Data and methodology / public overview

Know what the evidence can support.

Music Intel connects observations that normally sit in separate systems. This page explains the public operating model: what the data domains mean, what every engagement must define and where human judgement remains essential. Relevant method detail is reviewable under agreed confidentiality, while protected implementation detail remains confidential.

01 / Cross-reference model

Twelve domains, one defined scope.

Music Intel organises supported data into twelve domains. Within an agreed Musicata Pro scope, the daily cycle can evaluate up to 1,200 artist-level fields and observations from the relevant domains. That is a cross-reference model, not a promise that every field or domain is populated for every artist every day. Availability depends on the product, artist, source, territory, permission and configuration.

The point is not to create a larger pile of numbers. It is to compare related signals, retain their source and timing, and help a person decide what deserves attention next.

01

Streaming

Artist, recording and release activity reported by supported services.

02

Social

Audience, engagement, cadence and change across supported public profiles.

03

Video

Audience and content activity across supported video and short-form services.

04

Playlists

Editorial, algorithmic and user-curated placement context where available.

05

Charts

Position, entry, re-entry and duration across supported chart sources.

06

Geography

Country and city-level signals where the underlying source permits them.

07

Press and editorial

Relevant coverage and editorial signals across supported publications.

08

Search intent

Search interest and changes in audience discovery behaviour.

09

Owned audience

Permissioned first-party and organisation-level website activity where configured.

10

Rights and registrations

Source-bound catalogue and identifier records used within the agreed product scope.

11

Radio and broadcast

Airplay and broadcast activity across supported monitoring sources.

12

Live and touring

Venue, event and geographic demand signals where available.

02 / Scope before proof

Every engagement defines the boundary.

A decision-grade result needs more than a source list. Before a proof of value begins, the parties agree the question, the evidence boundary and how the result will be reviewed.

Entities and identifiers

Which artists, recordings, works and organisations are in scope, and how identities are resolved.

Sources and coverage

Which sources are used, the territories and history available, and any material gaps.

Freshness

How often each source can be refreshed and when an observation was last updated.

Provenance

Where a fact came from and whether it is authoritative, observed, inferred or supplied by the customer.

Permitted use

What the data may be used for, shared with and retained for under the agreed licence.

Limitations

Known blind spots, confidence boundaries and decisions that still require human review.

Delivery

The product view, report, export, feed or integration method agreed for the engagement.

03 / Product boundaries

The method follows the job.

The same governance principles apply across Music Intel, but the inputs, responsibilities and outputs are not interchangeable.

Musicata Pro

Roster and artist intelligence

Connects artist activity and workflow beside existing delivery, accounting and reporting systems. It supports priorities and action; it does not replace those operational systems.

See Musicata Pro →
BlackBox

Forensic royalty investigation

Works from a defined source and custody boundary. Candidate evidence, investigator actions and findings remain distinguishable throughout review.

See BlackBox Royalty Investigator →
Technology partnerships

Selected data and capabilities

Delivery, fields, permitted use, update pattern and support are agreed for the partner's product and operating model.

Explore technology partnerships →

Test the smallest credible question.

A proof of value should make its inputs, measures, limitations and decision point clear before work begins.

See the proof-of-value model → Discuss a data or technology scope →