Collaborative filtering examines and compares an individual’s behavior to other people’s taste.Spotify combined three different models to analyze the similarity of songs: Their strategy changed over time, but one of the algorithms that Spotify used to create the Discover Weekly playlists was a mix of the best strategies used by their competitors. Spotify, however, developed an engine that used three different recommendation models. I discuss the details of this approach later in this chapter. Last.Fm worked on yet another approach called collaborative filtering to identify songs that users might like. They listened to each song and added descriptive tags like ‘folk,’ ‘slow,’ ‘rap,’ or ‘love.’ With that information, Pandora created playlists that had similar songs, i.e., songs with related tags. Instead, the music experts manually tagged attributes for each song.
Like Songza, Pandora was one of the first players in the music streaming business, but they used a different approach from curating playlists. Songza built a respectable user base, but the major drawback of their approach was that it did not take into account the nuance of each listener’s individual taste of music.
#Songza listen later manual#
Manual curation meant that a team of music experts put together playlists by hand that they thought sounded good. In the early 2000s, Songza developed a product for automating music curation. Many people love and rely on this service to increase their exposure to new music. This custom playlist contains around 30 songs that they have never listened to before but will probably enjoy. Every Monday, over 100 million Spotify users receive a new playlist, Discover Weekly, tailored to them. Spotify is a prime example of this technology. With music, a song from the 1960s could be as relevant to someone today as the latest Ke$ha song.Īs in other fields, the music industry also benefits from Machine Learning, providing every listener with a personalized playlist. Music isn’t like news, where it’s what happened five minutes ago or even 10 seconds ago that matters. Users can also give new songs and playlists "thumbs up" or "thumbs down" to help the app learn preferences and provide improved recommendations, tailoring the experience to be more in line with their personal tastes.Behind the models that power Spotify’s Discover Weekly Searching for potentially interesting music in a favorite genre or looking for completely new music are both great ways to exercise the Self-Awareness thinking skill. Users can search for music relevant to their current mood or seek out new and unfamiliar experiences in an effort to alter their mood. Thinking about and understanding personal emotions and feelings is an excellent way to practice Self-Awareness, and the app, by design, encourages such activity. Songza is designed to tailor music listening to a users current activities and moods. Understanding our own actions, thoughts and feelings. Learning to appreciate new forms of music can be an excellent way to introduce users to the base components of the Flexibility thinking skill. Because the app allows only a limited number of "skips" per listening session, users must approach Songza with an open mind toward new and unfamiliar artists, albums, and songs. Users can also learn to be more flexible in their listening preferences as the app recommends an enormous variety of new music. Users will find its playlists designed for listening while exercising to be upbeat and energetic, while those designed for finishing schoolwork or sitting at the office induce a state of focus and concentration. The app is designed to present users with unique music suggestions tailored for any time of day, mood, or activity. THIS APP IS GOOD FOR KIDS WHO NEED HELP WITH: FlexibilityĪdapting and adjusting to changing conditions and expectations.