I have been marketing music since 1989 and, in that time, the music industry has undergone titanic changes. Not just in the ways we now consume music, but also in the ways we understand it.
There was a time when music industry data was little more than a name written on a piece of paper.
An artist. A song title. A songwriter. A publisher. A catalogue number. A sales figure.
That was data.
I know, because I did it myself. I still have one of those old iron filing cabinets in my loft, which now represents little more than a myriad of useless scraps of paper. Back then, that filing cabinet contained valuable information.
The earliest record companies maintained physical ledgers and card indexes documenting recordings, artists, composers, manufacturing and sales. Information was scarce, slow to arrive and usually retrospective. The industry knew what it had manufactured and, eventually, what it had sold.
But documenting it was a human responsibility, and humans make mistakes, right? More of that later!
The Birth of the Charts. And the Day Everything Changed
As recorded music became a mass-market business, data became increasingly important and, consequently, increasingly valuable. Sales information collected from record shops created the foundations of the record charts. Radio added another important measurement: airplay.
Suddenly, the industry had signals. Demographic indicators. Geographic understanding.
Labels could see which records were selling, which songs were being played and which artists were gaining momentum. But it remained a relatively blunt instrument!
If 50,000 albums were sold, the label knew that 50,000 albums had left the shops. It didn't necessarily know who bought them, why they bought them, which track they loved most or whether they played the record once or 500 times.
For decades, the music business largely operated on aggregated information, experience, instinct and relationships or simply guesswork!
Then Everything Became Digital
The CD accelerated the computerisation of music catalogues, but the real revolution arrived with the internet. Digital downloads transformed a recording from a physical product into a digital asset. And digital assets needed metadata.
Artist. Track. Album. Composer. Publisher. Label. Genre. Release date. Territory. Ownership. Identifiers.
Technologies including CD databases and ID3 tags became important building blocks of digital music metadata.
Unique identifiers such as ISRC for recordings and ISWC for musical works became increasingly important because the industry needed machines to accurately identify millions of recordings and compositions.
Then streaming changed everything again.
From Sales Data to Behavioural Data
Streaming didn't simply create another distribution format. It created an entirely new data economy. Every play became information. Every skip became information. Every playlist addition, search, save, share and repeat listen became another signal.
Add YouTube views, TikTok activity, Shazams, Instagram followers, ticket purchases, merchandise, radio airplay, geographic movement, demographics and thousands of other signals, and something extraordinary happened.
The music industry moved from measuring transactions to measuring behaviour.
Today, streaming represents around 69% of global recorded music revenues, with more than 750 million users of paid subscription accounts worldwide.
And the amount of music entering this ecosystem is staggering. In 2025, an average of approximately 106,000 new ISRCs were delivered to digital platforms every single day.
Welcome to the Era of Trillions
We have moved from filing cabinets containing thousands of pieces of information to technology capable of interrogating data in trillions of different ways.
Music analytics platforms were already demonstrating this scale years ago. BuzzAngle's methodology, for example, was described as enabling more than 10 trillion combinations of individualised reports across artists, songs, albums, labels and distributors.
Suddenly, the fragmented, departmentalised and individual responsibilities of different parts of the music industry could begin to come together.
Just think about that.
Information that was once distributed across millions of iron filing cabinets, departments, territories, data houses and analytics providers can increasingly be brought together into one central intelligence ecosystem. Wow!
Labels, publishers, managers and artists can see for themselves where the opportunities lie without leaving one digital location.
The modern artist leaves a vast digital footprint across streaming platforms, social networks, radio, video, ticketing, publishing, neighbouring rights, playlists, search engines and fan communities.
The challenge is no longer simply obtaining data. The challenge is connecting it, verifying it and understanding what it means. And that distinction matters.
A million streams is a statistic.
Knowing where those streams originated, whether the audience is authentic, who those listeners are, whether engagement is accelerating, what other artists they consume and where demand is developing geographically is music intelligence.
That is the next evolution and one I hope I get to see through the eyes of Music Intel.
Artificial intelligence and machine learning can now examine relationships across enormous datasets that no team of human analysts could realistically process manually. But there is an important irony.
Despite the extraordinary volume of information available, the industry still struggles with something remarkably basic: accurate metadata. Incomplete or inaccurate metadata can still delay payments, and sometimes prevent creators from being paid altogether, which still sends my head west!
Remember those humans making mistakes?
Some things haven't changed quite as much as we think. So, we have travelled an extraordinary distance. From a clerk recording an artist and song in a ledger...to computers processing billions of streams...to an interconnected global music ecosystem capable of generating and analysing trillions of potential data touchpoints.
For more than a century, the music industry asked:
“How many records did we sell?” Today it can ask: Who is listening? Where are they? What are they doing? Why is an artist growing? Is that growth genuine? What are the differences between MP3 and MP4 analytics? Where will they break next and what should we do about it?
The future of the music industry won't simply belong to those with the most data. It will belong to those who turn that data into music intelligence.
Gosh, I wish I was just starting, rather than just finishing!
About Music Intel
A company-level editorial statement.