Canadian Musician - January / February 2020 | Page 38

DEMYSTIFYING STREAMING PLAYLISTS How do you get on them & does it even matter? BY MICHAEL RAINE It’s commonly accepted that on-demand streaming has changed how people – especially young people – consume music. Apple Music, Amazon Music Unlimited, YouTube Music … They all feature a ton of playlists, but there is obviously one platform that, for good rea- son, has come to define this trend: Spotify. By making playlists a focus of its user experience, and not just for listening but also for engaging, Spotify amped up playlists’ im- portance in the music ecosystem. Spotify’s innovation wasn’t simply allowing users to curate their own playlists, which could draw from the entire history of recorded popular music. The simple but important thing Spotify pioneered was allowing user-created playlists to be public for other users to follow. Intentionally or not, this created a whole ecosystem of music influencers out of average music fans. It also created a massive, data-rich “farm system” through which Spotify could move songs in order to better curate its own playlists. Over the last few years, breaking into that playlist ecosystem and getting songs on the most popular ones has become something of a fixation for the music in- dustry, and it’s somewhat justified. Playlist placements can help break an artist and greatly boost their numbers, but like most fixations, its importance can be overblown. For artists, it’s important to under- stand how this playlist ecosystem works in order to better tailor your approach 38 C A N A D I A N M U S I C I A N to the game – or decide if it’s even worth playing. “I’d say about two or three years ago it really started ramping up,” says George Goodrich, founder of playlist pitching ser- vice Playlist Push, about when he noticed artists and industry really focusing their attention and efforts on playlists. “For an indie artist, just directly getting on a big playlist was super difficult; then, even- tually, people started figuring out that there’s a huge ecosystem of these smaller playlists that have a niche following on Spotify that they could tap into to at least get the wheels off the ground, and then they could build up from there. Now even the bigger labels are focused on these user-generated playlists.” Spotify’s playlist ecosystem essen- tially works like a pyramid that songs must climb. At the top are the biggest, human-curated playlists, such as the ex- tremely popular Rap Caviar and New Mu- sic Friday, each with millions of followers. The second tier of the pyramid is a larger swath of Spotify’s own algorithm-curated playlists, which are usually more genre- or mood-specific and can have tens- or hundreds-of-thousands of followers. The base of the pyramid is the ocean of user-generated playlists, of which there are literally billions. Obviously, the quality and importance of these user-generated playlists vary tremendously. It could be a playlist of only Right Said Fred songs with zero followers made for an “I’m Too Sexy”-themed kegger. Or, it could be a well-crafted playlist of cool new indie rock songs with 30,000 followers. Sometimes, the curator is trying to be an influencer in a genre or scene; others, they just happened to make a good playlist for their own enjoy- ment with an SEO-friendly title. “Most people tend to just focus on the big Spo- tify-branded playlists, but in reality, for the indepen- dent artists, those user- generated play- lists are the big opportunity,” says Kevin Breuner, the VP of marketing at CD Baby, co-host of its DIY Musician Podcast, and an indie musician with the band Smalltown Poets. If an artist is determined to break into the world of playlists, user-generated playlists are the open door in the base- ment. Because, unlike the major labels and larger indie labels, artists have no way of pitching directly to Spotify’s edi- tors.* And, it should go without saying, you obviously can’t pitch to an algorithm. What an artist can do, though, with a bit of hard work and ingenuity (and good songs), is generate the analytics that the algorithms will pick up on.