For everyone knows that the information poured on the network serves many programs, applications, social platforms have a complete profile about us and our digital behavior. Spotify is no slouch and knows a lot about you for the music you hear.

Music is one of the most defining of every human being hobbies, so the favorite repertoire of songs can talk to Spotify both age or place of residence , as other deeper and more complex as features political preferences, personality or the degree of sociability. 

Thus, the popular broadcast service is able to analyze all the activity of its users – what music they listen to , when, what breeding patterns continue, which lists created – to know their tastes and, from there, start recommending .

On the basis of that musical taste is unique and non – transferable, experts platform have uncovered valuable clues about human nature from the consumption of the songs.  “Of all the things we can measure technology, music is the more representative of our personality “ , explained to Efe agency responsible scientific data Spotify, Brian Whitman.

Customizing the user experience on Spotify

Experts in artificial intelligence, scientists, musicians and professionals sociology and psychology work to understand what does music mean to each user and thus to develop a customized product, as evidenced by recent features of Spotify as Radar .

“We are able to discover, with a high degree of reliability, things of you: of course your age and where you live, but also nuances of your character , “ says Whitman.

Among other things, following the extracted data of musical taste, analysts can know if a user is sociable, adventurous and introspective or the type of people they would be compatible.  Also, their political preferences.

Knowledge of the user, with limits

“Music partially serves to express who we are, but we will never be able to understand the complexity of a person from the limited view we form through his musical activity. We tried to make assumptions, although not always accurate “concluded the product manager of Spotify, Ajay.

On the platform no two users among its hundred million share identical tastes .Nor the same views about what song is happy, sad or relaxing. In order to categorize the best way its catalog of 30 million songs,  Spotify mathematically analyze their songs around the tempo or rhythm, driving on the web and social networks to study what is written about music and organizes meetings with users know their motivations. 

The next frontier, according to its chief scientist, is that the service “understands people as well as understand the music” . It is a complex process since  identity and musical activity often are not aligned  because in many cases it is shared in networks a type of music that is not really listening.

“We have seen that there are songs that people listen, but never shared because they want to be associated with them. And the opposite: very few compositions published in play but many networks. It ‘s fascinating, we want to understand what underlies this behavior and make the algorithm is able to understand whether this music really likes “ , says Kalia.

The emotional connection to music is evident and the Scandinavian company knows, but if they find a utopia determine if a song is sad or happy, much more being able to guess the mood of the listener and what you want.

Rocio Guerrero, head of the editorial team that produces music charts, draws two main conclusions: `on the one hand,  we are very tolerant of music and are open to discovery , and on the other, we like to bring emotions to the limit.

A future in the service of emotions

In the future, the service seeks to respond satisfactorily to requests such as :“Spotify, I’m depressed, animate me” or “I had a bad day, put me songs that relax me.” To do this, you must know what music achieves these effects in everyone. For now, this path of trial and error has its flag on the custom lists weekly, available every Monday discovery. 

It is likely that seventy percent of what he hears a user is similar to the other , “but what about thirty percent that makes you unique? Instead of focusing on the cliches, can we detect these rarities and give you something that only makes sense to you? In this we are “ , concludes Kalia.


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