It is surprisingly hard to answer a seemingly very simple question: how much money should be paid to an artist for using their music? There are a few key challenges in answering this question. Music can be used in many different ways from physical or virtual distribution to radio plays to licensing for films, tv shows, or ads, among others. This means that there are a lot of different silos of data out there which makes it difficult to keep track of where the music is being played.

The second biggest challenge is knowing who earns what. There can be multiple artists involved, there are labels and sometimes there are investor groups. There can also be different rules for different geographies which adds to the complexity. The metadata is extremely important to be able to identify who owns what. But ensuring that the metadata is complete and correct and can be used to process the data is challenging, particularly with the amount of music that is created on a daily basis.

The outcome of this for the artist is that you might never get paid or you get paid up to several months or even years after your music has been heard. Utopia was created to ensure fair play for every play so that more creators can live off their music.

Solving the Data Gap

To solve the data quality problem we use an artificial intelligence and machine learning engine to create a platform that collects the data from various sources, cleans it up, and enhances it. This single-source-of-truth data platform forms the core of Utopia but the data alone isn’t enough.

Given the size of the industry there are many different players in each of those three core problem spaces; creation, consumption and payments. This leads to the challenges of data being scattered everywhere. But by leveraging our core platform we have a lot of flexibility to create dedicated services and spin off new business units as needed and really to cover the whole industry.

Using this platform approach we have grown from 150 people to over 1,000 in less than 12 months through a combination of organic growth and programmatic M&A. Often there are existing businesses in the industry that are serving particular segments. Programmatic M&A is where we identify and acquire the businesses that would be a good fit for our strategy and where our platform can add value. This has allowed us to really accelerate our roadmap.

Acquisitions are always challenging from a cultural perspective. We really believe in team autonomy but we still need to work towards the business goals. Product, Technology, and Data work really closely together to balance the autonomy of the teams with the need for alignment across the teams.

As we have grown we have really started to see the network effect between the platform and the different business units that allow us to continually improve the platform services and then in turn improve the dedicated services which then leads to more customers, continuing the growth flywheel.

Wrapping it up

Closing that data gap of course it's not a journey that is going to end in a day or two a week or a quarter and all that we're in for the long term and it's going to take a while to get there.

Every single piece of data that we can leverage, make more complete and more transparent will get us closer and closer to this utopian view where there is fair play for every play and everybody can benefit from that thriving ecosystem.