In the first quarter of 2025, the music streaming service Spotify reached an all-time high with 678 million active users worldwide. This marked an increase of around ten 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 first quarter of 2025, the company reported 268 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.

In 2008, a small startup in Sweden set out to tackle a big problem, how to give people easy access to music without turning to piracy. That company was Spotify. Fast forward to 2025, and Spotify isn't just a music platform, it’s a cultural cornerstone. Whether you’re discovering indie artists,...

As of the first quarter of 2025, Europe accounted for ** percent of Spotify monthly active users. The popular Swedish streaming service had a strong user base in Latin America, accounting for ** percent of Spotify's total *** million MAUs at that time.
Spotify Since its launch in 2008, Spotify has grown into the most widely used music streaming platform in the world, controlling over a ***** of the industry’s global market share. Despite being in direct competition with some of the biggest names in the tech industry, the company has managed to accumulate over *********** million paying subscribers and millions more free and ad-supported users. Spotify has ensured that this massive userbase has led to increasing financial success. The company reported an annual revenue of around *** billion euros in 2018, outpacing its 2017 figure by well over a ******* dollars. Music streaming Music has always been an important form of human expression and entertainment, but never before has it been so easily accessible. Thanks to the growing popularity of smartphones and streaming services, hundreds of millions of people around the world have access to an almost unlimited library of music at the touch of a button. As of 2024, streaming accounted for ** percent of the total music industry revenue in the United States, up from ** percent six years earlier. This highlights the massive influence of companies like Spotify on the music industry as a whole.

As of March 2018, Spotify’s user base was dominated by Millennials, with ** percent of its users aged 25 to 34 and ** percent aged between 18 and 24 years old. The streaming giant has permanently altered how consumers discover, engage with and share music, and according to a 2018 survey, Spotify reaches almost **** of 16 to 24 year olds in the United States each week. The power of SpotifySpotify’s popularity is undeniable, accumulating millions of premium subscribers worldwide each quarter and hundreds of millions of unique visitors to Spotify.com every month. In the United States, Spotify is one of the most commonly used apps for listening to podcasts, and despite being in constant competition with Apple Music, remains a large part of U.S. music listeners’ lives. A survey revealed that Spotify is also the preferred music streaming service among 18 to 29-year-olds, which may seem unremarkable given the data on Spotify’s user base, but serves as further evidence of Spotify’s popularity among younger users. Whether Spotify’s growth will last forever, only time will tell, particularly as Apple Music continues to put up a good fight and smaller but increasingly popular services such as Deezer begin to make their mark. But with the company recording a profit in early 2019 for the first time since its inception, Spotify remains very much a market leader and firmly on the path to future success.

A dataset covering Spotify usage and artist performance in 2025, including metrics like monthly active users, premium subscriber counts, demographic breakdowns, and playlist analytics.

Gain valuable insights into music trends, artist popularity, and streaming analytics with our comprehensive Spotify Dataset. Designed for music analysts, marketers, and businesses, this dataset provides structured and reliable data from Spotify to enhance market research, content strategy, and audience engagement.

Dataset Features

Track Information: Access detailed data on songs, including track name, artist, album, genre, and release date. Streaming Popularity: Extract track popularity scores, listener engagement metrics, and ranking trends. Artist & Album Insights: Analyze artist performance, album releases, and genre trends over time. Related Searches & Recommendations: Track related search terms and suggested content for deeper audience insights. Historical & Real-Time Data: Retrieve historical streaming data or access continuously updated records for real-time trend analysis.

Customizable Subsets for Specific Needs Our Spotify Dataset is fully customizable, allowing you to filter data based on track popularity, artist, genre, release date, or listener engagement. Whether you need broad coverage for industry analysis or focused data for content optimization, we tailor the dataset to your needs.

Popular Use Cases

Market Analysis & Trend Forecasting: Identify emerging music trends, genre popularity, and listener preferences. Artist & Label Performance Tracking: Monitor artist rankings, album success, and audience engagement. Competitive Intelligence: Analyze competitor music strategies, playlist placements, and streaming performance. AI & Machine Learning Applications: Use structured music data to train AI models for recommendation engines, playlist curation, and predictive analytics. Advertising & Sponsorship Insights: Identify high-performing tracks and artists for targeted advertising and sponsorship opportunities.

Whether you're optimizing music marketing, analyzing streaming trends, or enhancing content strategies, our Spotify Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

It started with a pair of headphones and a curiosity, what's this song playing? In coffee shops, dorm rooms, and crowded subway rides, Spotify quietly transformed how we consume music. Over the years, it’s become more than just a streaming app. It’s a personal DJ, a data mirror of our...

By 2025, Spotify will have ***** million users, over ****** million more than the **** 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 *** to ***** million active listeners per year. Spotify and Pandora – more information Pandora In 2018, Pandora was most popular among users aged ** to ** and users aged 55 or above, whereas adults in the ** 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 **** million U.S. dollars to almost *** 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 *** billion U.S. dollars. Spotify In 2018, Spotify reported *** 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.

In the first quarter of 2025, Spotify had 423 million monthly active users, which was a little less than the record high of 425 million in the fourth quarter of 2024. Meanwhile, this figure represents an increase from 388 million users in the previous quarter, highlighting Spotify's ability to attract and retain users through it's free, ad-supported tier. The company's strategy of offering a free option alongside its premium subscription service appears to be paying dividends in terms of user acquisition. User base growth and market penetration Spotify's total active user base hit an all-time high with 678 million active users in Q1 2025, marking a surge of 75 million users in just one year. This growth encompasses both ad-supported and premium subscribers, with the latter reaching 268 million in the same quarter. The platform's expansion is particularly strong in Europe and North America, which together account for 63 percent of Spotify's premium subscribers. Europe remains Spotify's strongest market, representing 37 percent of paying users. Revenue challenges and competitive landscape Despite the robust user growth, Spotify faces challenges in monetizing its expanding ad-supported user base. The company's premium average revenue per user (ARPU) has been declining since 2017, reaching 4.73 euros in first quarter of 2025. This trend suggests that while Spotify excels at attracting users, converting them to higher-paying tiers remains a challenge. The company operates in a competitive landscape that includes rivals like Pandora and Apple Music, forcing Spotify to continually innovate and improve its offerings to maintain its market position.

In the second 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.

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.

💁‍♀️Please take a moment to carefully read through this description and metadata to better understand the dataset and its nuances before proceeding to the Suggestions and Discussions section.

Dataset Description:

This dataset compiles the tracks from all of Beyoncé's albums available on Spotify, showcasing the evolution of one of the most influential artists in the music industry. It represents a comprehensive array of genres, influences, and musical styles that Beyoncé has explored throughout her career. Each track in the dataset is detailed with a variety of features, popularity, and metadata. This dataset serves as an excellent resource for music enthusiasts, data analysts, and researchers aiming to explore the impact of Beyoncé's music, identify trends in her musical evolution, or develop music recommendation systems based on empirical data.

Scope of the Data:

The focus of this dataset is on providing a comprehensive view of Beyoncé's musical releases on Spotify, specifically tailored to showcase her creative output. To this end, the dataset includes tracks from the following album types: - Albums: Full-length albums released by Beyoncé, encapsulating a range of her musical styles and eras. - Singles: Standalone single releases, highlighting key songs that have been released independently of her full albums. It's important to note that this dataset deliberately excludes compilation albums. Compilations, which often contain a mixture of tracks from various artists or previously released tracks by Beyoncé, are not included to maintain a focus on her original releases and to provide a clearer picture of her artistic evolution.

Data Collection and Processing:

Obtaining the Data: The data was obtained directly from the Spotify Web API, specifically focusing on albums and tracks by Beyoncé. The Spotify API provides detailed information about tracks, artists, and albums through various endpoints.

Data Processing: To process and structure the data, Python scripts were developed using data science libraries such as pandas for data manipulation and spotipy for API interactions, specifically for Spotify data retrieval.

Workflow: - Authentication - API Requests - Data Cleaning and Transformation - Saving the Data

Attribute Descriptions:

• artist_name: the name of the artist (Beyoncé and collaborators)
• track_name: the title of the track
• is_explicit: Indicates whether the track contains explicit content
• album_release_date: The date when the track was released
• genres: A list of genres associated with Beyoncé
• danceability: A measure from 0.0 to 1.0 indicating how suitable a track is for - dancing based on a combination of musical elements
• valence: A measure from 0.0 to 1.0 indicating the musical positiveness conveyed by a track
• energy: A measure from 0.0 to 1.0 representing a perceptual measure of intensity and activity
• loudness: The overall loudness of a track in decibels (dB)
• acousticness: A measure from 0.0 to 1.0 whether the track is acoustic
• instrumentalness: Predicts whether a track contains no vocals
• liveness: Detects the presence of an audience in the recordings
• speechiness: Detects the presence of spoken words in a track
• key: The key the track is in. Integers map to pitches using standard Pitch Class notation
• tempo: The overall estimated tempo of a track in beats per minute (BPM)
• mode: Modality of the track
• duration_ms: The length of the track in milliseconds
• time_signature: An estimated overall time signature of a track
• popularity: A score between 0 and 100, with 100 being the most popular

Possible Data Projects:

• Trend Analysis in Beyonce's Musical Evolution
• Mood and Musical Elements in Beyonce's Tracks
• Beyonce's Influence on the Music Industry Analysis

Disclaimer and Responsible Use:

This dataset, derived from Spotify focusing on Beyoncé's albums and tracks, is intended for educational, research, and analysis purposes only. Users are urged to use this data responsibly, ethically, and within the bounds of legal stipulations. - Compliance with Terms of Service: Users should adhere to Spotify's Terms of Service and Developer Policies when utilizing this dataset. - Copyright Notice: The dataset presents music track information including names and artist details for analytical purposes and does not convey any rights to the music itself. Users must ensure that their use does not infringe on the copyright holders' rights. Any analysis, distribution, or derivative work should respect the intellectual property rights of all involved parties and comply with applicable laws. - No Warranty Disclaimer: The dataset is provided "as is," without warranty, and the creator disclaims any legal liability for its use by others. - Ethical Use: Users are encouraged to consider the ethical implications of their analyses and the potential impact...

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

According to a survey about the music streaming industry in the Middle East and North Africa (MENA) region in the first half of 2020, ** percent of respondents in Saudi Arabia were aware of Spotify as a music streaming platform. In comparison, **** percent of respondents were loyal to the brand.

According to a survey about the music streaming industry in the Middle East and North Africa (MENA) region in the first half of 2020, ** percent of respondents in the United Arab Emirates (UAE) were aware of Spotify as a music streaming platform. In comparison, ** percent of respondents were loyal to the brand.

Music streaming has its roots in the peer-to-peer file sharing industry. Napster, Limewire and BitTorrent were at the forefront of changing the way people thought about music, and while they only...

1) Data Introduction • The Spotify Tracks Dataset contains information on tracks from over 125 music genres, including both audio features (e.g., danceability, energy, valence) and metadata (e.g., title, artist, genre).

2) Data Utilization (1) Characteristics of the Spotify Tracks Dataset: • The data is structured in a tabular format at the track level, where each column represents numerical or categorical features based on musical properties. This makes it suitable for recommendation systems, genre classification, and emotion analysis. • It includes multi-dimensional attributes grounded in music theory such as track duration, time signature, energy, loudness, tempo, and speechiness—enabling its use in music classification and clustering tasks.

(2) Applications of the Spotify Tracks Dataset: • Design of Music Recommendation Systems: It can be used to build content-based filtering systems or hybrid recommendation algorithms based on user preferences.

In the second quarter of 2025, Spotify had over 63 million premium subscribers in Latin America, up from 51.12 million in the second quarter of 2024 – an annual increase of about 17 percent. Meanwhile, the number of Spotify monthly active users (MAUs) in Latin America grew by about six percent in the second quarter of 2025 compared to the second quarter of 2024. Brazil and Mexico spend the most time streaming music Recent data shows that internet users in Mexico and Brazil devote more than 2 hours of their daily time to streaming music. However, while Brazil experienced a year-on-year growth of 6 percent in this regard, in Mexico, music streaming time declined by a fraction of a percentage point in the same period and by close to 3 percent since 2020. It is yet too early to say whether this trend will be a lasting one. Spotify still the top streaming choice What is certain is that music listeners in both countries rely heavily on Spotify. The company’s dominance is especially prominent in Mexico, where more than three-quarters of music streamers subscribe to the service. Interestingly though, Spotify has lost some ground in favor of other services such as YouTube Music, Apple Music, and Amazon Prime Music since 2021. In Brazil, Spotify is the leading streaming service, however, the market there is more varied. Here, the difference in usage between Spotify and its competitors such as YouTube Premium, Deezer and Amazon Music is not so pronounced, indicating perhaps an audience more open to less obvious players.

Content

This is a dataset of Spotify tracks over a range of 125 different genres. Each track has some audio features associated with it. The data is in CSV format which is tabular and can be loaded quickly.

  Usage

The dataset can be used for:

Building a Recommendation System based on some user input or preference Classification purposes based on audio features and available genres Any other application that you can think of. Feel free to discuss!

  Column… See the full description on the dataset page: https://huggingface.co/datasets/maharshipandya/spotify-tracks-dataset.

This dataset was extracted from the Spotify platform using the Python library "Spotipy", which allows users to access music data provided via APIs. The dataset collected includes about 1 Million tracks with 19 features between 2000 and 2023. Also, there is a total of 61,445 unique artists and 82 genres in the data.

This clean data has been prepared and utilized for research purposes. Its significance lies in its potential to unravel patterns and predict song popularity prior to its release. This dataset could be used to create various predictive models with machine-learning/deep-learning techniques.

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