Changing Their Tune: How Consumers' Adoption of Online Streaming Affects Music Consumption and Discovery
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Marketing Science Institute Working Paper Series 2016 Report No. 16-136 Changing Their Tune: How Consumers’ Adoption of Online Streaming Affects Music Consumption and Discovery Hannes Datta, George Knox, and Bart J. Bronnenberg Revised May 2017 “Changing Their Tune: How Consumers’ Adoption of Online Streaming Affects Music Consumption and Discovery” © 2016 Hannes Datta, George Knox, and Bart J. Bronnenberg; Report Summary © 2016 Marketing Science Institute MSI working papers are distributed for the benefit of MSI corporate and academic members and the general public. Reports are not to be reproduced or published in any form or by any means, electronic or mechanical, without written permission. Report Summary Streaming has rapidly become a predominant technology for the distribution and consumption of digital goods like music and movies. Unlike in the ownership model, when consumers purchase content, streaming services provide consumers access to vast libraries where content is free at the margin. Hence, the price of variety decreases for adopters of streaming. Constructing a unique panel data set of individual consumers’ listening behavior on digital music platforms, the authors estimate the short-, medium-, and long-term effects of adopting a particular streaming service on quantity, variety and discovery of new digital content. Among key findings, they find that consumer adoption of streaming leads to: Increases in quantity of consumption. A half-year after users adopt Spotify, consumption, measured in play counts, is up by 43%. Increases in variety of consumption. For example, the number of unique artists listened to increases by 36% six months after adopting streaming. Increases in discovery of new music. Relative to music ownership where experimentation is expensive, repeat listening increases for consumers’ best new discoveries. Implications The results have implications for consumers and producers of music, and are also of interest to entertainment researchers, trade organizations (e.g., RIAA) and governmental agencies (e.g., FCC). • Streaming revenues are climbing not only because more consumers are adopting streaming, but because consumers’ overall consumption of music is growing as well. • Streaming creates a more level playing field for smaller artists; however, while it is easier to enter the consumption set, it is harder to stay there. • Streaming expands consumers’ attention to a wider set of artists, potentially increasing demand for complementary goods, like live performances. • Streaming alleviates a deadweight loss problem for varieties where valuation is positive but below the price of ownership. • Streaming increases consumer welfare by reducing search frictions (e.g., enhancing discovery) and helping users discover new high-value content. Hannes Datta is Assistant Professor of Marketing and George Knox is Associate Professor of Marketing, both at Tilburg University, The Netherlands. Bart J. Bronnenberg is Professor of Marketing, Tilburg University, and Research Fellow in Industrial Organization, CEPR, London. Marketing Science Institute Working Paper Series 1 Acknowledgements The authors thank Wes Hartmann and Puneet Manchanda for comments on an earlier draft. They are also grateful for comments from seminar participants at Amsterdam Business School, INSEAD, Tilburg University, the University of Cologne, the Catholic University of Leuven and Vlerick Business School, the University of Oxford, the University of Michigan, Yale University, Eurosonic Noorderslag, participants at the 2016 Marketing Science and Marketing Dynamics Conferences, and executives at Buma/Stemra, Sony Music and Spotify. The authors acknowledge financial support from the Netherlands Foundation for Science (NWO 453-09-004) and from the Marketing Science Institute (MSI 4-1854). Marketing Science Institute Working Paper Series 2 Introduction Traditionally, copyright-related industries have suffered as new digital technologies disrupted their revenue models. One such disruptive technology that is taking over the music industry is streaming, which allows consumers to rent unlimited access to a vast library of content. Digital music revenues, previously driven by purchases, now mostly derive from subscription fees; in 2015, streaming became the single largest source of music industry revenues in the U.S. (Friedlander 2016). A similar shift from ownership-based to streaming-based business models is taking place in other copyright-related industries (e.g., movies, games, books). Similar to research on file sharing, the rise of streaming has triggered a discussion among researchers about its effects on producers’ profits. Using song-level digital sales, Aguiar and Waldfogel (2015) find that streaming displaces ownership-based downloads. In a survey panel, Wlömert and Papies (2016) show that free, ad-supported streaming services cannibalize demand from other channels; since revenues from paid subscriptions more than offset this effect, streaming positively affects sales. Aguiar (2015) documents that ad-supported streaming of music increases visits to legal and illegal downloading websites among heavy users. Missing from the literature is an account of how streaming affects consumption behavior at the individual level. We study how streaming technology affects music consumption in three ways. We first ask to what extent streaming generates additional music consumption rather than displacing consumption from other platforms. Access to a wide variety of content on a streaming platform may entice consumers to consume more, potentially turning deadweight loss —music that is valued above zero but below its purchase price, and hence is not consumed— into surplus (e.g., see also Waldfogel 2012). Another possibility is that consumers merely shift consumption to other platforms: the songs may be different, but the time spent listening remains unchanged. Second, music is a consumption good for which most consumers have a love of variety. We study the effects of streaming on the nature and size of the subset of variety chosen. In the ownership model, when consumers purchase and download specific music titles, variety is costly at the margin; in the streaming model, variety is free at the margin. We measure the breadth of variety in terms of the number of distinct artists, songs, and genres consumed. Next, we measure how users reallocate their time listening, whether they concentrate on a few artists (e.g., superstars, Elberse 2008; Rosen 1981), songs or genres, or spread their time listening across a Marketing Science Institute Working Paper Series 3 wider set of artists. If consumers concentrate their consumption on a few major artists, they perpetuate a winner-take-all market. If, on the other hand, consumers now broaden their consumption, streaming may level the playing field to the benefit of smaller music producers, e.g., indie artists or labels. Third, an important determinant of welfare are consumers’ search frictions when discovering new high-value content. We investigate how music discovery changes after adopting a streaming technology. By reducing the costs of exploring the variety of music, streaming allows—according to one estimate—the average user to discover 27 new artists per month (Kissel 2015). To what extent do these new discoveries actually yield highly played songs? We investigate this issue empirically by considering how streaming affects repeat consumption for new titles in general, and for selected popularity deciles of new discoveries. We examine the effects of streaming by focusing on the moment of adoption of Spotify, currently the largest streaming provider serving 100 million customers in 60 countries (Spotify 2016). We construct a unique panel data set capturing individual-level music consumption by using a third-party service that tracks consumers’ platform choices and listening behavior across a wide set of platforms. We identify (self) “treated” consumers who adopt streaming in our observation window, though they may continue to use other providers. Next, we match adopters to “control” users who do not adopt streaming. We also measure variety using a secondary data set with meta-level characteristics for more than 200,000 artists. We identify treatment effects of adopting a streaming service on total music consumption on all platforms in the short- (within two weeks), medium- (up to six months), and long-term (six to twelve months after adoption). We use a differences-in-differences (DID) approach that controls for unobserved user-level and time-varying characteristics. Two forms of selection complicate our identification strategy. First, our data lack a randomized assignment of consumers into treatment and control conditions; we use a quasi-experimental procedure to distinguish causal treatment effects from simple differences in the characteristics between adopters and non- adopters (e.g., Bronnenberg, Dubé, and Mela 2010). Second, the demographic profile of sampled consumers may not be representative of the larger population of potential adopters. Hence, we study local average treatment effects (LATE) among those consumer segments who adopt streaming. Marketing Science Institute Working Paper Series 4 We find that adoption of streaming services leads to a long-run growth of 43% in overall music consumption across all platforms. A sizeable amount of consumption on streaming services comes at the expense of ownership platforms such as iTunes, Winamp and Windows Media Player. Breadth of variety increases and concentration