While all of these services desperately try and establish a point-of-difference, they’re all essentially music streaming platforms and the only difference between them is; who has the biggest catalogue, the aesthetic of the interface and the deals the service has established with labels and distributors.
Discovering new music is a painful process with any of the above aforementioned services. Not once has Spotify recommended me something I haven’t heard before and would listen to, instead it would rather recommend the shitty dubstep my friends have been listening to. I don’t pick my friends based on their musical tastes, I could care less what my friends deem to be an acceptable form of music.
Algorhythmic music discovery is a hard problem to solve. Just because you like the Red Hot Chili Peppers doesn’t mean you’ll like Pearl Jam. Just because you have a couple of Eminem songs in your playlist doesn’t mean you’ll like Kendrick Lamar. The music tastes of a 21st century music lover are highly evolved, music is more personal than movies and books. People don’t just like one type of music, this isn’t the 1950’s any more.
It is safe to assume that people are more likely to read a particular type of literature and that people are either into action movies or they’re into romantic comedies than it is to assume a listener of Metallica will be interested in listening to Slayer. It is worth pointing out movie recommendations suffer from the same problem, Netflix have been running a contest for years to improve their movie recommendations algorithm which still isn’t perfect.
Music discovery with a human element is the only way music discovery can evolve, but can a human element in music discovery scale? Yes.
The direction music discovery is going in is obvious. Just like financial analysts with a good track record are respected, so too are people with music tastes that others deem to be good. Everyone has that one friend who is always telling you about new music they’re finding, you’ve probably heard a similar sentence from a friend recently: “Hey, I’ve really been liking this new StabbyStabStab track, I think you’ll like it”
If you like metalcore, you most likely will be interested in hearing what the vocalist of Caliban recommends and listens to over any automatic suggestion your favourite music service recommends. If you like rap, you will be more inclined to listen to a rap artist or album recommended by Dr Dre or Eminem.
However, music discovery even with a human element thrown into the mix can only go so far. Your favourite metal band vocalist might not actually listen to that much metal, maybe he/she gets their inspiration from classical jazz. Just because your favourite vocalist or taste maker listens to jazz doesn’t mean you will like jazz.
Or to complicate the problem further, you might consider yourself an avid rock fan, however you reach for a sharp knife every time you hear Nickelback playing. A band like Nickelback is considered rock, but is not very well-liked by people who consider themselves rock fans. This is where algorhythmic solutions choke up and can’t easily bypass.
Just like you follow people on Instagram because you like what they post or you follow someone on Twitter because you like what they post, you’re not always going to like what you see being shared, so it is not so much a problem with personal music discovery, but rather a flaw-by-design in the way we form our own tastes and opinions.
Twitter tried and failed to build a music platform based on what others were listening to after acquiring We Are hunted, it wasn’t integrated with the core Twitter product correctly from the beginning and lacked that human element that is becoming increasing crucial for music services to recommend more personalised and correct music recommendations.
The best way to describe what is happening: is the fashion industry. In the fashion industry you have leaders and followers. The leaders are respected in their field and the followers listen and trust what those leaders are saying. If mr bigshot designer is saying loafers are going to be a big deal and has a big enough following, loafers will be a big deal. People will listen to someone they trust and respect: the same theory applies to music discovery.
Fashion magazines are the distribution channel and the listeners are the people that buy the fashion magazines wanting to know what is currently hot and what to wear.
Keep an eye on this space as more and more music services move towards humanised personal music discovery. It is the only way forward.