The Spotify Recommender System and Its Impact On User Satisfaction

Spotify is the world’s leading music streaming platform and offers various kinds of services. As with many digital platforms, Spotify use artificial intelligence to person-alize the user experience, also known as a recommender system. This study investi-gates what role Spotify´s recommender system plays in the use of Spotify and if there are any differences in satisfaction between different ages and gender. Therefore, we conducted a survey about how customers are using Spotify, which was shared in dif-ferent forums. In total we received 159 answers with respondents from 21 different countries. One of the main findings was that the three services “Make your own playlist”, “Playlist made by Spotify” and “Recommended songs” are the most popu-lar. Also, a correlation was made in order to investigate the relationship between the satisfaction of “Recommended songs” and if customers add them to their own playlists. The correlation coefficient was 0.44, which is a weak value. Further, two conclusions were arrived at. Firstly, the recommender system plays a major part in how customers use Spotify. Secondly, we cannot see that age and gender would affect the satisfaction of the recommended songs that Spotify suggest significantly.