What might be the perfect tune for dozing in the sun, for running along a stormy beach or, perhaps, the soundtrack to the first flush of true love?
The more data Spotify can collect on listener habits, the better the recommendations its algorithms can produce. As well as music, motion, heart rate, and temperature, Spotify could start to monitor sleep patterns, according to Donovan Sung , Spotify’s product manager for discovery and recommendations.
"Maybe with motion sensors in phones, we can start guessing things whether users are running, biking or driving? Maybe the phone has a temperature sensor, or a heart rate sensor, we could guess whether the user is tense..." said Sung, talking to TechRadar.
Sung explained that information provided by sensors could be used to automatically generate playlists based on activities such as workouts, driving, sleeping or late-night working, without user interaction.
The service could automatically start playing pumping music when it is time to go for a run or peaceful ambient tracks for when sleep is required.
“The more we know about you, the better the [recommendation] engine can be,” said Sung, who warned that overloading listeners with choice provided a poor user experience, and that a fine balance must be struck between quantity and quality of recommendations.
Human editors, algorithms and social data
Spotify’s recommendation engine is currently powered by a combination of human editors, algorithms, social data and previous listening history, which provide personal recommendations for users of artists, albums and tracks. These also inform Spotify’s shuffle play feature, which it unveiled in December 2013 and is continuing to improve.
“Nearly half of mobile listening, if not more, is people listening to their own curated playlists," said Daniel Ek, Spotify’s founder at the time. "With shuffle play, you can now play any of your playlists for free. Spotify's new mobile experience is music for anyone and the best experience and access in the history of music.”
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image: © Sara Alfred