How many paid subscribers does Spotify have? As of the first quarter of 2025, Spotify had 268 million premium subscribers worldwide, up from 239 million in the corresponding quarter of 2024. Spotify’s subscriber base has increased dramatically in the last few years and has more than doubled since early 2019. Spotify and competitors Spotify is a music streaming service originally founded in 2006 in Sweden. The platform can be used from various devices and allows users to browse through a catalogue of music licensed through multiple record labels, as well as creating and sharing playlists with other users. Additionally, listeners are able to enjoy music for free with advertisements or are also given the option to purchase a subscription to allow for unlimited ad-free music streaming. Spotify’s largest competitors are Pandora, a company that offers a similar service and remains popular in the United States, and Apple Music, which was launched in 2015. While Pandora was once among the highest-grossing music apps in the Apple App Store, recent rankings show that global services like QQ Music, NetEase Cloud Music, and YouTube Music now generate higher monthly revenues.Users are also able to register Spotify accounts using Facebook directly through the website using an app. This enables them to connect with other Facebook friends and explore their music tastes and playlists. Spotify is a popular source for keeping up-to-date with music, and the ability to enjoy Spotify anywhere at any time allows consumers to shape their music consumption around their lifestyles and preferences.

As of January 2025, Spotify has over 640 million monthly active users. Here is the full breakdown of Spotify users by year since 2015:

In the fourth quarter of 2024, the music streaming service Spotify reached an all-time high with 675 million active users worldwide. This marked an increase of around 12 percent in just one year. What is Spotify? Spotify is a music streaming service that offers digital audio content. Basic audio content can be accessed for free whereas premium user subscriptions enable users to access offline mobile content as well as listen to music without advertising. In the fourth quarter of 2024, the company reported 263 million paying subscribers. Launched in 2008, Spotify originated in Sweden before expanding to European markets and the United States in 2011. Spotify’s U.S. launch was strongly marketed through Facebook, with the music streaming app profiting from the social listening integration via social media. Part of Spotify’s appeal can be attributed to the user- and brand-curated playlists, which can be shared publicly or between friends. Fans may choose what to listen to based on their current mood or preference, and the ability to share such content provides an element of social connectivity ordinarily reserved for networking sites.

North American Spotify users spend the most time on the platform steaming an average of 140 minutes of content on the Spotify app daily.

Paying subscribers account for about half of Spotify’s monthly active users. This is the number of paying subscribers by year that Spotify has had since 2015.

34% of Spotify’s monthly active users live in Europe. That means that Spotify has 147.22 million users in the EU regions alone. Here’s the breakdown of regions that contribute the most users to Spotify:

In the first quarter of 2025, Spotify reported having ** percent of their total monthly active users (MAUs) located in Latin America, which translates to around ***** million MAUs in the region, up from around *** million a year earlier – an annual increase of ** percent. Overall, the region accounts for over one-fifth of Spotify’s MAUs worldwide.

29% of all Spotify users fall into the 25 to 34 age range. This is closely followed by 26% of users in the 18 to 24-year-old age.

By 2025, Spotify will have 100.6 million users, over twenty million more than the 78.5 million recorded in 2020. However, a gradual decline in Pandora's user base is anticipated to continue over the coming years, with the company losing two to three million active listeners per year.

Spotify and Pandora – more information Pandora

In 2018, Pandora was most popular among users aged 25 to 34 and users aged 55 or above, whereas adults in the 18 to 24-year-old age bracket was by far the company's weakest market segment. Pandora's user base may be flatlining compared to Spotify's, but Pandora’s revenue jumped from four million U.S. dollars to almost 1.5 billion in a decade, showing incredible and consistent growth during that time. Pandora generates most of its revenue from advertising, although has grown increasingly reliant on revenue from subscription services. Pandora was acquired by Sirius XM in February 2019 for 3.5 billion U.S. dollars.

Spotify In 2018, Spotify reported 5.2 billion euros in revenue, following a history of significant growth. Spotify was operating at a loss for years, but reported its first quarterly operating profit at the beginning of 2019. the company has placed a stronger focus on podcasts and will continue to do so according to industry experts and company reports, and is one of the most popular podcast providers in the United States.

Spotify has about 80 million individual tracks on the platform.

The latest Spotify statistics from the company’s annual report show that 69% of Spotify premium subscribers are located in Europe and North America.

According to the most recently available data, the average amount of time spent listening to Spotify by the platform’s active users was ** hours per month. The idea of spending more than an entire day per month streaming Spotify content might sound unbelievable, but internet usage is higher than ever and vastly supersedes time spent with radio, print media and even television. Streaming has become one of the most popular media activities in the world, and Spotify is the global market leader when it comes to digital music streaming. Spotify and the music marketSpotify dominates the global music streaming market and offers artists serious amounts of exposure, with some musicians garnering audiences of several million each month. The company’s user base has increased dramatically, even in the face of antitrust complaints and competition from Apple Music, as well as users expressing concern over how little Spotify pays its artists. In 2018, music streaming revenue amounted to *** billion U.S. dollars worldwide, more than six times the figure recorded for 2013. Whilst revenue growth has slowed, this is not the case when it comes to subscriber numbers, which in Spotify’s case have been increasing at a quarterly rate. Spotify reported ** million premium subscribers worldwide at the end of 2018, finishing the year with a flourish after regular growth and accumulating ** million more paid users in just twelve months. The company also commands more than ** percent of music streaming subscribers worldwide, outperforming both Apple Music and Amazon.

This dataset contains customer reviews and ratings for the Spotify application, collected directly from the Google Play Store. It offers insight into user experiences and satisfaction with one of the world's largest music streaming services, which serves over 422 million monthly active users [1]. The data provides a valuable resource for understanding public sentiment towards the application and identifying factors that contribute to user satisfaction or dissatisfaction [1]. The data was collected by scraping Spotify reviews from the Google Play Store [1].

Columns

• Time_submitted: Records the specific time and date when a review was submitted by a user [2].
• Review: Contains the full text of the user's review [2].
• Rating: Represents the numerical score given by the user, ranging from 1 to 5, indicating their satisfaction level [2].
• Total_thumbsup: Indicates how many other users found the particular review helpful [2].
• Reply: Shows any direct reply to the user's review, often from the application developer or support [2].

Distribution

The dataset comprises 61,594 rows (or records) of Spotify app reviews [2]. The data is typically available in a CSV file format [3]. Review ratings range from 1 to 5, with 22,095 reviews rated 4.80 - 5.00, and 17,653 reviews rated 1.00 - 1.20 [4]. The number of 'thumbs up' for reviews ranges from 0 to 8195, with the vast majority (61,378 reviews) having between 0 and 409.75 thumbs up [5].

Usage

This dataset is ideal for various analytical applications, including: * Sentiment analysis to gauge overall user sentiment towards the Spotify app [1]. * Identifying key themes and reasons behind 1-star and 5-star reviews to understand user satisfaction drivers and pain points [1]. * Analysing trends in user feedback over time. * Developing machine learning models for text classification or natural language processing (NLP). * Understanding the impact of app updates or changes on user perception.

Coverage

The dataset covers reviews submitted between 1st January 2022 and 9th July 2022 [2]. The reviews were collected globally from the Google Play Store [2, 6]. There are no specific demographic notes on data availability, as it is based on publicly available app store reviews.

License

CC-BY

Who Can Use It

• Data Scientists and Analysts: For conducting sentiment analysis, natural language processing, and building predictive models.
• Product Managers: To gain insights into user feedback, identify features that users appreciate or dislike, and inform product development decisions.
• Market Researchers: To understand consumer perception of streaming services and competitive analysis.
• Academic Researchers: For studies on user behaviour, app reviews, and digital product success.
• App Developers: To monitor user satisfaction and identify areas for improvement in their applications.

Dataset Name Suggestions

• Spotify App Reviews 2022 (Google Play Store)
• Google Play Store Spotify User Reviews
• Spotify Mobile App Ratings and Feedback
• Spotify User Sentiment Data
• Global Spotify App Reviews (Jan-Jul 2022)

Attributes

Original Data Source: Spotify App Reviews

This dataset was created using Spotify developer API. It consists of user-created as well as Spotify-curated playlists. The dataset consists of 1 million playlists, 3 million unique tracks, 3 million unique albums, and 1.3 million artists. The data is stored in a SQL database, with the primary entities being songs, albums, artists, and playlists. Each of the aforementioned entities are represented by unique IDs (Spotify URI). Data is stored into following tables:

album

artist

track

playlist

track_artist1

track_playlist1

album

| id | name | uri |

id: Album ID as provided by Spotify name: Album Name as provided by Spotify uri: Album URI as provided by Spotify

artist

| id | name | uri |

id: Artist ID as provided by Spotify name: Artist Name as provided by Spotify uri: Artist URI as provided by Spotify

track

| id | name | duration | popularity | explicit | preview_url | uri | album_id |

id: Track ID as provided by Spotify name: Track Name as provided by Spotify duration: Track Duration (in milliseconds) as provided by Spotify popularity: Track Popularity as provided by Spotify explicit: Whether the track has explicit lyrics or not. (true or false) preview_url: A link to a 30 second preview (MP3 format) of the track. Can be null uri: Track Uri as provided by Spotify album_id: Album Id to which the track belongs

playlist

| id | name | followers | uri | total_tracks |

id: Playlist ID as provided by Spotify name: Playlist Name as provided by Spotify followers: Playlist Followers as provided by Spotify uri: Playlist Uri as provided by Spotify total_tracks: Total number of tracks in the playlist.

track_artist1

| track_id | artist_id |

Track-Artist association table

track_playlist1

| track_id | playlist_id |

Track-Playlist association table

• - - - - SETUP - - - - -

The data is in the form of a SQL dump. The download size is about 10 GB, and the database populated from it comes out to about 35GB.

spotifydbdumpschemashare.sql contains the schema for the database (for reference): spotifydbdumpshare.sql is the actual data dump.

Setup steps: 1. Create database 2. mysql -u -p < spotifydbdumpshare.sql

• - - - - PAPER - - - - -

The description of this dataset can be found in the following paper:

Papreja P., Venkateswara H., Panchanathan S. (2020) Representation, Exploration and Recommendation of Playlists. In: Cellier P., Driessens K. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019. Communications in Computer and Information Science, vol 1168. Springer, Cham

This dataset is based on the subset of users in the #nowplaying dataset who publish their #nowplaying tweets via Spotify. In principle, the dataset holds users, their playlists and the tracks contained in these playlists.

The csv-file holding the dataset contains the following columns: "user_id", "artistname", "trackname", "playlistname", where

• user_id is a hash of the user's Spotify user name
• artistname is the name of the artist
• trackname is the title of the track and
• playlistname is the name of the playlist that contains this track.

The separator used is , each entry is enclosed by double quotes and the escape character used is \.

A description of the generation of the dataset and the dataset itself can be found in the following paper:

Pichl, Martin; Zangerle, Eva; Specht, Günther: "Towards a Context-Aware Music Recommendation Approach: What is Hidden in the Playlist Name?" in 15th IEEE International Conference on Data Mining Workshops (ICDM 2015), pp. 1360-1365, IEEE, Atlantic City, 2015.

In 2017, 4.9 million Italian users listened music or podcasts on Spotify, which were 1.2 million users more than in the previous year. In May 2019 a large quota of users preferred to access it from mobile devices, as the unique daily audience using smartphones was over 2.1 million users. The online reach of Spotify through desktop computer was under 41 thousand users.

Users perception on Spotify  

Apart from the usage, users seem to have a positive perception of Spotify as a brand. In the analysis of web conversations, users associated Spotify with positive values. Among the key characteristics, users mentioned utility and quality of the streaming services, together with popularity of the platform.

Beyond Spotify  

Spotify has been the favorite music streaming platform between 2015 and 2016, while the results of a more recent survey in 2018 showed that YouTube was also used as a platform of music streaming, and had a higher preference rate.

About Dataset

Overview:

This dataset provides detailed metadata and audio analysis for a wide collection of Spotify music tracks across various genres. It includes track-level information such as popularity, tempo, energy, danceability, and other musical features that can be used for music recommendation systems, genre classification, or trend analysis. The dataset is a rich source for exploring music consumption patterns and user preferences based on song characteristics.

Dataset Details:

This dataset contains rows of individual music tracks, each described by both metadata (such as track name, artist, album, and genre) and quantitative audio features. These features reflect different musical attributes such as energy, acousticness, instrumentalness, valence, and more, making it ideal for audio machine learning projects and exploratory data analysis.

Schema and Column Descriptions:

Key Features:

• Comprehensive Track Data: Metadata combined with detailed audio analysis.
• Genre Diversity: Includes tracks from various music genres.
• Audio Feature Rich: Suitable for audio classification, recommendation engines, or clustering.
• Machine Learning Friendly: Clean and numerical format ideal for ML models.

Usage:

This dataset is valuable for:

• 🎵 Music Recommendation Systems: Building collaborative or content-based recommenders.
• 📊 Data Visualization & Dashboards: Analyzing genre or mood trends over time.
• 🤖 Machine Learning Projects: Predicting song popularity or clustering similar tracks.
• 🧠 Music Psychology & Behavioral Studies: Exploring how music features relate to emotions or behavior.

Data Maintenance:

• Source: https://huggingface.co/datasets/ConquestAce/spotify-songs
• Last Updated: 2025/04/26
• License: Check original source for usage terms.

Additional Notes:

• This dataset can be enhanced by merging it with user listening behavior data, lyrics datasets, or chart positions for more advanced analysis.
• Some columns like key, mode, and explicit may need to be mapped for better readability in visualization.

This statistic shows the estimated weekly number of Spotify, YouTube and Facebook users in Finland from 2016 to 2017. The weekly user estimates for both Facebook and YouTube reached three million per platform. Moreover, Spotify's user base increased during the survey period. As of 2017, it was estimated that the Swedish-origin music streaming platform had 1.5 million weekly users in Finland.

Spotify Million Playlist Dataset Challenge

Summary

The Spotify Million Playlist Dataset Challenge consists of a dataset and evaluation to enable research in music recommendations. It is a continuation of the RecSys Challenge 2018, which ran from January to July 2018. The dataset contains 1,000,000 playlists, including playlist titles and track titles, created by users on the Spotify platform between January 2010 and October 2017. The evaluation task is automatic playlist continuation: given a seed playlist title and/or initial set of tracks in a playlist, to predict the subsequent tracks in that playlist. This is an open-ended challenge intended to encourage research in music recommendations, and no prizes will be awarded (other than bragging rights).

Background

Playlists like Today’s Top Hits and RapCaviar have millions of loyal followers, while Discover Weekly and Daily Mix are just a couple of our personalized playlists made especially to match your unique musical tastes.

Our users love playlists too. In fact, the Digital Music Alliance, in their 2018 Annual Music Report, state that 54% of consumers say that playlists are replacing albums in their listening habits.

But our users don’t love just listening to playlists, they also love creating them. To date, over 4 billion playlists have been created and shared by Spotify users. People create playlists for all sorts of reasons: some playlists group together music categorically (e.g., by genre, artist, year, or city), by mood, theme, or occasion (e.g., romantic, sad, holiday), or for a particular purpose (e.g., focus, workout). Some playlists are even made to land a dream job, or to send a message to someone special.

The other thing we love here at Spotify is playlist research. By learning from the playlists that people create, we can learn all sorts of things about the deep relationship between people and music. Why do certain songs go together? What is the difference between “Beach Vibes” and “Forest Vibes”? And what words do people use to describe which playlists?

By learning more about nature of playlists, we may also be able to suggest other tracks that a listener would enjoy in the context of a given playlist. This can make playlist creation easier, and ultimately help people find more of the music they love.

Dataset

To enable this type of research at scale, in 2018 we sponsored the RecSys Challenge 2018, which introduced the Million Playlist Dataset (MPD) to the research community. Sampled from the over 4 billion public playlists on Spotify, this dataset of 1 million playlists consist of over 2 million unique tracks by nearly 300,000 artists, and represents the largest public dataset of music playlists in the world. The dataset includes public playlists created by US Spotify users between January 2010 and November 2017. The challenge ran from January to July 2018, and received 1,467 submissions from 410 teams. A summary of the challenge and the top scoring submissions was published in the ACM Transactions on Intelligent Systems and Technology.

In September 2020, we re-released the dataset as an open-ended challenge on AIcrowd.com. The dataset can now be downloaded by registered participants from the Resources page.

Each playlist in the MPD contains a playlist title, the track list (including track IDs and metadata), and other metadata fields (last edit time, number of playlist edits, and more). All data is anonymized to protect user privacy. Playlists are sampled with some randomization, are manually filtered for playlist quality and to remove offensive content, and have some dithering and fictitious tracks added to them. As such, the dataset is not representative of the true distribution of playlists on the Spotify platform, and must not be interpreted as such in any research or analysis performed on the dataset.

Dataset Contains

1000 examples of each scenario:

Title only (no tracks) Title and first track Title and first 5 tracks First 5 tracks only Title and first 10 tracks First 10 tracks only Title and first 25 tracks Title and 25 random tracks Title and first 100 tracks Title and 100 random tracks

Download Link

Full Details: https://www.aicrowd.com/challenges/spotify-million-playlist-dataset-challenge Download Link: https://www.aicrowd.com/challenges/spotify-million-playlist-dataset-challenge/dataset_files

The music streaming market refers to the digital distribution of music content, enabling users to access and listen to songs, albums, and playlists on demand via the internet, without the need for physical media. This market has evolved with the proliferation of mobile devices, high-speed internet, and cloud-based services, making it easier for consumers to enjoy music anytime, anywhere. Music streaming platforms such as Spotify, Apple Music, YouTube Music, and Amazon Music dominate the industry, providing users with subscription-based services, freemium models, and ad-supported options. The rise of artificial intelligence and data analytics also plays a significant role in music streaming, offering personalized recommendations and curated playlists based on user preferences and listening habits. Music streaming is revolutionizing the music industry by reducing piracy, offering a wider variety of music, and providing revenue-sharing opportunities for artists, which have become essential for the growth of the global market. Several factors drive the growth of the music streaming market, including increased smartphone penetration, faster internet connections, and the growing popularity of on-demand media consumption. Recent developments include: November 2022: Mercedes Benz automobiles now include Apple Music's highly acclaimed audio with support for Dolby Atmos as a natural experience, according to a joint announcement from Apple Music and Mercedes Benz. This fulfills a shared commitment to provide customers throughout the world with the best music experience., October2021: Amazon has announced that users of the unlimited tier of the service can now stream music blended in dynamic audio from more devices than ever before, including iOS (iPhone Operating System) and Android systems with their existing headphones and select devices that support Alexa.. Key drivers for this market are: Growing popularity of on-demand media consumption. Potential restraints include: licensing agreements with record labels and content providers can limit the availability . Notable trends are: Rising adoption in digital comic is driving the market growth.