DocumentCode
638055
Title
Building clusters for CRM startegies by mining airlines customer data
Author
Miranda, Helena Sofia ; Henriques, Rui
fYear
2013
fDate
19-22 June 2013
Firstpage
1
Lastpage
5
Abstract
As airlines strive to gain market share and sustain profitability in today´s economically challenging environment, they should develop new ways to optimize their frequent flyer programs while increase revenues. Aware of the challenges, airlines want to implement a customer relationship management (CRM) strategy based on customer analytics and data mining techniques to support marketing decisions. So, to achieve this goal, we have to apply clustering techniques to the company customer databases and develop a single view of customer across their demographic and behavioral characteristics as well as their value for the company. This will enable the company to identify the most profitable customers and run marketing campaigns more efficiently.
Keywords
consumer behaviour; customer relationship management; data mining; database management systems; marketing data processing; pattern clustering; travel industry; CRM strategies; airlines customer data mining; behavioral characteristics; clustering techniques; company customer databases; company value; customer analytics; customer relationship management; demographic characteristics; frequent flyer programs; market share; marketing decisions; profitability; revenues; Algorithm design and analysis; Clustering algorithms; Companies; Data mining; Databases; Partitioning algorithms; Self-organizing feature maps; Cluster analysis; airlines; customer relationship management; data mining; decision support;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Systems and Technologies (CISTI), 2013 8th Iberian Conference on
Conference_Location
Lisboa
Type
conf
Filename
6615775
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