Have you ever wondered why Spotify can recommend the songs you actually like? How does Spotify Algorithm works and find these great soundtracks from the corners of the massive pile of music?

If yes, then this article is just for you. In this article, I will tell you about how the Spotify Algorithm actually works. This article is based on educated guesses and my analysis of Spotify’s song recommendations and rankings.

You will also learn about How Spotify identify the type of songs their listeners like. Let’s get right into it.

How does the Spotify Algorithm works?

The Workflow of the Spotify algorithm can be divided into three steps – Identification, Monitoring, and Discovery.

With the help of these 3 steps, Spotify is able to learn about the individual preferences, soundtrack’s character, and ins and outs of the listener’s behavior.

Now let us look at each step of Spotify’s Algorithm one by one in detail.

Identification

The identification system helps Spotify identify the individual as well as mixed audio files(samples, loops, acapella, etc). It can not only differentiate the songs based on Pitch and Tempo, but also the amount of compression, distortion, Filter, Tonal balance, and other important audio effects.

The identification system can identify the long as well as the short samples(as small as 1 second). It can also analyze the Chords used in a song.

However, this is just the tip of the iceberg.  Spotify goes beyond identifying the songs and also works on the individual streams in all derivative soundtracks(Remix, covers, Instrumentals, etc).

From the listener’s and artist’s perspective, the identification system can be divided into 3 parts –

Monitoring

Spotify keeps track of the music streams, downloads, and mentions worldwide on all blogs, websites, charts, and radio stations. This helps Spotify to keep up with the trending genres, styles, and soundtracks.  At the same time, it also keeps track of the usage of copyright-protected soundtracks and their use throughout the internet.

Another important job of the Spotify Algorithm’s Monitoring system is to track the listening habits of people across the globe. It helps Spotify keep track of real-time trends; both international and regional. It also helps them create alerts for the listeners.

Discovery

The final step of Spotify Algorithom’s workflow is Discovery. Spotify Discovery helps the algorithm understand the music taste of its listeners. Based on the user’s search, streams, and behavior on the Spotify player, the algorithm learns about the music interests of its user.

But the function is not limited to this. Spotify algorithm’s  Discovery function is also responsible for analyzing the listening habits of people around the world as a whole. This includes people’s opinions about the soundtracks. Based on the listening habit of people around the world, Spotify can learn whether a soundtrack is good or not.

How does Spotify Recommendation Algorithm  work?

Spotify uses the Sequential recommendation model to recommend new songs, playlists, and artists based on the previous behavior of the user.  The Spotify recommendation depends on the following factors-

1. Danceability
2. Acousticness
3. Energy
4. Popularity
5. Tempo
6. Valence
7. Lyrics

Let’s look at each of them one by one. Remember that the recommendation is based on user behavior.

Danceability

Just like the name suggests, Danceability accounts for how good the soundtrack is for dancing. For example, an Electronic Dance Music Record will have higher Danceability than a Cinematic composition. If a person often searches for EDM songs or artists, he will get more songs related to Dance music in his or her recommendation.

Acousticness

This factor accounts for acoustic the song is. To be more precise, if the song elements are real instrument recordings(Guitar, Acoustic Drums, etc) or made by electronic means(Synths). Genres like Country, Jazz, and Rock have more acousticness than EDM music.

Energy

The Soundtrack’s Energy depends on Harmonic content, Dynamic range, Distortion amount, Loudness, and other similar factors. A Dubstep soundtrack will have more energy than a Jazz Piece. Similarly, an Unplugged song will have less energy than a Metal record.

Popularity

Based on the listener’s feedback on a track from around the world, Spotify can determine the popularity of a soundtrack and recommend them to listeners who like the same kind of music.

The popularity factors work for Global as well as Local/Regional demographic. So if you are from India and love Hindi music, it will automatically recommend popular and trending Hindi music.

Tempo

Tempo is the speed of a soundtrack. It determines how fast or slow a song is. Spotify Algorithm can recommend songs based on what kind of temp the listener likes. It can be slow, mid, or high tempo.

Genres like Drum and Bass have a high tempo, Chill out generally has a low tempo while ambient music is at a low tempo.

Valence

This is probably the most important factor in Spotify Algorithm’s recommendation process. Valance determines the mood of a song. It can differentiate between happy, sad, uplifting, and other moods of soundtracks. Based on the user’s preferences and behavior, it can recommend the song that fits the listener’s mood.

Lyrics

This factor is indirectly connected to Valence. The algorithm is AI trained to capture the mood of a soundtrack based on its lyrics. Furthermore, it is a better way to predict the mood of a soundtrack accurately.

By comparing the lyrics with acousticness, the data can be further refined.

Monstra – Spotify’s New Music Recommendation Engine

In 2022, Spotify released a research paper. It specifically talked about their new Song recommendation engine Mostra; short for Multi-objective Set Transformer. This is Spotify’s next-generation Song recommendation system.

So what is Monstra? According to the Official Source Blog of Spotify, “Monstra combines Transformer Encoders with a Novel beam search algorithm. This is a Neural network that recommends the next song based on user satisfaction.”

Mostra recommends songs based on two major factors

1. User Satisfaction
2. Creator’s Objectives

Objectives of Spotify’s Music Recommendation Engine

There are 4 main objectives behind Spotify’s Music Recommendation Engine

1. SAT
2. Discovery
3. Exposure
4. Boost

Here is a brief intro to each of them…

• SAT determines whether the user has listened to the entire song or not.
• Discovery records whether the user is listening to the song or artist for the first time or not. This helps users find fresh music and discover new artists.
• Exposure determines if the song user is listening to belongs to an emerging artist or not. and finally
• Boost determines whether the song qualifies for boosting by Spotify through means such as playlists, recommendations, etc. It also determines if a song belongs to any trend or honors a group of artists.

How does Monstra works?

Monstra follows these systematic steps to determine the next recommendation for its users.

1. User data is encoded and fed into Transformer based encoder. This encoder analyzes the score of the song.
2. Each song is further analyzed based on the artist and platform-centric objectives.
3. The song which has the closest score to the objective is set as the recommendation.

Results of Monstra

Monstra; the new dynamic recommendation engine of Spotify is much more efficient. It is not only creator centric but also recommends the music that listeners actually like. This system can be applied to other parts of Spotify as well. And Spotify’s system engineers can tune the Engine at any time.

How can artists use the Spotify Algorithm for Music Marketing?

Now that you understood how the Spotify algorithm works, how can you use it in your favor to promote music? To take maximum benefits of the Spotify Algorithm, you should focus on the quality of music, e-mail outreach, Release Schedule, and Playlist placement.

Build an email list of your fans and followers, send regular emails promoting the song, and get as many pre-saves and saves as possible.

Another great Spotify music marketing tip is to submit the song to as many quality playlists as you can. Scrape the internet database to search for good playlists. The Spotify playlist curators need good music as much as artists need placement.

Try to increase the average listening time of your soundtrack. Releasing an extended, original, and instrumental version can further push your catalog.

The Takeaways

After reading this article, you must have got a broad idea about How the Spotify algorithm works, what are its necessary components, and what is Monstra. We also discucced a few points to promote music on Spotify. At this point, if you have any questions or want to add some extra information to the article, feel free to write in the comment below. Thanks for Reading!