Streaming services: Netflix and Spotify’s recommendation services
The video streaming service, Netflix, first integrated a new recommendation system into its platform at the beginning of 2016. The algorithm displays suggestions depending on each Netflix user’s personal taste in movies and series. These algorithms, however, don’t take demographic data into account, such as age and gender. It’s simply the collected data that is used to decide on which suggestions to display. When the user sets up their account, they are asked to reveal their favorite movies and series. Questions need to be answered such as 'what has the customer previously seen?' and 'how did they rate it?'. By comparing all customers based on their preferences and ratings, the platform can make accurate suggestions.
There used to be problems every time the service was introduced in a new country. This is because there was no previous data to calculate any recommendations from. The new algorithm works with transnational customer groups. In this context, country-specific and region-specific tendencies are still included.
The music streaming service, Spotify, has been working with personal recommendations for a long time. The service compiles a list of songs each week that potentially match the user’s taste. Your Daily Mix playlist is automatically created by algorithms.
These playlists are partly self-generated playlists from other users that the user creates themselves and partly Spotify attempting to build an accurate profile depending on the user’s tastes. The service works with extremely narrow genre definitions. A software is used additionally that analyzes articles and texts on blogs and magazines to classify artists as accurately as possible. The recommendation service also recognizes so-called genre anomalies, which do not fit into the overall profile because the user maybe decided to play the song on a whim. Spotify doesn’t include these songs in the personalized playlist.