Metadata is the foundation of the modern digital music industry. It’s one of the most important things for independent musicians to master. In this post, we’re here to break down the 3 different types of metadata you’ll encounter throughout your career. Here’s what you need to know…
3 Types of Music MetadataReleasing music without accurate metadata is like writing a book report and not signing your name. Without it, you don’t just miss out on royalties and sales, you miss out on well-deserved credit for your hard work. Click To Tweet
When it comes to metadata, there are 3 main types you need to be aware of:
- Descriptive Metadata
- Ownership/Performing Rights Metadata
- Recommendation Metadata
Descriptive meta provides details about the content of a recording when it comes to text tags. That includes things like:
- song title
- release date
- track number
- performing artist
- cover art
- main genre, etc.
Every time someone needs to organize, sort, or present the music in some way, descriptive metadata is used. For example, its used to identify it on the radio, to build an artist page on Spotify, etc.
- You’ve probably encountered butchered descriptive data before. — Ever see a misspelled song name or mixed-up release date on Spotify? That’s due to improper descriptive metadata. As you can imagine, this causes a lot of confusion for, not only the artist, but consumers, as well.
Ownership/ Performing Rights Metadata
Typically, numerous parties are involved when it comes to digital streaming. Whether it’s split between lyricists, songwriters, producers, or all three, the revenue has to be properly split up somehow. That’s where Ownership/Performing Rights Metadata comes out to play.
Ownership metadata’s sole purpose is to make sure everyone involved is getting paid accordingly. Royalty splits are incredibly important and can be complicated as it is, don’t make it even harder by inputting inaccurate data.
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Recommendation metadata is a bit different from the other two types of metadata. The other two are clear and definitive. There’s only one song name, one right way to spell the artist’s name, etc.
Recommendation Metadata is subjective.
This data is made up based on how the recording sounds. As you already know, streaming services like Spotify and Soundcloud thrive on their respective music discovery services. However, each platform has its own unique algorithm for doing so, and a different approach to how they input this data.
From mood labels and generative genre tags to song similarity scores, recommendation metadata helps to provide more meaningful connections between tracks and music discovery features to provide better recommendations for users.
Metadata is crucial to the music industry. Whether for better or for worse, the impact it can have on a songwriter’s career is substantial. So, what can you do to avoid making any mistakes?
- Keep track of your metadata from start to finish.
- Make sure your split sheets are defined BEFORE any work ever leaves the studio.
- Double or triple check your metadata before you submit it.
- Follow all guidelines to a “T”.
Releasing music without accurate metadata is like writing a book report and not signing your name. Without accurate metadata, you don’t just miss out on royalties, sales, play counts and more, you miss out on well-deserved credit for your hard work.
To help you out, AFEM and CI have teamed up to create a “Meta Data Best Practice Guide”, and it’s definitely worth checking out. // To download the guide, click here.