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How can Data and Analytics Really Help the Music Industry

Music streaming services like Spotify, Apple Music and Amazon have returned the recorded music industry to growth, YouTube has more than one billion people a month watching music videos and social networks like Facebook and Twitter have become important marketing channels for labels and artists.

All these platforms are also huge generators of data for labels, distributors and managers. But they are also the spur for a new challenge for our industry: how best to process, understand and act on the billions of lines of data that they are providing.

This goes hand-in-hand with another key trend: the shift from measuring sales of music to measuring consumption of music and acting on the lessons of that measurement to help services maximize their user base and engagement, and give artists the best chance of reaching, retaining and growing their audiences.

The use of data in an industry which has often relied on ‘gut instinct’ created some initial tensions, despite the historical importance of chart data within the industry. In 2018, the emphasis is on marrying the two disciplines: the intuition of creative humans and the analysis of data to back up their instincts, or to help them understand when they may need to tweak their strategies.

Data is also a new source of costs for labels, services and distributors, as they decide whether to build their own data-processing and analysis tools in-house, or use those of third-party technology providers. Some use a hybrid of the two.

There is a widespread understanding that a firehose of data from streaming services and social networks is useless unless it can be interpreted correctly, and used to make key creative and business decisions.

There is already a hierarchy of digital service providers (DSPs) in terms of how much investment and effort labels are able to put into bespoke tools and teams to analyse their data. Services like Spotify, Apple Music and Deezer are the audio-streaming focus for the data teams at most labels, while YouTube is key on the video side.

The data provided by these DSPs also necessitates collaboration for different industry players: for example between labels and artist managers, when labels are granted access to the data that artists and management have already been receiving directly from the streaming services.

Labels are putting this data to work on a day-by-day basis in the service of their artists. It may be as simple as identifying when a track is taking off so that marketing resources can be shifted instantly to take advantage; through to using ‘data storytelling’ in the pitching process to get on to the key programmed playlists at Spotify and Apple Music. Evidence that an artist is building traction on those platforms and elsewhere can help to build a convincing case.

From proving that a ‘heritage’ act is already reaching young fans via streaming ahead of a tour, to identifying spikes in a certain territory that may indicate potential for collaborating with local artists, data can have an impact on the businesses as well as the creative projects of musicians. However, labels understand that the data must be used to inform the creative process, rather than to drive it.

In the year of the Cambridge Analytica data-privacy controversy, labels, music companies and streaming services are well aware of their responsibilities around the data they collect, store and use on fans.

Compliance with the recently-introduced GDPR regulations in Europe has been a priority for the industry, and although labels accept that this compliance has, for example, reduced the size of many mailing lists for artists, they hope that the fans who remain are the most engaged – and so qualitatively, this is no bad thing.

Finally, the challenges and opportunities around data are sparking plenty of activity in the startup sector, with technology companies keen to help labels and music companies make sense of their data pipelines, or simply to ensure that their own data is clean and fit-for-purpose.

Ten of them – Asaii, Auddly, Chartmetric, Instrumental, Linkfire, Seated, Seeqnc, Sodatone, Soundcharts and WARM – are profiled in this report.