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Introducing Spotify Jam: Collaborate with 32 users on real-time playlists

Spotify has introduced a new tool called ‘Jam’ that allows up to 32 users to collaboratively build a playlist in real-time. This feature expands on Spotify’s existing Collaborative Playlist and Blend options, which enable users to invite friends to add songs to existing playlists or generate a shared playlist for two users based on their preferences. Spotify reported that users have created over 45 million Blends and collectively spent more than 200 million hours listening to Collaborative Playlists. With Jam, Premium users can invite others to contribute through a shared queue, enhancing the group listening experience.

Hosts of Jam playlists can invite a mix of Free and Premium users, regardless of their location. Participants on the same shared Wi-Fi network will receive prompts to join the Jam, where they can add songs to the queue, view contributor details, and receive personalized recommendations. Only the host can manage the playlist by adjusting the track order and removing songs that don’t align with the collective vibe. This new feature follows Spotify’s beta release of Group Session in 2020, which offers Premium users worldwide the ability to synchronize their listening experience. Jam joins Spotify’s suite of personalized playlists, including Daylist, Discover Weekly, and On Repeat playlists.

Spotify continues to enhance its social features to maintain its dominance in the global streaming market and attract a wider user base. The company has seen a surge in Premium subscribers, reaching a total of 220 million by the end of the second quarter. Spotify’s revenue from Premium subscriptions in Q2 increased by 14% compared to the previous year. Additionally, leaked code suggests that Spotify may introduce a premium plan called ‘Supremium,’ offering lossless music and AI playlist creation for a higher monthly subscription price. Moreover, Spotify is piloting an AI-powered Voice Translation tool for its podcasts, allowing podcasts to be translated into additional languages using the podcaster’s own voice.

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