Streaming (DSPs)
Plays, listeners, saves, skips, retention. Artist, track, and album level.
Every major independent music data platform built in the last decade has been acquired by a label or shut down. Music Intel remains independent. We measure the infrastructure behind the music industry - streaming, social, rights, and charts - across every market where royalties are collected.
Some teams watch Spotify. Others watch TikTok. Others the UK charts. We watch all of it - and everything between. Twelve categories of signal, measured daily, cross-referenced against a reference universe of over two hundred million recordings. A single decision-grade view of every artist on your roster.
Plays, listeners, saves, skips, retention. Artist, track, and album level.
Audience size, engagement, post cadence, demographic mix, velocity.
Views, watch time, cover versions, UGC volume, sound usage on short-form.
Editorial placements, algorithmic reach, user playlists, followers, churn.
9,198 chart sources scanned daily. Position, weeks-on, debut, re-entry.
Where the listeners actually are. Country and city-level attribution across 105 territories.
News mentions, reviews, features, podcasts, interviews. Sentiment-scored.
Organic interest across Google and partner search. Pre-Shazam momentum.
Identifiable industry visitors to your artist's website. Labels, broadcasters, agencies, sync houses - mapped to IP the moment they land.
111K IPIs, 2.7M works indexed for ISWC lookup, 7.6M recording-to-work links.
Airplay across terrestrial, satellite, and streaming radio. Spin counts, rotation, DJ support.
Tour announcements, venue sizes, ticket prices, box office settlement where visible.
Scout Alert maps industry IP addresses - labels, publishers, booking agencies, broadcasters, sync supervisors, festival bookers - to the artists they're watching. A lightweight pixel on your artist's site, a reverse-DNS lookup, and a push notification the moment a recognised visitor lands. One of twelve categories we measure. All of them work this hard.
Every signal. Every day. One company, independent, unacquired.
Every artist in your catalogue, cross-referenced daily against 1,200 signals. Fraud flagged before it corrupts reporting. Breakouts surfaced before competitors notice. Territory intent measured, not guessed. Decisions you can defend in a meeting.
A 207-million-track reference catalogue, cross-referenced with chart, streaming, and rights data. Establish the writer, the plays, the listeners, and the gap. Produce the evidence pack. File the claim. Settle in days rather than years.
The scale of the black box, measured in dollars rather than rhetoric. And what a single-country figure implies globally.
Read the market →Anomalies are cheap. Evidence is not. A short paper on the difference between a chart movement and a verified listening event.
Read the method →Six months inside a back-catalogue recovery: the writer, the gaps, and the claim that settled in ninety-one days.
Read the forensic →A coordinated bot campaign has a fingerprint in the raw data. Streaming counts are only the first layer.
Read the method →The window between a genuine organic breakout and a commercial response is shrinking. Most artists with momentum signatures have no infrastructure to capitalise on them.
Read the market →Streaming fraud is not random. It clusters geographically and operationally. A composite case showing how a coordinated playlist network generates high play counts with zero legitimate engagement.
Read the forensic →In a significant number of markets, streaming data signals meaningful live demand that booking agents are not acting on. The gap is measurable.
Read the market →A significant percentage of CWR transactions contain errors that cause royalties to fail silently. Accepted by societies but matched to the wrong work, the wrong writer, or no work at all.
Read the method →UK artists performing on recordings played in Germany, the Netherlands, and Scandinavia are owed money from three of the highest-paying neighbouring rights societies in the world. Most are not claiming it.
Read the market →M&A diligence looks at what a catalogue has earned. It almost never looks at what it should have earned. A composite case showing the gap between acquisition model and royalty reality.
Read the forensic →