New Demo Music Observatory Dataset: Domestic Market Share On Spotify National Charts
The conversion to a subscription-based sales model with Spotify, Apple Music, YouTube Music, Deezer, Pandora and similar services was hailed by some to beat piracy and bringing back growth to the recording industry. However, there are very few labels and artists who actually feel that they are profiting from this conversion.
In our Central European Music Industry Report we have shown the paradox of streaming growth: while the streaming market appears to be growing, for the individual rightsholder, artists, or label, neither the volumes nor the revenues show much of a growth. There are many factors contributing to the fact that for the ‘typical’ artist streaming does not bring revenue growth, and one of them is the increasing competition with the major label released music, particularly from the United States.
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For a long time, the user base of Spotify and similar services did not expand at the same rate as the available repertoire, so more and more songs were competing for not so many users, many of them ending up on the never played Forgetify list. In other words, competition has been steadily growing.
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In Europe, almost everybody would like to get to the U.S. (getting harder and harder) or the UK (getting somewhat more accessible). Some have a strong market background at home, others lost their home market without gaining foreign markets.
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Some smaller markets are somewhat protected from the competition often have low revenues because of the lower subscription fee and slower roll-out of the services. In the first years of the introduction of these services, like in Croatia or Russia this year, it is critically important to use this period to gain experience with holding or increasing local market shares.
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The local music industry must find ways to train algorithms, promote local music contain that is relevant for the new audiences who use streaming platforms. Our Listen Local Initiative aims build new data integrations that can help training data that reverses this trend.
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Our Music Observatory project is aiming to track all indicators that jointly determine streaming success: subscription fees, exchange rates, subscription numbers, use hours, levels of competition, typical playing volumes, typical stream prices, and likelihood of crossing borders to export markets.
Our aim with the Demo Music Observatory is to find a validated business model to bring to light the roughly 2000 indicators collected by our CEEMID project for music pricing, AI, licensing, monitoring, grant evaluation, export market targeting and similar uses. We would like to transfer these data assets to a future European Music Observatory. We are giving away in these weeks about 50 automatically maintained, well documented, high-quality indicators with history and timely new data publications for potential users and founding partners of the European Music Observatory.
We placed the following dataset in our observatory, to be refreshed weekly:
You can download the entire dataset in different formats here in the Music Diversity & Circulation pillar (see all pillars) of our Demo Music Observatory.
We share the view that big data creates injustice
. Organizations that control large amounts of data, for example, the entire listening history of hundreds of millions of people in all major countries of the world, can train algorithms and robots that drive most of the music sales in the world. They can make your investment into a sound recording successful or doomed. They can circumvent or help a local content regulation, reinforce, or disable a national cultural policy goal. We want big data to work for small venues, independent labels, startups, great and undiscovered artists
. We believe that you cannot make a successful album launch, a market entry or introduce a successful cultural policy without large amounts of well processed and correctly analysed data. We want to create a Music Observatory that integrates the small data of many small bands, small labels, small venues, small countries, and mount correct the injustice. Make algorithms transparent and the competition fair.