SPOTIFY

Oskar Stål, Spotify’s vice president of personalization, explains how it works – Spotify


Spotify’s music lovers are eagerly anticipating for Monday and Friday who are looking to unveil new artists. Every Monday, Discover Weekly, a playlist that lets listeners like tracks based on their past listening history, is updated. Friday is the day of the release radar, when the playlist is refreshed with new songs from the user’s favorite artists. And more and more personalization is happening every day on SpotFi. Our editors curate and create playlist users across playlists.

In fact, personalization starts right on the home page, after a while the new user downloads and signs up for Spotify. New users are being asked to select a few artists of their choice. From that moment on, the app started to spin the creators, based on what the audience might like. “But it’s responsible for a small part of how we personalize Spotify’s listening experience,” said Spotify’s vice president of personalization. Oscar stall, In an interview with For the record.

How personalization came to life

Personalization Hall sounds like this: it ensures that the content you get on Spotify is based on your favorite audio. This is now considered the key to the Spotify experience – but Spotify has not always focused there. Spotify was originally created 15 years ago to act as a library, where you can play the songs you’re interested in and you already know. But over time, our engineers realized that “the more you discover, the more you enjoy Spotify and most people don’t have time to discover themselves,” Oscar said.

“Maybe you’re a 46-year-old dad with three kids and you don’t have time to discover music by yourself,” Oscar joked, pointing to himself, “or a student looking for inspiration. When you serve something and it’s your choice and you It will be a combination of whatever you like, then it will be most helpful. Then you will stay for more. “

Personalization, he explains, was a powerful experience for audiences who didn’t have the time or knowledge to create endless unique playlists for every dinner party or road trip. It opens up discovery on a larger scale, enabling the discovery of hundreds of artists each year. And most importantly, personalization helps create a better app experience because it ensures that people want to stay in the app – but not spend all their time there. The method of spotting is to ensure the audience has a “full content food”.

“If we really want you to stay in the app for another three minutes, we’ll play your favorite song,” Oscar explained. “All we have to do is play your favorite 20 songs in a loop. But this means that you are not discovering anything, and you will eventually get tired and bored with the audio experience.

The Spotify app manages a number of personalization features within the app so that listeners can enjoy Discover Weekly and the like outside of classics. Leave the radar. Earlier this year, we made our debut Spotify Mix A listener will love or like a style, artist, or music arranged with the era. Just last month, we introduced Blend, Which combines two audience taste profiles, creates a playlist that combines both of their favorites and allows them to share their results on social media. And most recently, we launched Advanced Playlists, a feature users can toggle on or off that allows Spotify to recommend new songs that may be compatible with the user’s custom-made playlists.

This is in addition to what we call our “algorithmic” playlists: a set of songs that our editors put together for specific moods or moments that are also suitable for individual users. “Song to sing in the car It may not sound personal, but it is, “said Oscar.” Everyone sees a classification that fits that classification, but it is also consistent with what they like to hear. In fact, there is only one Spotify experience. There are another 365 million different experiences – for each user – that are deeply personalized for their wants and needs.

How does personalization actually work?

The answer is machine learning, a complex code-based system with thousands of inputs, all up to the recommendation of a song, which is done faster than the blink of an eye. But Oscar broke it:

“Imagine you and another person have the same taste in music. You have four top artists, but your fifth artist is different. We’ll take those two nearby matches and think, ‘Hmm, maybe everyone will like the other’s fifth artist’ Now imagine that the process is happening on a scale কেবল not just one-on-one, thousands, millions of connections and likes are instantly considered and always updated.Every day, half a trillion events, they search, listen or like, happen on Spotify, our Strengthens and manages machine learning systems.

As machine learning technology Spotify matures, with advances we only once dreamed of becoming a reality. This reality also affects where we can go with personalization and what we can serve to the audience. “The breakthrough in machine learning has really allowed us to rethink how it can help users discover new audio content. Although in many cases machine learning has focused on the solution to click immediately ou ‘you like this song. I offer you more of the same kind of music – we are now able to better understand the content and how listeners and producers relate to it.

The future of personalization on Spotify

Podcasts, in particular, create a significant opportunity due to user input: it takes a little longer to decide if you like a particular show or episode – the song takes much longer than 20 seconds but as Oscar mentioned, podcasts on Spotify We already had a great start to discovering: “We’re investing heavily in developing the world’s best-recommended algorithms for power connections between podcasters and listeners. We’ve already had a really good system for recommending music for over 10 years, and it turns out that We can guess what kind of podcast the listener can enjoy based on the taste of their music.

The effects of personalization – and the potential to spread further. As much as personalization can be enjoyable and relevant to the audience, it is vital for producers who are trying to increase the number of fans. Spotify Machine Learning has been trained to identify artists, genres and even potential matches across the country.

“Personalization is really a two-way street,” Oscar said. “The insights we’ve gathered allow us to see if there can be a Finnish artist who has music that will be a hit in Latin America. And those Latin American audiences have the opportunity to bring that music through our personalization channel. Introduces what they may not have been able to discover on their own.

As Spotify didn’t start with personalization capabilities, listeners now expect, the story of personalization doesn’t end there either. “Personalization is essential to the listening experience,” Oscar reminds us. “What we’re really working to do is create a more holistic understanding of the audience by optimizing them for long-term satisfaction rather than short-term clicks, offering them a more fulfilling content diet. Listeners are on a journey of discovery, and we want to help them get the best experience as they discover millions of audio content on Spotify.



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