Chartmetric VS Every Noice at Once

I don't deal in the music you make to understand your market, but use https://everynoise.com/ to really narrow the genre and then check https://chartmetric.com/ for the stations that play those artists. Source: about 1 year ago

Could get a bit costly but look into chartmetric.com. It's a music database full of different playlists and their curators. Ideally your best bet is to find smaller-indie artists you consider yourself similar to and look into what playlists they've been featured on and try contacting those curators. If they don't have a lot of major artists on their playlists and typically feature material from bands/artists that... Source: about 1 year ago

I interned at a company called Chartmetric one summer that you may find interesting. Happy to chat if you have any questions! https://chartmetric.com/. - Source: Hacker News / over 1 year ago

I tried looking at some tools out there like ChartMetric but they don't have the data we need. I also tried to contact Spotify but they couldn't help me out there. Source: over 1 year ago

Has anyone used programs like Chartmetric, Sodatone, Songsters and Sound Charts? Pros/Cons? What type of data or queries do you find the most useful? Are there any other programs besides these that are helpful? Source: about 2 years ago

I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / 9 days ago

Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / 25 days ago

The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 4 months ago

This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 5 months ago

Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 5 months ago