How Spotify Discover Weekly Took Me on a Journey of Rediscovery

We’re all music curators.

Portrait of Tammy Strobel
We’re all music curators.
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I’ve been a paying subscriber of Spotify for over a year now. And despite having multiple alternatives to choose from, I’m not going anywhere any time soon. That’s not because Spotify puts all the music I could possibly want at my fingertips – it does – but because of the weekly curated playlists that just get me.

Updated every Monday morning, Discover Weekly gives Spotify listeners the equivalent of a two-hour mixtape tailored for them. For me, this means that my weekly playlist has been stocked with Mandarin songs. Ironically enough, while my grasp of the language is fairly abysmal, I have always enjoyed listening to tunes from artists like Jay Chou, Mayday and Yoga Lin.

While Discover Weekly has definitely disappointed me before, in recent weeks it’s served up some selections that make it seem almost magical. Suddenly, I was being confronted with songs I had listened to and loved over a decade ago, but had since forgotten about.

Furthermore, while Spotify says that Discover Weekly intentionally includes songs that listeners have heard before in order to build trust and a sense of familiarity, these songs had slipped off my radar entirely. I had never played them on Spotify, so the streaming service and its algorithms had no way of knowing that I had ever listened to them before. So when a long forgotten track started up in my ear a month ago, I had a serendipitous feeling of stumbling upon something that I didn’t even know I had missed.

From Khalil Fong’s 红豆 (Red Bean) to David Tao’s Melody and F.I.R.’s Lydia, I was having the time of my life looping these familiar tunes. But perhaps the most significant aspect of rediscovering these songs was the nostalgia that came with them. Given my penchant for running my favorite tunes on endless repeat, I’ve come to vividly associate specific songs with particular memories.

So when Michael Wong’s 童话 (Fairy Tale) and Coldplay’s The Scientist came on, it was easy to be transported back to the time when my biggest concern was whether or not I had brought the right textbook to class. It was almost uncanny – S.B.D.W’s 世界 末日 (End of the World) even showed up one week, as if Spotify knew that I had been enamored with Jay Chou’s 2001 rendition and wanted me to check out original.


While Discover Weekly has definitely disappointed me before, in recent weeks it’s served up some selections that make it seem almost magical. 

These were songs I loved back then, and still appreciate now (whatever you may think of my taste in music), and Discover Weekly helped me see that perhaps some things don’t change much after all.

How does Spotify do it?

Personalized music curation is hard. On the one hand, it requires a certain intimacy that machines and algorithms cannot provide, but on the other it’s also nearly impossible to hire enough music experts to handpick songs for everyone.

But what Spotify has done is turn its user base into a collective music curation resource, where user preferences are aggregated and parsed as a data layer that can be used to provide personalized recommendations for everyone. Simply put, Spotify leverages the playlist (of which there are over 2 billion) – an act of curation in itself – to provide curation at scale to its listeners. 

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Deep learning smarts
Discover Weekly is actually pretty smart, because it knows when not to include that weird song your niece or nephew played on your phone as part of your taste profi le. It differentiates between the music you actively listen to and the songs you listen to passively (or outliers) through clustering algorithms. It works something like this:
• Songs you listen to, but which you’re secretly embarrassed about.
• The bulk of what you listen to, which also best represents your musical identity.
• Outliers, perhaps from when your phone was hijacked by friends in a car.
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