We practice socially responsible management, which provides enhanced opportunities for the artists.
We offer artists an option to retain some investment upside via participation in MBPG’s aggregated portfolio of pooled royalties and remain active in their own catalog. It is our missions to help improve the economic equation for songwriters by advocating for the increase of royalty rates and integrating participation in catalogs.
We use AI & ML capabilities to discover areas of optimization for each catalog.
Mockingbird Publishing Group owns the intellectual property to two bespoke proprietary machine learning and artificial intelligence (AI/ML) algorithms referred to as “Bass” and “Treble”. These algorithms use a recommendation engine to optimize revenue streams by identifying new sources unavailable or unknown to the artist, through the lens of the artist’s historical revenues and prior data provided by industry professionals.
This proprietary valuation algorithm created by our team helps to develop the value of artist catalogs or songs based on data sets.
Once the Bass Algorithms gives Mockingbird a look at value ranges based on earnings then the Treble Algorithm provides the company with a look at potential future earnings or a “return on investment” perspective based on a discounted cash flow paradigm.
We’re dedicated to the development & success of our clients.
Unlike many traditional publishing companies, Mockingbird Publishing Group is dedicated to the development and success of underutilized catalogs. With over 100 collective years of experience in the industry, our expert management team produces proactive servicing and pitching.
Applications of AI in Music Business
The way we listen to music has evolved over the last decade. As consumers stream music, movies and Peloton workouts, enormous amounts of data are being captured and stored to help inform processes and automate the tedious. With the introduction of AI (artificial intelligence) in the music industry, significant changes have been made in all areas of the business from music production to royalty collection.
Mockingbird is an investment science pipeline of music
containing robust data sources as inputs and quantitative investment strategies as outputs.
We augment our process through an approach that down-selects datasets from artists
management, Public Rights Organizations (PRO’s) and accounting sources. From there
we develop strategy types that optimize for a variety of market-dependent variables:
market cycle, risk-return profile, and future development.
By incorporating artificial intelligence and machine learning capabilities, we are able to increase managed catalog ROI, while bringing innovation and more efficient processes to the industry.