Why Spotify nudges you towards developing "better taste" in music?

The impact of Spotify on the music industry is undeniable. Their algorithms are reshaping how we engage with music, and as they continue to evolve, they will keep the world of music discovery endlessly enticing and delightfully surprising.

The question that often crosses my mind is, whether all the efforts towards developing more and more advanced recommendation system is to align with their vision? Which is to create a “cultural platform where professional creators can break free of their medium's constraints and where everyone can enjoy an immersive artistic experience that enables us to empathize with each other and to feel part of a greater whole”, or is it to keep up with their competitors who are anyways so far behind in this race of creating superior algorithms or there is no other way to survive in this market?

On diving deeper into the roots of it, I realized that maybe this is the only way to survive in the market. To understand this, we first need to get familiar with how their revenue gets distributed among artists. As per some articles I read which were updated in January 2022, Spotify primarily uses a pro-rata payment system to distribute its revenue among artists. Here's a general overview of how it works:

Spotify generates revenue through both premium subscriptions and advertising on its free tier. Premium subscribers contribute a monthly fee, while free users generate revenue through ads. Spotify pools all the revenue generated from subscriptions and ads into a single pot. The total revenue is then divided among rights holders based on their share of total streams on the platform during a specific period (usually a month).

Rights holders typically include record labels, distributors, and, indirectly, the artists themselves. Record labels and distributors take a percentage cut of the revenue before passing on the remaining amount to the artists. The percentage cut retained by labels can vary and is determined by the terms of the contracts between labels and artists. The remaining revenue is then distributed to artists based on their contractual agreements with labels or distributors.

It's essential to note that the exact payment structure can vary based on individual contracts between artists, record labels, and distributors. Some artists may negotiate more favorable terms, such as higher per-stream rates or a larger share of the revenue.

The Theory

The gist of this revenue distribution structure infers that if music industry remains traditional – where access to underrated artists is ladled with barriers and popular distasteful fast moving consumer good is portrayed as the only option, a significant portion of royalties will go to a small number of top-charting artists or in other words big record label companies.

And for a 40-billion-dollar company who provides streaming services, coming to favorable terms with big record label companies is way harder than dealing with an independent artist, purely on monetary basis. Record labels will always expect higher percentage of revenue because they function on margins, independent artists can be paid lesser in comparison to record labels and yet it can be a win-win scenario for both.

This is where diversification helps, introducing users to a wider variety of artists and genres on Spotify can have several potential benefits, including reducing content costs by paying lesser royalties to big record labels and music publishers. The process of achieving the same depends on 2 major formulas that Spotify sticks to.

The Magic of Personalization

Every magic often results from continual and meticulous efforts, Spotify’s algorithms or personalization formula sift through an extensive database of songs, analyzing their acoustic properties, genres, and subgenres. This examination of the musical DNA helps the algorithms identify songs that complement your tastes, introducing you to hidden gems and tracks you might not have discovered on your own.

A musical portrait is crafted for each end user through a complex and multifaceted process that is leveraged by a combination of user-generated data, user behavior, and advanced algorithms. Here are some factors involved in creating these portraits:

User registration and profiles, listening history, likes and dislikes, skip and repeat behavior, time and duration of listening, genre and artist diversity, social interactions, location and device data.

Once this wealth of data is collected, it's processed through complex algorithms. These algorithms can analyze the data to identify patterns, clusters of similar users, and associations between songs and genres. Machine learning models are often used to identify correlations between users with similar tastes and suggest music that these similar users have enjoyed.

The result is a continuously evolving musical portrait that reflects the user's unique preferences, habits, and moods. This portrait is the foundation for creating personalized playlists, recommendations, and radio stations that keep users engaged and delighted with the music they discover on platforms like Spotify.

However, the recommendations that Spotify shows are not always to maximize the user experience. ?Because even if a user listens to limited genres, given the variety that the world produces in music, a streaming service with all the available music always chooses the option where their benefits are maximized without hampering the user’s expected utility from the musical interaction.

Long-Tail Economics

In the "long-tail" model of economics, a substantial portion of revenue comes from niche or less-popular products (in this case, music). By facilitating the discovery and enjoyment of niche music, Spotify taps into this long-tail effect, generating revenue from a wide range of tracks. This can contribute to overall cost efficiency.

By exposing users to a wider range of artists and genres, Spotify can encourage users to explore music beyond mainstream and popular tracks. This diversification can lead to a more balanced distribution of streams across a variety of artists. Introducing users to lesser-known or niche artists can reduce the concentration of streams on a few high-profile musicians, which may help balance royalty payments.

Lesser-known and independent artists often rely on streaming revenue to support their careers. By promoting their music to a broader audience, Spotify also helps these artists gain recognition and increase their streaming numbers.

Eventually it is a win-win scenario for both the users and Spotify. Introducing users to diverse and lesser-known music can enhance their overall listening experience. Users who discover new and unique tracks are more likely to engage with the platform, leading to longer listening sessions, higher retention rates, and potentially increased subscription revenue.

Conclusion

It's important to note that while introducing users to a variety of artists and genres offer benefits, Spotify's approach must strike a balance between promoting independent and niche artists and delivering the popular music that many users seek. Spotify also needs to consider the preferences of its diverse user base.

Additionally, the effect on content costs and royalties can vary depending on user behavior and platform strategies. Achieving a balance that benefits both lesser-known artists and users while maintaining a sustainable business model is a complex challenge for streaming platforms like Spotify. Spotify's commitment to fostering independent and niche artists, as well as its long-term sustainability, remains a subject of interest and evolution within the music streaming industry.

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