Explore music data to enhance customer satisfaction
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Date
2019
Authors
Gizem Kayar
Tolga Sümer
Furkan Soytürk
Galip Erkin Doruk
Cihan Cobanoglu
Journal Title
Journal ISSN
Volume Title
Publisher
Texas A and M University kangjae@tamu.edu
Open Access Color
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Abstract
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. © 2020 Elsevier B.V. All rights reserved.
Description
Keywords
Customer Satisfaction, Data Analysis, Spotify Api, Customer Satisfaction, Data Analysis, Spotify API
Fields of Science
Citation
WoS Q
Scopus Q
Source
E-Review of Tourism Research
Volume
17
Issue
3
Start Page
444
End Page
451
