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.