Chartmetric for Music Catalog Scouts: What to Look at Before Pitching

Chartmetric is the data platform most catalog buyers use to underwrite indie deals. For scouts sourcing those deals, it's the same data — used for qualification rather than underwriting. Here's how scouts should actually read a Chartmetric profile to decide whether an artist is worth pitching.

If you're sourcing music catalog finance deals seriously, Chartmetric is the tool you'll spend more time in than any other. Founded in 2015, it's now the de facto data layer for most professional music industry research — covering 8M+ artists across Spotify, Apple Music, YouTube, TikTok, social platforms, and ~250 chart and playlist sources globally. The catalog buyers on the other side of your deals (beatBread, Symphonic, Xposure, Connect Music) all use Chartmetric in their underwriting; the data on it is the data they're modeling against.

What scouts often miss: Chartmetric has many more useful signals than the obvious "monthly listeners" number on the front page. The signals that actually predict whether a buyer will underwrite an artist's catalog are layered deeper — trajectory, audience stickiness, platform mix, regional spread, sync history, decay rate. Scouts who learn to read those signals quickly can qualify in 30 seconds what would take a less-trained scout 30 minutes.

This piece walks through what to actually look at on a Chartmetric profile when you're deciding whether an artist is worth pitching, in the order that matters most.

The qualification question Chartmetric answers

When you're scouting, you're trying to answer one specific question fast: Is this artist's catalog likely to clear the underwriting bar at the buyers I work with?

The underwriting bar varies by buyer but the variables don't. Every credible buyer looks at roughly the same things:

• Current royalty income (estimated from streams)
• Income trajectory over the last 12–24 months
• Catalog depth and revenue concentration
• Audience quality and stickiness
• Decay rate / catalog half-life
• Platform diversification
• Regional revenue distribution
• Sync history and frequency

Chartmetric surfaces each of these. Some are obvious; some are buried. The skill is knowing where to look and what threshold tells you "this is worth a real conversation" vs. "skip and move on."

The first 30 seconds: top-line filtering

When a new artist comes up in your sourcing queue, the first look is a 30-second scan to decide whether to invest more time. Open the Chartmetric profile and check, in order:

Monthly Listeners (and the 90-day trend)

The most-visible number, and the one most scouts over-index on. Useful as a quick filter, but only with context. Three rules:

• Under 5,000 monthly listeners: probably too small. The streaming-income math typically doesn't support a buyer's minimum deal size. Exceptions: artists with strong YoY growth or strong sync income (which won't show in monthly listeners).
• 5,000–50,000 monthly listeners: the indie-finance sweet spot. Most deals at beatBread, Symphonic, and RoyFi happen here.
• 50,000–500,000 monthly listeners:premium indie band. Talk to Xposure, Connect Music, Intercept — bigger advances available.
• 500,000+ monthly listeners: entering label- adjacent territory. Multiple buyer options exist; the artist may already have one.

Then check the 90-day trend curve right below the headline number. Steady or growing is good. Sharp decline is a yellow flag — buyers underwrite to the trajectory, not the peak. A 50K-listener artist trending down toward 30K gets a smaller offer than a 30K-listener artist trending up toward 50K.

Catalog Size (Spotify Tracks)

The number of tracks in the artist's catalog. Found under the Spotify section. The relevance:

• Under 10 tracks: very small catalog. Risky for buyers because revenue concentration is high. Single viral hit = single point of failure.
• 10–30 tracks: typical indie catalog. Most buyer math works here.
• 30+ tracks: deep catalog, revenue spread across more tracks. Better for buyers because portfolio effect kicks in.

Most Popular Tracks

Look at the top 5 tracks by Spotify stream count. The question: how concentrated is income in the top 1–2 tracks?

A healthy catalog has revenue distributed: the top track might be 25–35% of total streams, with the rest spread. Concerning catalogs have 70%+ of streams in one track — buyers discount these because if that single track decays fast, the whole catalog economics collapse.

The next 90 seconds: trajectory + audience quality

If the top-line filter passed, dig into trajectory and audience.

Monthly Listener history chart (1Y, 2Y views)

Switch the Monthly Listeners chart to 1-year and 2-year views. The shape matters more than any specific number. Healthy shapes:

• Stair-step growth: sustained increases with each release cycle, holding the gains. Best possible profile.
• Plateau with occasional bumps: stable base audience with growth on releases. Solid.
• Slow steady growth: not exciting but financeable. Multiple usually 7x–10x.
• Spike-and-decay: one viral moment, then collapse. Concerning. Buyers underwrite to where the decay is heading.
• Long-term decline: hard pass. Even at decent absolute numbers, a declining trajectory means the underwriting math doesn't work.

Listener-to-Follower ratio

Found by comparing the Spotify listeners number to the Spotify followers number. Healthy ratios are 1:1 to 3:1 (listeners:followers). Concerning ratios are 10:1 or higher — it means most of the audience is passive playlist consumption rather than fans, and playlist-driven catalogs decay faster than fan-driven ones.

Genre + Audience demographics

Chartmetric tags genres and shows audience demographics by age, gender, country. Two things to check:

• Genre fit for buyers: indie rock, alt R&B, indie folk, ambient electronic, Latin alternative — all have active buyer interest. Lo-fi instrumental, meditation, children's music — less buyer appetite (lower per-stream payouts).
• Regional concentration: 80%+ of listeners in one country is concerning. Buyers prefer geographic diversification because it spreads royalty platform risk (if Spotify cuts US rates, a 100%-US artist gets hammered).

The deeper 5 minutes: data that buyers actually underwrite to

If the artist still looks interesting, this is where you spend real time before deciding to pitch them. The data here is what gets surfaced in beatBread or Xposure underwriting memos.

Streaming projections

Chartmetric's Pro tier offers projection tools that model future streaming income based on historical trajectory. The 12-month and 36-month projections are useful gut-checks: buyers' offers will be roughly anchored to similar projections.

Royalty calculator outputs

Chartmetric exposes estimated royalty income per platform. For US listeners on Spotify, expect ~$3–$4 per 1,000 streams gross, $1.50–$2.50 net to the artist after distributor cut. Apple Music pays roughly 50% more per stream. YouTube is variable but usually lower. The aggregate gives you a back-of-envelope annual royalty income — the foundation of every advance calculation.

Playlist mix

Are the artist's plays coming from editorial Spotify playlists (Spotify-curated), algorithmic playlists (Release Radar, Discover Weekly), user-generated playlists, or direct listens? Higher direct-listen percentages = stickier audience. Higher algorithmic percentages = more fragile to algorithm changes.

Social platform integration

Chartmetric also pulls Instagram, TikTok, YouTube, and other social signals. Two things matter:

• Engagement, not just follower counts. An artist with 100K Instagram followers and 0.5% engagement is less valuable than an artist with 10K followers and 8% engagement. The second number is the real audience.
• TikTok presence + recent virality. Streaming growth often follows TikTok moments. An artist with a recent TikTok hit driving streams is worth underwriting differently than an artist with steady-state streams from older catalog.

Sync history

Chartmetric pulls sync placements (TV, film, ad placements). Tracks that have synced before are statistically more likely to sync again, and sync income is meaningfully more predictable than streaming. Even one or two prior syncs materially improve a buyer's underwriting model.

What to record as you scan

For each artist you qualify, the data you should capture for the buyer pitch:

• Monthly listeners (current + 90-day trend direction)
• Estimated annual streaming royalties (USD)
• Catalog size (# tracks)
• Top track + % of total streams
• Genre + listener regional spread
• Listener-to-follower ratio
• Playlist mix (editorial / algorithmic / user)
• Notable sync history
• Distributor (DistroKid, TuneCore, Symphonic, label, etc.)
• Instagram + TikTok engagement signals

With those 10 fields, you can run a credible first pitch to a buyer. Without them, you're asking the buyer to do your work — which is fine occasionally but doesn't scale.

Chartmetric pricing for scouts

Chartmetric has a free tier, a Pro tier (around $140/month billed annually), and a Business tier with API access. For scouts, the Pro tier is usually the right starting point — you get the projections, deeper trajectory views, and historical data that matter for catalog finance work. The Business tier with API access is worth it once you're doing enough volume that you want to automate qualification (which Praecora handles natively, integrating Chartmetric and Spotify data automatically into the artist record).

Common mistakes scouts make on Chartmetric

Looking only at the front page

The Monthly Listeners number is one input. Scouts who qualify entirely on that number miss most of the signal (trajectory, concentration, sync history) and burn time on deals that look big but underwrite small.

Ignoring trajectory

A 30K-listener artist with steep growth is more valuable than a 50K-listener artist with sustained decline. Underwriting cares about where the curve is heading, not where it currently is. Scouts who don't internalize this pitch the wrong artists.

Skipping the regional check

A 50K-listener artist with 95% of listeners in one country is meaningfully riskier than a 50K-listener artist with listeners spread across 20 countries. Buyers know this. Scouts who skip the check waste pitches.

Pitching one-hit catalogs

80% revenue concentration in one track = limited buyer appetite at almost every credible buyer. Don't burn relationships pitching these. Note the concentration risk and move on (or pitch a different deal structure that's not a pure royalty advance).

The bottom line

Chartmetric is the qualification engine for serious music catalog scouting. The 30-second top-line scan filters obvious no-go artists. The 5-minute deeper read produces a qualified data set buyers will take seriously. Scouts who learn to read Chartmetric efficiently can qualify 50 artists in an hour; scouts who don't burn an hour on 5.

For the broader sourcing context — how scouts actually find artists, what cold outreach looks like, how the buyer landscape works — see our pieces on the broker playbook and the buyer directory. For Spotify-specific data fields that complement Chartmetric, see our piece on Spotify for Artists data.

Praecora integrates Chartmetric and Spotify data directly into the scout's artist record, so qualification happens automatically as new artists enter the pipeline — no manual tabbing required. Book a 20-minute demo to see what the integrated qualification flow actually looks like in practice.