Explore music data to enhance customer satisfaction

Kayar G., Sümer T., Soytürk F., Doruk G. E., Çobanoğlu C.

e-Review of Tourism Research, vol.17, no.3, pp.444-451, 2019 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 3
  • Publication Date: 2019
  • Journal Name: e-Review of Tourism Research
  • Journal Indexes: Scopus
  • Page Numbers: pp.444-451
  • Keywords: Customer satisfaction, Data analysis, Spotify API
  • TED University Affiliated: Yes


© 2019 Texas A and M University.Restaurant-like service areas have been adapting different technologies to enhance customer satisfaction for many years. In this LBR, we share our research idea about how to integrate music data and its analysis for this purpose. In the first part, we propose a voting system tocarry your favorite song to the top of the list to be played next in your place. In the secondpart, we propose a recommendation system to find a place that suits your music requirements inyour close proximity. Our preliminary survey results for the first part and the data analysis results for the second part shows that our approach has a promising potential for customer satisfaction.