FOR ARTIST MANAGERS

Unlock your artist's next move.

Music Tomorrow gives artist managers — and independent artists building their own careers — access to best-in-class algorithmic intelligence. Understand how the algorithm positions your artist today. Prepare every release with deep market intelligence and audience insights, not gut feel. Make the collaborations and career decisions you can actually stand behind.

Trusted by 150+ artists and music industry leaders worldwide

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WHAT MANAGERS DO WITH MUSIC TOMORROW

Three ways artist managers use Music Tomorrow

Understand how the algorithm positions your artist

Know exactly which playlists, listening contexts, mood and genre signals the algorithm associates with your artist, and which adjacent audiences create natural growth opportunities. Walk into every label meeting, DSP conversation, or release planning session knowing exactly where your artist stands — and where to go next

Used with: Audience →

Go into every release with a clear game plan.

Music Tomorrow maps your artist’s algorithmic profile, identifies the right audiences to target, and helps you build a tailored action plan for each each release. For managers who want clear direction without digging through the data themselves, Copilot turns data into a ready-to-act briefs. Priorities, recommendations, and next steps, delivered monthly

Used with: Copilot →

Find collaborations that expand the audience

Find the right artists for collaborations, remixes, and live shows. Music Tomorrow surfaces peers in your niche with genuine audience overlap, validates their algorithmic trajectory, and gives you the data you need to make career decisions with confidence.

Used with: Reports →

CUSTOMER STORY

How Bishop Ivy’s team built an 11× algorithmic success story with Music Tomorrow

Bishop Ivy’s artist team used Music Tomorrow to fix a fundamental problem before their next EP release. Past campaigns had tied the artist’s profile to misaligned audiences, pushing new releases to the wrong listeners. Using Music Tomorrow, the team identified three audience clusters that matched the EP’s sound and generated precise targeting materials for Meta, pairing every single on the EP with the audience most likely to compound into algorithmic exposure.

In the three weeks after the EP drop, it generated more algorithmic streams than his previous EP had accumulated in over two years. Algorithmic stream share hit 45% — driven almost entirely by Discover Weekly and Release Radar, with no Discovery Mode push. Compared to the previous release cycle, run on a similar budget and timeline, the EP saw an 11× uplift on algorithmic streams.

11×
Uplift on algorithmic streams
45%
share of algorithmic streams

The Music Tomorrow products artist managers use

Ready to manage with proof, not just intuition?

Sign up and run your first artist analysis free — no card required. Or talk to the team about ongoing Copilot support for your roster.