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Towards Recommender System Optimization: Our Data Tool for Algorithmic Optimization on Spotify [Part 1]
Music Tomorrowmusic-tomorrow.com![Thumbnail of Towards Recommender System Optimization: Our Data Tool for Algorithmic Optimization on Spotify [Part 1]](https://uploads-ssl.webflow.com/6206e1343aa2f122195717f8/6310b1a1447a22ac785a50ae_alina-grubnyak-ZiQkhI7417A-unsplash%20(1).jpg)
2020 was the first year when streaming services overtook "family and friends" as the primary channel for music discovery, with over 62% of music listeners in the US naming DSPs among their top discovery sources.
Music Tomorrow • Towards Recommender System Optimization: Our Data Tool for Algorithmic Optimization on Spotify [Part 1]
Spotify, for example, has invested heavily in its own curation services — both algorithmic and human — after finding that many of its listeners were baffled by superabundance, burdened by excessive choice and uninterested in charting their own paths through the digital wilderness.
Rogers Brubaker • Hyperconnected Culture and Its Discontents
In a way, recommender systems have become some of the most important opinion leaders in the industry. The same way a recommendation from a trusted friend can go a long way — compared to, let's say, an ad you see on Instagram — a recommendation from a "trusted" algorithm brings about a sort of post-social proof.
Music Tomorrow • Towards Recommender System Optimization: Our Data Tool for Algorithmic Optimization on Spotify [Part 1]
