A Rant on Sleep, Spotify, and Personalized Suggestions

I’ve always had a tricky relationship with sleep. It’s like sleep and I are two ships passing in the night—except one ship is always stuck at the dock, and the other is out of reach. I’ve tried all the usual remedies: counting sheep (they kept getting lost), drinking herbal teas (which taste like I’m sipping a garden), and even meditation (but my mind feels like it has too many browser tabs open). The one thing that has consistently helped me drift off is music—specifically, the sleep playlists on Spotify.

The Spotify Love Story

Let me preface this by saying that I’m a loyal Spotify fan. I don’t want or in a better way I’m unable to use Apple Music or YouTube Music (which is not even a good option to consider). Maybe I’m blind to the problems comparing to other products I usually rant about, but I’m just happy with it.

The curated categories are a godsend. Feeling nostalgic? There’s a playlist for that. Need to focus? They’ve got you covered. Want to explore genres you didn’t even know existed, like Viking jazz or underwater techno? Dive right in. And don’t get me started on the personalized playlists like “Discover Weekly” and “Release Radar.” It’s as if Spotify peered into my soul and said, “You know what you’d like? This band from Iceland.” And a lot of times, I find treasure singles for my personal playlists which are more mood-based and less genre-based.

The Nightly Lullabies

But let’s circle back to my nocturnal nemesis: insomnia. In a quest to outsmart my overactive brain, I turned to Spotify’s sleep playlists. These aren’t just any playlists; and you’ll feel strange if you see those songs as singles in their artist’s page. Soft piano melodies, ambient nature sounds, white noise. I’ve tried them all. There’s something oddly comforting about listening to rain falling on a tin roof when you’re lying in bed, even if it’s perfectly dry outside (not a problem in Netherlands of course 😅).

The Algorithm Strikes Back

However, there’s a catch. A side effect, if you will. While these sleep playlists are helping me catch some sleep, they’re also confusing the heck out of Spotify’s algorithms. Suddenly, my “Release Radar” is flooded with new tracks that are just noises. I know I like them at night, but while driving it’s just wrong to me. My “Discover Weekly” thinks I’m exclusively interested in Tibetan singing bowls. Not that there’s anything wrong with those, but they’re not exactly the energizing tunes I need when I’m trying to debug code.

It’s gotten to the point where my annual “Spotify Wrapped” looks like I spent the year in a spa. Friends glance at my shared playlists and raise an eyebrow. “I didn’t know you were into ambient meditation music,” they say cautiously, perhaps wondering if I’m on a journey of self-discovery that I forgot to mention. I have to explain that no, I’m not planning to open a yoga studio; I just can’t sleep without the sound of gentle ocean waves anymore.

The UX Conundrum

This brings me to my main point: Spotify’s user experience design is missing a crucial element—contextual awareness based on time of day. Why can’t it adapt to my nighttime listening habits without derailing my daytime recommendations?

Imagine a Spotify that recognizes when you’re listening to certain types of music based on the time. It’s 11 PM, and you fire up a sleep playlist. Spotify could note that and think, “Ah, they’re trying to sleep. Let’s not let this influence their ‘Discover Weekly’ too heavily.” Then, when morning comes and you switch to your “Get Stuff Done” playlist, the algorithm could prioritize those genres for your personalized suggestions.

I can even make it easier for the algorithm. Just give me a button to exclude a playlist from history. That way it doesn’t have to care about it.

This isn’t just a theoretical idea. Other apps and services are starting to incorporate contextual and temporal data to enhance user experience. When I get into my car on Saturday mornings to get my weekly groceries, opening Apple Maps (yes, don’t judge me) suggest me the location I usually go at the same time. So why can’t my music app figure out that I’m not trying to become a full-time zen master?

As someone who writes code for a living, I understand that implementing such features isn’t as simple as flipping a switch. Algorithms are complex beasts, fed by massive amounts of data and designed to find patterns that even we might not notice. But that’s precisely why I believe this is possible. We have machine learning models that can predict user behavior with uncanny accuracy. Incorporating an additional layer of time-based context could refine these predictions even further.

And one last problem which is why i wanted to write this post even in the first place. Why the Sleep category isn’t on the top of the list of categories at nights? In December, I see Christmass category on top, why not having time-related ones in the right place too? At nights when I want to change to another playlist I have to scroll to find it. When? At 3AM! Why?

The Human Element

There’s also a psychological aspect to consider. Music is deeply personal and often tied to specific moods or activities. By not accounting for the context in which music is played, Spotify risks alienating users who find their recommendations no longer align with their preferences. It’s like if a bookstore started recommending only cookbooks to someone who bought a recipe book as a gift once. Useful in that moment, perhaps, but not reflective of their true interests.

Moreover, the current system doesn’t account for shared accounts or devices. What if you’re playing sleep music for your baby? Should your “Discover Weekly” now be filled with lullabies and nursery rhymes? Without contextual awareness, the algorithm lacks the nuance to make these distinctions.

Potential Solutions

So what can be done? Here are a few ideas:

Time-Based Weighting: Adjust the algorithm to give less weight to songs played during typical sleep hours (e.g., 10 PM to 6 AM).
Activity Tags: Allow users to tag listening sessions with activities like “sleep,” “workout,” or “study,” helping the algorithm understand the context.
Profile Customization: Offer settings where users can choose which types of listening should influence their recommendations.
Separate Profiles or Modes: Introduce different modes within the app, such as a “Sleep Mode,” where the music played doesn’t affect the main recommendation engine.
Order of categories: Put the Sleep category at the top of categories list if it’s after 8pm.

So here’s my open letter to Spotify: Let’s make our relationship even better. I love you for your vast library, your intuitive UI, and your knack for introducing me to my next favorite artist. But I need you to understand that the lullabies I play at 2 AM aren’t a cry for more whale songs in my daily mix. Let’s work together to keep our rhythms in sync.

And to my fellow insomniacs and music lovers: Keep searching for those perfect tracks that make your day (or night) a little better.