In our modern world, music metadata has become an essential statistic to track like keeping a finger to the pulse of the industry to keep track of everything that happens to digital music. But before getting into music metadata management, let’s define what metadata is:
There are generally three different types of music metadata:
- Descriptive metadata
- Ownership/Performing rights metadata
- Recommendation metadata
Descriptive metadata is the “front-end” of the data which the copyright owner describes and the listener can see. This metadata is the band or artist name, song titles, track listing, release and creation date, the cover art or song art, and genres the track is listed under. If you look on Spotify, all the music data you can actively see is provided from the descriptive metadata.
Ownership/Performing rights metadata is the data that lists and sets the proportion of the royalty and licensing of the music track. This data is what record labels and artists receive to help them manage royalties and understand how they should operate their music business effectively. This metadata is one of the best tools for music labels and publishers.
Recommendation metadata becomes a little confusing as it’s more dependent on the streaming platform or recommendation service. They would designate this metadata to better suit their service’s listeners to allow the music to reach the right ears. This metadata can include genre, similar genres, mood, beats per minute, and even the demographic of the listeners. An example of this is found in Spotify’s recommended playlists as similar songs match the same recommendation metadata of the music someone was previously listening to.
Why Should Music Professionals Take Music Metadata Seriously?
From the creation of descriptive metadata to recommendation metadata, it’s extremely important to have a clean music metadata database. In our digital world, metadata can help music professionals sort their work and help manage royalties and licensing.
Music metadata accuracy has become one of the biggest gifts and issues in the modern streaming age of music. There are many cases where descriptive metadata was typed incorrectly, or not as detailed as it should be and caused much confusion or lack of recommendation to listeners. Once the metadata is correct and detailed, this accuracy can benefit professionals as the music can be properly sorted and distributed.
Performance metadata has become vital to track as this metadata describes how many digital streams, sync, and airplay the music has done. Once this metadata is collected, the music label or copyright owner can distribute royalties appropriately with a solid record to work from. The accuracy of this data is extremely important to keep labels and artists happy, and many software suites like Reptroir helps to keep track of everything.
Streaming services are always working on developing more accurate recommendation systems based on music metadata. After these platforms create proper descriptive metadata, the streaming services can properly recommend music. Spotify, for example, acquired The Echo Nest data platform in 2014 for 49.7 million euros to better enhance their service. This data platform has been expanded and improved to help Spotify build better recommendation metadata to more effectively engage listeners. Recently, a subsection of recommendation metadata, discovery metadata, has become a hot topic to help smaller labels and artists become discovered.
How to Manage Music Metadata?
When preparing music for distribution, it’s wise to fill in as much descriptive metadata as accurately as possible. It’s best to make this a conscious habit to fill every section of metadata and check spelling and details twice over. It’s not uncommon for song titles to be typed incorrectly, contributing artists to be forgotten, and genres to be too broad.
It’s recommended to manage performance rights metadata within a software including a music metadata database. Good news: we commercialized the software suite our team used for music metadata management!
Reprtoir was made to better enhance the accuracy of royalty splits and manage artists and labels. When this metadata is handled properly, it can be a breeze to work with. However, when there’s an issue or confusion with the metadata, it becomes cumbersome to work with and many problems can arise. Common issues are human errors and computer glitches that lead to missing performance metadata.
Recommendation metadata is typically handled quite well by streaming services since much of their platforms operate from recommendations and discovery. However, it’s important to keep up to date with how their services change to understand the underlying technology through press releases and technology updates.
Reprtoir has built a CMS especially designed for music metadata management: Catalog Management Solution. Users can upload their catalogs, fill in the details and keep updating all their tracks and albums. You can then access the rest of our features to manage releases, royalties, playlists…
This is all a part of a software squirt from Reprtoir, integrating several products and music service integrations to fit the needs of our users. Willing to get in touch with us? You can book a demo here.