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

  • Célia M. Q. RamosEmail author
  • 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)


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.


Digital marketing Marketing intelligence Marketing automation Big Data Tourism organizations 



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


  1. 1.
    Albert, W., Tullis, T.: Measuring the User Experience: Collecting, Analyzing and Presenting Usability Metrics, 2nd edn. Newnes, Oxford (2013)Google Scholar
  2. 2.
    Alpaydin, E.: Introduction to Machine Learning, 3rd edn. MIT Press, Cambridge (2014)zbMATHGoogle Scholar
  3. 3.
    Brown, B., Sikes, J., Willmott, P.: Bullish on Digital: McKinsey Global Survey Results. Mckinsey & Company, New York City (2012)Google Scholar
  4. 4.
    Büchner, A.G., Mulvenna, M.D.: Discovering internet marketing intelligence through online analytical web usage mining. ACM Sigmod Rec. 27(4), 54–56 (1998)CrossRefGoogle Scholar
  5. 5.
    Burke, M., Hiltbrand, T.: How gamification will change business intelligence. Bus. Intell. J. 16(2), 8–16 (2011)Google Scholar
  6. 6.
    Cascada, P., Ramos, C., Sousa, C.: Utilização de medidas de valor do cliente na criação de listas de distribuição: aplicação ao setor hoteleiro. DosAlgarves. Multi. E-J. 23, 51–74 (2014)Google Scholar
  7. 7.
    Deighton, J.A.: The future of interactive marketing. Harv. Bus. Rev. 74(6), 151–160 (1996)Google Scholar
  8. 8.
    Di Tria, F., Lefons, E., Tangorra, F.: Big data warehouse automatic design methodology. In: Hu, W.-C., Kaabouch, N. (eds.) Big Data Management, Technologies, and Applications, pp. 115–149. IGI Global, Hershey (2014). doi: 10.4018/978-1-4666-4699-5 CrossRefGoogle Scholar
  9. 9.
    Dionísio, P., Rodrigues, J.V., Faria, H., Canhoto, R., Nunes, R.C.: B-Mercator - Blended Marketing. Publicações Dom Quixote, Lisbon (2009)Google Scholar
  10. 10.
    Douyère, C., Sosthé, F.: e-Reputation management and strategic business development using web 2.0 tools: the case of the hotel industry. In: Mariani, M.M., Baggio, R., Buhalis, D., Longhi, C. (eds.) Tourism Management, Marketing, and Development, pp. 99–112. Palgrave Macmillan, US (2014). doi: 10.1057/9781137354358.6 Google Scholar
  11. 11.
    Fan, S., Lau, R.Y., Zhao, J.L.: Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Res. 2(1), 28–32 (2015)CrossRefGoogle Scholar
  12. 12.
    Floreddu, P.B., Cabiddu, F., Evaristo, R.: Inside your social media ring: how to optimize online corporate reputation. Bus. Horiz. 57(6), 737–745 (2014). doi: 10.1016/j.bushor.2014.07.007 CrossRefGoogle Scholar
  13. 13.
    Hassenzahl, M., Tractinsky, N.: User experience - a research agenda. Behav. Inf. Technol. 25(2), 91–97 (2006). doi: 10.1080/01449290500330331 CrossRefGoogle Scholar
  14. 14.
    Hellemans, K., Govers, R.: European tourism online: comparative content analysis of the ETC website and corresponding national NTO websites. In: Frew, A.J. (ed.) Information and Communication Technologies in Tourism 2005, pp. 205–214. Springer, Vienna (2005). doi: 10.1007/3-211-27283-6_19 CrossRefGoogle Scholar
  15. 15.
    Inmon, W.H.: Building the Data Warehouse. Wiley, Hoboken (2005)Google Scholar
  16. 16.
    Kimball, R., Ross, M.: The Data Warehouse Toolkit. Wiley, Hoboken (2002). doi: 10.1145/945721.945741 Google Scholar
  17. 17.
    Kotler, P., Bowen, J.T., Makens, J.: Marketing for hospitality and tourism, 5th edn. Pearson Education, India (2009)Google Scholar
  18. 18.
    Lendrevie, J., Lévy, J., Dionísio, P., Rodrigues, J.V.: Mercator da língua Portuguesa. Publicações Dom Quixote (2015)Google Scholar
  19. 19.
    Matos, N., Correia, M.B., Ramos, C.M.Q., Sousa, C.M.R., Cascada, P.M.: Marketing intelligence – a conceptual model for the development of a marketing intelligence platform for tourism organizations. In: TMS ALGARVE 2016 – Tourism and Management Studies International Conference, 16–19 November, Olhão, Portugal, p. 120 (2016)Google Scholar
  20. 20.
    Mediact, I.: 5 Holiday shopping trends to watch in 2015 (2015).
  21. 21.
    Michalski, R.S., Carbonell, J.G., Mitchell, T.M. (eds.): Machine Learning: An artificial intelligence approach. Springer Science & Business Media, Heidelberg (2013)Google Scholar
  22. 22.
    Middleton, V., Clarke, J.: Marketing in Travel and Tourism, 3rd edn. Butterworth-Heinemann, Oxford (2001)Google Scholar
  23. 23.
    Mohanty, S., Jagadeesh, M., Srivatsa, H.: Big Data Imperatives. Apress, Berkeley (2013). doi: 10.1007/978-1-4302-4873-6 CrossRefGoogle Scholar
  24. 24.
    Novelli, M., Schmitz, B., Spencer, T.: Networks, clusters and innovation in tourism: a UK experience. Tour. Manage. 27(6), 1141–1152 (2006). doi: 10.1016/j.tourman.2005.11.011 CrossRefGoogle Scholar
  25. 25.
    Oliveira, C.: Consultoria e formação em Marketing Digital para PME’s. Instituto Politécnico do Porto (2014)Google Scholar
  26. 26.
    Öztürk, S., Okumuş, A., Mutlu, F.: Segmentation based on sources of marketing intelligence, marketing intelligence quotient and business characteristics in software industry. J. Sch. Bus. Adm. 41(2), 227–240 (2012)Google Scholar
  27. 27.
    Pan, B., Li, X.R.: The long tail of destination image and online marketing. Ann. Tour. Res. 38(1), 132–152 (2011). doi: 10.1016/j.annals.2010.06.004 CrossRefGoogle Scholar
  28. 28.
    Pang, Y., Hao, Q., Yuan, Y., Hu, T., Cai, R., Zhang, L.: Summarizing tourist destinations by mining user-generated travelogues and photos. Comput. Vis. Image Underst. 115(3), 352–363 (2011). doi: 10.1016/j.cviu.2010.10.010 CrossRefGoogle Scholar
  29. 29.
    Ramos, C.M.Q., Correia, M.B., Rodrigues, J.M.F., Martins, D., Serra, F.: Big data warehouse framework for smart revenue management. In: 3rd NAUN International Conference on Management, Marketing, Tourism, Retail, Finance and Computer Applications (MATREFC 2015), pp. 13–22 (2015)Google Scholar
  30. 30.
    Ramos, C., Rodrigues, P., Perna, F.: Sistemas e tecnologias de informação no sector turístico. J. Tour. Dev. 12, 21–32 (2009)Google Scholar
  31. 31.
    Rich, E., Knight, K., Nair, S.B.: Artificial Intelligence, 3rd edn. Tata McGraw-Hill, New Delhi (2009)Google Scholar
  32. 32.
    Schmitt, B.: Experiential marketing. J. Market. Manage. 15(1–3), 53–67 (1999). doi: 10.1362/026725799784870496 CrossRefGoogle Scholar
  33. 33.
    Schmitt, B.: The consumer psychology of brands. J. Consum. Psychol. 22(1), 7–17 (2012). doi: 10.1016/j.jcps.2011.09.005 CrossRefGoogle Scholar
  34. 34.
    Sebastião, S.P.: Comunicação Estratégica – as Relações Públicas. Instituto Superior de Ciências Sociais e Políticas, Lisboa (2009)Google Scholar
  35. 35.
    Tang, L.R., Jang, S.S., Morrison, A.: Dual-route communication of destination websites. Tour. Manage. 33(1), 38–49 (2012)CrossRefGoogle Scholar
  36. 36.
    Volo, S.: Bloggers’ reported tourist experiences: their utility as a tourism data source and their effect on prospective tourists prospective tourists. J. Vacation Market. 16(4), 297–311 (2010). doi: 10.1177/1356766710380884 CrossRefGoogle Scholar
  37. 37.
    Wiedmann, K., Prauschke, C.: How do stakeholder alignment concepts influence corporate reputation? The role of corporate communication in reputation building. In: 10th Conference on Reputation, Image, Identity, and Competitiveness (2006)Google Scholar
  38. 38.
    Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann Publishers Inc., San Francisco (2005)zbMATHGoogle Scholar
  39. 39.
    Wymbs, C.: Digital marketing: the time for a new “Academic Major” has arrived. J. Market. Educ. 33(1), 93–106 (2011). doi: 10.1177/0273475310392544 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Célia M. Q. Ramos
    • 1
    • 2
    Email author
  • 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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