Bestseller lists and product discovery in the subscription-based market: Evidence from music streaming

Abstract

Our study analyzes the impact of hourly-updated bestseller lists on music discovery in a digital streaming platform to provide evidence of whether and why bestseller lists affect consumer decisions in the subscription-based market. We circumvent the problem of demand-popularity simultaneity by leveraging high-frequency data and a regression discontinuity design. We find that being added to the top 100 charts increases song discovery by 11–13%. Furthermore, a series of analyses suggest that the saliency effect, instead of observational learning, is more likely to drive this behavioral change among streaming users. Specifically, we find that a song's chart entrance increases repeat consumption, normative rank positions within the top 100 lists do not demonstrate significant discontinuity, and an artist or a song's prior popularity does not moderate this effect.