The Path to Success - How Playlist Inclusions Predict Success of Songs on Music Streaming Services

Aktivität: VortragWissenschaftlicher Vortrag (Science-to-Science)


On access-based online content services users are confronted with ever-increasing content libraries and content owners compete for the users limited time. One example is the music industry, where streaming services provide consumers with access to millions of songs and content owners (e.g., artists and labels) earn
income according to their market share of streams. To help consumers navigate
these vast content libraries, curated playlists, which feature selections of songs by
different artists according to a specific context, have emerged as a new tool to
influence demand. Despite their important position, the role of playlist curators in
shaping demand is not well understood. On the one hand, curators base their
decisions on information about new songs before they become available and may
thus influence the trajectories of song. On the other hand, curators may select
songs that are already successful and hence, merely react to a song's positive
trajectory. In this research, we develop a methodology to determine the influence
of playlist curators using network analysis techniques. By placing each playlist in
a latent space, their centrality in the dynamic network of playlists at a given point
in time can be determined. We show that listings on more central playlists have a
positive effect on the success of a songs and this effect is stronger than the number of followers a playlist has. The results are relevant for content publishers,
whose investments in new talent are both costly and risky due to the low success
rate in this market. Our model can be used to identify promising talent early in
their careers. In addition, artists may use the findings to design efficient seeding
strategies by targeting influential curators with their content. Our findings also
explain which curation decision drive the importance of a curator in the network
and may thus be used to optimize curation.
Zeitraum3 Juni 20215 Juni 2021
EreignistitelINFORMS Marketing Science 2021
VeranstaltungstypKeine Angaben