One Artist. 11 Platforms. Complex Splits.
Figuring Out Who Gets Paid Became Automatic.
PlayLedger is a music royalty tracking and payout calculation system built by Nigel Brooks for an independent artist with a large catalog and multiple collaborators across every release. Pulling data from 11 streaming platforms, calculating per-track splits, and generating accurate payout reports had become a second job. PlayLedger made it infrastructure.
The Challenge
11 different platforms. Different payout cycles. Multiple collaborators on every track.
Every streaming platform has its own reporting format, its own payout timeline, and its own per-stream rate that fluctuates over time. An artist with a large catalog spanning multiple release years accumulates royalty data across Spotify, Apple Music, YouTube Music, Tidal, Amazon Music, and beyond, each reporting independently with no unified view.
Add collaborators, producers, featured artists, co-writers, each with a negotiated percentage on specific tracks, and the calculation problem becomes significant. Paying the wrong amount or missing a collaborator entirely creates legal and relationship risk. Doing it manually every quarter was no longer sustainable.
Royalty Flow
The Build
Python pulls the data. The math handles itself.
PlayLedger pulls royalty data from 11 streaming platforms using a Python data pipeline. Each platform's report format is normalized into a unified data model so the system can aggregate streams and earnings across all sources for any given track, release, or time period.
Collaborator splits are stored per track, producer percentage, featured artist share, co-writer cut, and applied automatically when royalties are calculated. The system produces payout reports broken down by collaborator, by platform, and by release period so every payment is traceable and defensible.
The dashboard surfaces earnings trends, top-performing tracks, and per-platform breakdowns through a data visualization layer. The artist can see exactly where money is coming from and who needs to be paid, without opening a single spreadsheet.
What Was Delivered
11-Platform Data Pipeline
Automated ingestion and normalization of royalty data from 11 streaming platforms.
Collaborator Split Engine
Per-track split rules applied automatically across the full catalog.
Payout Report Generation
Itemized reports per collaborator, per platform, and per release period.
Earnings Dashboard
Visual breakdown of streaming performance, top tracks, and revenue by source.
More from The Build Log
Work with Nigel Brooks
Have a data or payments problem that needs a system?
Nigel G. Brooks is a cloud engineer and IT consultant based in Houston, TX. He builds data pipelines, dashboards, and payout systems for businesses that need their numbers to be right.
Get in touch ↗