From Rainy Days to Real Vibes: Rethinking Spotify's 'Daylist'

A UX Perspective 🎵

I’ve always been an avid music lover. Whether it’s searching for songs to play on the guitar, creating custom playlists for an upcoming event, or simply listening to music while designing, I’m constantly trying to find better song recommendations. So, I gave Spotify's "Daylist" a whirl, hoping for a personalized vibe to kick off my Monday.

To my surprise (and total amusement), I got a playlist called "Heartbroken Rainy Day Monday." Not exactly the mood lifter I was aiming for. It seems Spotify’s attempt at customization, while earnest, is still missing the mark for creating truly personalized experiences.

Sure, I listen to rain sounds to sleep, but I didn’t expect my playlist to turn into a weather forecast! The algorithm took my nighttime rain sounds and assumed I wanted to drown in melancholy on a Monday morning. This highlights a key issue in user experience: understanding context and intent.

From a UX perspective, effective personalization requires more than just aggregating user data. It demands an understanding of the user’s context and current needs. Here’s where Spotify’s "Daylist" stumbles. The approach appears to be based on a surface-level interpretation of user habits without diving deeper into the "why" behind those habits.

In my Vybe mobile app streaming service concept, I explored a different approach to creating personalized playlists. Imagine this: instead of a static algorithm making assumptions about your mood, you start by answering a few quick questions about how you’re feeling. Are you energized, mellow, or somewhere in between? What’s your current activity—working, relaxing, or exercising?

Then, Vybe presents you with short samples of songs to swipe left or right on, similar to a dating app. This method allows users to interact with the AI, providing immediate feedback and refining the playlist in real-time. The longer you swipe, the more the AI hones in on your exact musical tastes.

This approach leverages several key UX principles:

1. User Control and Freedom: By allowing users to interact with song choices, Vybe puts the user in control. This reduces frustration and increases satisfaction, as users can directly influence their listening experience.

2. Flexibility and Efficiency: Quick preliminary questions streamline the customization process, making it efficient without sacrificing depth. The swiping mechanism is flexible, allowing for continuous refinement of the playlist based on immediate feedback.

3. Recognition Over Recall: Vybe’s design minimizes the need for users to recall their preferences or previously liked songs. Instead, it presents options that users can easily recognize and respond to, simplifying the decision-making process.

4. Contextual Awareness: By considering the user’s current mood and activity, Vybe ensures that the playlist is relevant to the user’s present context. This prevents mismatches like the "Heartbroken Rainy Day Monday" scenario.

5. Engagement and Enjoyment: The interactive nature of swiping makes the customization process enjoyable. It transforms the creation of a playlist into an engaging activity, enhancing the overall user experience.

There’s no hate from me when it comes to Spotify itself; it’s one of my favorite and top-used applications on my phone. It’s clear that they take direct initiatives to constantly grow and improve their user experience.

Spotify’s "Daylist" is a step in the right direction for personalized music streaming, but it needs to evolve. Taking inspiration from Vybe, integrating user control and contextual awareness could create a more nuanced and satisfying listening experience. Let’s move away from rainy heartbreak and towards a playlist that truly matches our vibe.

Update: Spotify is currently rolling out an AI-powered playlist option designed to tackle some of the key issues I’ve discussed. Although this feature is still in beta testing, it shows promising potential. While it may not yet fully match the ease of swiping right or left to give real-time feedback, it represents a significant step forward in creating more personalized and context-aware listening experiences. I'm excited to see how this new feature evolves.