In December Blokur was announced as an official partner of the Mechanical Licensing Collective’s (MLC) Data Quality Initiative (DQI).
As I said at the time, Blokur is delighted to be working with the MLC to help our music publisher clients big and small ensure their rights are accurately represented in the MLC database so that they get their fair share of streaming royalties.
Today I’m pleased to announce an update to Blokur’s MLC offering that means we can do an even better job of helping publishers and songwriters to get paid what they should, when they should.
The standard DQI allows publishers to check their rights in the MLC database using an identifier like an HFA Song Code or an ISWC. That’s already a great opportunity to identify missing registrations or mismatching shares. But we are now improving on that in two ways:
(i) by performing our analysis not just on the basis of identifiers but on the raw metadata of the MLC’s full 17 million song database; and
(ii) by bringing our sub-graph matching technology to bear on duplicates, conflicts and errors.
The challenge with identifying whether your song is correctly registered in such a large database is that duplicates and conflicts may be disguised by alternative titles, writer pseudonyms and duplicate identifiers. Imagine that you register your 60% interest in Uptown Funk by Bruno Mars with ISWC0001 and somebody else registers a 60% interest in Up Town Funk by Peter Gene Hernandez with ISWC0002. If the two registrations have not been merged, you may be losing out to a hidden duplicate.
Blokur’s sub-graph matching technology analyses songs and contributors not as names or IDs but as a graph of relationships. This graph of relationships takes account of all the available context: co-writers, pseudonyms, alternative IPI and ISWC codes, alternative titles…you name it. That means that Blokur can identify duplicates, conflicts and errors that are otherwise invisible. The bottom line is that there is no better way to make sure that you are getting paid all the streaming royalties you should.
We’re also improving our DQI reporting.
Blokur’s MLC analysis produces automated reports to help you prioritise and take the action you need to update the MLC database as quickly and easily as possible. This includes:
(i) A duplicates file capturing all the MLC works that need to be merged, in a format that can be processed by the MLC. No need to analyse DQI reports yourself to identify where the duplicates are.
(ii) A conflicts file prioritising conflicts by the popularity of the song on streaming services. That means spending more of your time on the issues that will have the most impact.
We’re already performing this analysis for both majors and indies. Want to learn more? Drop us a line at phil [@] blokur [dot] com.