Music Listening Data
Buy and sell music listening data data. What people listen to, when, for how long, and what they skip. The dataset that powers every playlist recommendation algorithm.
No listings currently in the marketplace for Music Listening Data.
Find Me This Data →Overview
What Is Music Listening Data?
Music listening data captures what people listen to, when they listen, how long they engage with tracks, and which songs they skip. This behavioral dataset powers recommendation algorithms across streaming platforms and is collected through passive tracking of user activity on music apps and services. The data includes granular event logs with song titles, artists, albums, and timestamps, often enriched with audio features like genre, instrumentation, and lyrical language. Music listening data is valuable for both industry and research because large-scale, openly available datasets remain scarce. Platforms like Spotify, Last.fm, and ListenBrainz have accumulated hundreds of millions of listening records. The data reflects broader trends in music consumption, artist popularity, and cultural taste evolution, making it essential for content recommendations, music discovery, and understanding listener behavior patterns.
Market Data
180+ million unique listens
ListenBrainz Listening Records
Source: ResearchGate
4,500+ users
ListenBrainz Active Users
Source: ResearchGate
590+ million
Spotify Monthly Active Users
Source: ResearchGate
58,247 unique songs tracked
Example User Dataset Coverage
Source: MDPI
Who Uses This Data
What AI models do with it.do with it.
Music Recommendation Engines
Streaming platforms train collaborative filtering models on listening history to generate personalized playlist recommendations and track discovery suggestions.
Music Industry Analytics
Labels, distributors, and artists analyze listening trends to understand song popularity dynamics, genre evolution, and emerging artist trajectories.
Academic Research
Researchers study music preference patterns, listener behavior, and the relationship between musical characteristics and consumption habits.
Marketing & Advertising
Advertisers and media companies target campaigns based on listening demographics, genre preferences, and user behavior patterns.
Pricing depends on the proposed terms
We do not have a verified, comparable price for your dataset. Consider the permitted uses, license term, exclusivity, provenance, coverage and quality. A seller asking price is a proposal, not an appraisal or guaranteed sale. Compare prices only when the source, date, currency, unit and license scope are known.
What Buyers Expect
What makes it valuable.valuable.
Complete Event Logs
Time-stamped records including song title, artist, album, play duration, and skip events for accurate behavior modeling.
Audio Feature Enrichment
Linked metadata on genre, instrumentation, tone, tempo, and lyrical language to enable content-based filtering and music characterization.
Data Validation
Technical and manual validation of song-to-metadata matches; filtering of non-musical tracks and artifacts to ensure analytical reliability.
Privacy & Consent Clarity
Transparent data collection practices and user consent documentation; clear licensing terms for commercial vs. non-commercial use.
Potential applications and organizations
Who's buying.buying.
Operates largest music streaming service with 590+ million monthly active users; uses listening data to power recommendation engines and analyze popularity trends.
20-year-old music tech company that aggregates listening history across multiple platforms; provides users with personal analytics and tracks industry-wide listening patterns.
Analyze listening data to forecast track popularity, identify emerging artists, and make marketing and A&R decisions.
Access open datasets like ListenBrainz to build recommendation models and study the relationship between musical features and listener behavior.
FAQ
Common questions.questions.
What exactly gets recorded in music listening data?
Music listening data includes time-stamped event logs capturing song title, artist, album, play duration, and skip events. This raw data is often enriched with audio features (genre, instrumentation, tone, lyrics) and listener context (time of day, device type) for deeper analysis.
How is music listening data used for recommendations?
Streaming platforms use collaborative filtering on listening histories to identify patterns: if users with similar taste profiles listened to track A and B, but you've only heard A, the algorithm recommends B. The ListenBrainz dataset, for example, achieved a 10.56% root mean square error in early recommendation models trained on 180+ million listens.
Is music listening data available for purchase?
Open datasets like ListenBrainz are free under Creative Commons licensing for commercial and non-commercial use. However, individual user listening histories on platforms like Spotify are proprietary. Aggregated market reports and licensed datasets have variable pricing based on scope and exclusivity.
What are the privacy and consent considerations?
Last.fm and similar platforms emphasize the importance of user consent and transparency in data collection. Many listeners want control over how their listening data is used and expect clear disclosure of which third parties can access their history. Ethical data practices are increasingly important to users and industry players.
Sell yourmusic listeningdata.
Describe your music listening data and the uses you are authorized to offer. Price, legal suitability, and buyer interest require separate evaluation. No match or sale is guaranteed.
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