The innovative side of Spotify – which has integrated the notion of audio streaming into our lives – aside, it has managed to differentiate itself from its competitors by focusing on a personalized musical experience and by offering personalized playlists to its users. Initially, the main purpose of Spotify was to make it easier to find the music you want but increasingly, Spotify focused on personalization and discovery of new songs, that is why it had to invest heavily in Machine Learning.
Spotify collects personal data with the aim of satisfying its users, knowing that a streaming platform is nothing without them. Admittedly, Spotify needs to process the data in question, but does so as part of its vision of a personalized experience that it wishes to give to its users by using Machine Learning. A good will have an economic value if it is useful and possible to assign. Its value will increase depending on its rarity. Thus, a group of information can have a value, in the digital age, both direct because they can be the subject of an assignment for the benefit of third parties, and indirect when for example the platforms process it to improve their service. This is the case with Spotify, which uses this information to provide a personalized experience to its users.
If Spotify wants to keep its place in the hierarchy and thus obtain economic gains, it will have to be correct with users, but also continue to feed its platform so that they do not get bored. To be more attractive, as we have seen, Spotify offers personalized playlists and other features, generated using data collected by users.
Mémoire “Les conditions d’utilisation des plateformes de streaming audio : l’exemple de Spotify à travers makromusic”, Irmak TUNCER, juriste Propriété Intellectuelle.