The Data & Design of Spotify Wrapped

Since 2016, the release of Spotify Wrapped has become a hallmark of the holiday season as the internet is flooded by users sharing their data. For those unfamiliar with the campaign, Spotify Wrapped supplies users with a report of their listening habits from the past year, including insights such as their most listened to songs, the total number of minutes they used Spotify, or whether they were amongst an artist’s top listeners. The immensely popular campaign has become a cultural phenomenon with some users even altering their listening habits in the latter half of the year in an attempt to skew their data & appear “cool”.

How Spotify Uses Data for Wrapped

Through listening, liking, creating playlists, and essentially any general use of the service, subscribers provide Spotify with a myriad of data on their preferences. So much and such detailed data in fact, that in 2018 it was reported that the Bank of England was analysing Spotify data to appraise the general mood and mindset of the United Kingdom.

For logistical reasons, only data from user’s activities between 1 January and 31 October is included, meaning that Wrapped is not actually representative of a user’s behaviour in a calendar year. Through the use of algorithms and artificial intelligence (AI) Spotify is able to create customised graphics for each user based upon their data. Spotify’s collection and use of user data is not a Wrapped-exclusive phenomenon, in fact, their use of user data & AI extends throughout the calendar year and aid in the creation many popular features of the service, particularly customised playlists, which are tailored according to data harvested from a user’s profile.

Central to this customisation is Spotify’s algorithmic recommender system, which employs three models: including collaborative filtering, Natural Language Processing (NLP), and audio models.

  1. Collaborative filtering helps Spotify identify other users with similar tastes based upon your behaviours.
  2. Natural language processing breakdown song lyrics, playlists titles, and more into text documents and analyses lyrical patterns.
  3. Audio models which identify different characteristics of songs, such as tempo or pitch. The songs are then added to playlists where feedback from users can provide additional data on the songs.

These models help Spotify produce playlists, including “Discover Weekly” by identifying users with similar preferences, comparing their data, and compiling a playlist of new songs each week based on the preferences of their musical “neighbours”. The data collected from users and put through Spotify’s recommender system is also used to inform playlists publicly released by Spotify, like “Today’s Top Hits”.

In the case of Wrapped, the recommender system allowed for the creation of user’s “Your Missed Hits” feature which functions similarly to Discover Weekly, providing users with songs they may have missed and will likely enjoy from the past year.

Spotify’s ability to personalise is key to their success: as Ferrer states “consumer interest in Wrapped isn’t just about the data itself, but the way that Spotify personalises and presents this data to them. This is hyper-personalization at its finest, as each user is served up a story where they are the main character.”

The Perfect Marriage of Data & Design

While the yearly wrap-ups of rivals such as Apple Music often fall flat, Spotify’s combination of data and creativity have capitulated Wrapped to success year after year. What sets Wrapped apart from the yearly reviews of competitor’s is not the data itself but the user-experience it provides through data insights and visualisations.

As Galant states “Spotify Wrapped is a stellar example of how powerful user-experience (UX) design can create intrigue and drive engagement around something that would otherwise go overlooked” as it “gives its data right back to its users—but the way the data is presented is what gets people excited in a similar way that a personality test might.”

Behind the creative of Spotify Wrapped is Marie Rönn, the Global Group Creative Director at Spotify, and her team which includes data scientists and engineers, designers, audio editors, and more. Her team starts working on the year’s Wrapped in early spring, studying data, trends, and the general climate of the year in order to develop ideas and seek inspiration. Each year they develop new “data stories” such as 2022’s Audio Day & Listening Personalities, 2019’s Decade Wrapped, or 2018’s Horoscopes.

The combination of familiar highly anticipated insights and evolving data stories keep Spotify’s 456 million users intrigued and differentiates them from rivals. In fact, in the lead up to the new year, the number of Spotify users actually increases, demonstrating the value of seamless UX design and data insights.

Data scientists are an integral part of Spotify Wrapped success, developing the data visualisation for which it is renowned. While careers in data often get the reputation of being math-heavy, Spotify’s design process for Wrapped demonstrates the immense creative potential of a career in data.

Additionally, the success of Spotify Wrapped against competitors also shows the importance of strategic and exciting UX design. If you’re interested in a career in user experience or you’re looking to strengthen your existing skills, check out our new short course UX Design Fundamentals where you can master the essentials of UX design!


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