How to Analyze a Music Catalog

Catalog reviews fail for one reason more than any other: they start too big. A focused analysis of a representative sample produces answers in weeks; a full-catalog exercise produces a project plan.

Step 1 — Define the question

Are you testing whether reporting is complete, whether metadata is sound, or what the catalog is worth? Each implies a different sample and a different output. Write the question down before exporting anything.

A note on the word "audit"

What follows is an analytical review: a structured comparison of datasets you control. It is not a statutory or financial audit, it produces no audit opinion, and where findings have legal or financial consequences they should be validated by qualified professionals.

Step 2 — Take a defensible sample

• Include your highest-earning works, where errors cost the most.
• Include works you believe are underperforming, where leakage is most likely.
• Include at least one recently acquired segment, where documentation is weakest.
• Cover more than one territory, since practice differs by market.

Step 3 — Assess data quality first

Measure identifier completeness, share integrity, duplicate rate and territory coverage before looking at money. These four numbers tell you how much weight the rest of the analysis can carry.

Step 4 — Reconcile detection against reporting

For the sample and period, compare detected usage against statements. Classify each difference: confirmed gap, ambiguous, or explained. Attach the evidence to each item as you go, not afterwards.

Step 5 — Prioritise and act

Rank findings by potential value and by how strong the evidence is. Route the strong, high-value items into claims; route systemic metadata issues into a cleanup backlog. The second group usually prevents more future loss than the first recovers.

Findings are opportunities, not receivables. What ultimately gets paid depends on ownership, reporting rules, territory, contracts and the organization handling the claim.