Spotify Playlists Explained
Allot Lines Customer Support
Last Update 2 years ago
Playlists play an important role in any artist’s career and recognizing the different types of playlists, knowing how they’re created, and what you can expect from them will be vital into truly understanding the playlisting landscape. Spotify has millions of playlists on its platform, all of which can be sorted into a few different categories: Editorial, Algorithmic, and User-generated.
Editorial Playlists
Most digital music services, including Spotify, have a global team of editors that curate playlists to highlight releases and artists to the wider listener base. Spotify editorial playlists exist in the thousands and range from ‘new music’ playlists (Ex: New Music Friday), genre-based playlists (Ex: Indie Pop), mood playlists (Ex: Confidence Boost), decades playlists, and more. These playlists are curated and edited fairly frequently by Spotify editors to keep them up to date with new music, popular tracks, and artists on the rise.
Note: There are now personalized editorial playlists which means some of Spotify’s most popular editorial playlists will have different tracks on them depending on the listener.
Note: Editorial playlists aren't all updated on the same schedule. You may see some updated weekly (New Music Friday) while some others, especially the genre and mood playlists, are updated at different rates.
Algorithmic Playlists
Music fans around the globe utilize Spotify not only to stream music, but also to discover new music as well. Spotify offers algorithmic playlists which use listening history and patterns, as well as the listening practices of similar Spotify users, to curate a playlist specifically for you. A few examples of Spotify’s algorithmic playlists are:
- Discover Weekly: A playlist of 30 songs curated each Monday for a Spotify listener. Discover Weekly is all about just that -- discovery! Spotify will recommend new music based on past listening habits as well as other Spotify users’ listening habits who have similar listening tastes to that specific user.
- Release Radar: Release Radar is generated each Friday and highlights newer music (music released within the last 28 days) Spotify thinks the user will enjoy, but more notably, music by artists the user follows. You must submit your track via Spotify’s Playlist Tool at least 7 days in advance of release day to land Release Radar playlists. Only one track by an artist can be included in a Release Radar at a time, so its important to plan your releases accordingly.
Tip: You’ll want to ensure you encourage your fans to follow you on Spotify so your music lands on their Release Radar playlists.
Other algorithmic playlists on Spotify include: Your Summer Rewind, On Repeat, Your Daily Mix, and Wrapped.
User-generated Playlists
Spotify has millions of users across the globe, many of whom create playlists of their own. Spotify users are able to make their own playlists to collate their favorite tracks, artists, and albums which they can then share with their friends, family, on socials, and more.
User-generated playlists are really important for an artist and to a release as they can help you understand your fan base, increase engagement and activity surrounding a track, and also can spread your music to Spotify users you may not have reached otherwise. These user-generated playlists also help Spotify’s algorithms ‘learn’ what types of Spotify users are listening to your music and make more improved recommendations based on these listening habits and playlists.
Tip: Research your audience and tastemakers and try to reach out to the independent playlist curators. Smaller playlists can be key to have more engaged listeners that can be converted to fans and help your overall performance on Spotify.
It’s important to include user-generated playlists in your marketing efforts, and remember that building consistent engagement on Spotify is key.
Important: You cannot pay to be included on an official Spotify playlist, and Spotify generally recognizes paying for playlist placement as streaming manipulation. You can read more about this here.