlines can be enhanced; thus, this study aims at Taiwan’s airline market as a research area.Design/methodology/approachThis research uses data mining technologies with a proposed model to analyse airline customer values for big data online marketing systems, such as customer relationship management (CRM) system. The research applied supervised apriori algorithm, socio-economic variables and a proposed model to discover the rules/markets.FindingsThe results show that eight markets were discovered and three association rules were established for business systems of airlines.Originality/valueThe valuable travellers/markets can be discovered by this research. By collecting shoppers’ transactional data, global online CRM and point of sales (POS) systems can be big data marketing systems. The research framework can be easily applied in online CRM/POS or big data marketing systems for international airlines; however, it is for other global businesses as well.

Journal

KybernetesEmerald Publishing

Published: Mar 5, 2018

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