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Marketing Intelligence and Automation – An Approach Associated with Tourism in Order to Obtain Economic Benefits for a Region

  • Célia M. Q. Ramos
  • Nelson Matos
  • Carlos M. R. Sousa
  • Marisol B. Correia
  • Pedro Cascada
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10277)

Abstract

Technologies have revolutionized the way campaigns are developed in the digital medium, and how customers search for information and buy products or services. At the same time, the development of technologies has led to an exponential growth of information, a proliferation of data sources, and the emergence of new tools to support the process of building campaigns targeted at customers. In this context, there is a challenge to surmise that technologies can be the solution to improve communication and information dissemination through the development of digital marketing platforms. The platforms automate campaigns, by using and accessing information stored in the tourism and hospitality organizations’ Data Warehouse, to perform data analysis that include data mining techniques, bringing this way economic benefits for these organizations. The present article proposes a methodological framework for the development of a Marketing Intelligence Automation system, with the objective to facilitate the management of an integrated marketing strategy for online channels of hospitality and tourism organizations.

Keywords

Digital marketing Marketing intelligence Marketing automation Big Data Tourism organizations 

Notes

Acknowledgements

This work was supported by CEFAGE (PEst-C/EGE/UI4007/2013).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Célia M. Q. Ramos
    • 1
    • 2
  • Nelson Matos
    • 1
    • 4
  • Carlos M. R. Sousa
    • 1
  • Marisol B. Correia
    • 1
    • 3
  • Pedro Cascada
    • 1
  1. 1.School of Management, Hospitality and Tourism (ESGHT)University of the AlgarveFaroPortugal
  2. 2.CEFAGE – University of ÉvoraÉvoraPortugal
  3. 3.CEG-IST – University of LisbonLisbonPortugal
  4. 4.CIEO – University of the AlgarveFaroPortugal

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