For millions of Spotify users, the "Wrapped" feature—which crunches the numbers on their annual listening habits—is a highlight of every year's end, ever since it debuted in 2015. NPR once broke down exactly why our brains find the feature so "irresistible," while Cosmopolitan last year declared that sharing Wrapped screenshots of top artists and songs had by now become "the ultimate status symbol" for tens of millions of music fans.
It's no surprise then that, after a decade, some Spotify users who are especially eager to see Wrapped evolve are no longer willing to wait to see if Spotify will ever deliver the more creative streaming insights they crave.
With the help of AI, these users expect that their data can be more quickly analyzed to potentially uncover overlooked or never-considered patterns that could offer even more insights into what their listening habits say about them.
Imagine, for example, accessing a music recap that encapsulates a user's full listening history—not just their top songs and artists. With that unlocked, users could track emotional patterns, analyzing how their music tastes reflected their moods over time and perhaps helping them adjust their listening habits to better cope with stress or major life events. And for users particularly intrigued by their own data, there's even the potential to use AI to cross data streams from different platforms and perhaps understand even more about how their music choices impact their lives and tastes more broadly.
Likely just as appealing as gleaning deeper personal insights, though, users could also potentially build AI tools to compare listening habits with their friends. That could lead to nearly endless fun for the most invested music fans, where AI could be tapped to assess all kinds of random data points, like whose breakup playlists are more intense or who really spends the most time listening to a shared favorite artist.