This is how the Spotify algorithm recommends new music

If you use Spotify, there's a good chance you have an opinion on the recommendation algorithm. I like it quite a bit, but I've noticed a significant number of repeat recommendations, especially for music I've listened to many times before. As it turns out, Spotify has actually laid out how its recommendation algorithm works, which might help you know too.

This is how Spotify's recommendation algorithm works

There is a lot of machine learning

Spotify has laid out the basics of how its recommendation algorithm works, and these are the technical details to break down this simplified information into what it is Strictly speaking means. These are the three pillars of recommendation Spotify uses:

• Collaborative filtering: This model suggests content based on similarities between users and their behavior. If two users listen to similar songs, Spotify may recommend additional songs that one user likes to the other. Collaborative filtering is great when data is available about multiple users with common preferences.
• Content-based filtering: This model recommends songs based on the characteristics of the content itself. Spotify categorizes songs based on metadata (e.g. genre, tempo, mood) and may use Natural Language Processing (NLP) to analyze lyrics or external descriptions. If a user often listens to upbeat pop songs, content-based filtering can suggest similar-sounding pop songs.
• Deep learning models/neural networks: Spotify uses neural networks to identify complex patterns in user data and content features for personalized playlists like Discover Weekly or Release Radar. Recurrent neural networks (RNNs) are often used in sequence-based recommendations to predict what a user wants to hear next based on their listening history.

The first is a very common strategy that is also used by other streaming services, notably Netflix. To give an example, if one user enjoys the same shows as another, Netflix will recommend the first person the same shows that the other person enjoys. Additionally, Spotify also looks for certain characteristics that we know from the company's annual Unwrapped event, which it tracks much of data about the music shared on the service. You can even search for parameters like “danceability” using the Spotify API.

Spotify also uses similar techniques when searching. Spotify says if many users searching for something interact with a particular result, this will inform the results of future searches for future users. The company's neural networks also create your “taste profile,” and actions like searching, listening, skipping, or saving to your library tell Spotify what you like and don't like.

Finally, Discovery Mode allows artists and labels to highlight specific songs for better visibility and basically prioritize those tracks in the recommendation algorithm. However, this is not a guarantee of placement; Spotify continues to ensure that all promoted content matches your taste profile and interaction patterns. Of course, if a song doesn't resonate with listeners in Discovery Mode, Spotify's algorithm will downgrade it. This works in the same way as regular targeted advertising, where you will only be shown content that matches your interests.

How to influence Spotify's algorithm?

Spotify provides you with some tools for this

If you want to guide your recommendations, you can give Spotify signals about your preferences:

• Exclude from your flavor profile: You can exclude certain playlists from influencing your taste profile, helping Spotify understand that these particular listening habits do not necessarily reflect your overall musical tastes.
• Mark songs as “Not Interested”: Actively flagging a song or artist as not interested reduces the likelihood of similar content appearing in your recommendations, giving you more control over what you see.
• Explicit content filter: If you'd rather avoid explicit content, Spotify's explicit filter will block it and exclude it from your recommendations entirely.

Basically, Spotify's recommendation algorithms work in the same way you would expect any recommendation algorithm to work. Use the tools the service makes available to you and you can change how it recommends titles to you.

Spotify's algorithm is more than just a playlist generator, it's a music discovery service that can help you find new artists and songs that fit your listening profile. Of course not everything will suit you, but I know that it has helped me find music and discover new artists that I would never have found otherwise.