• 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