Spotify Artist Scout – Monthly Listeners, Play Counts, AI Score on the Apify Store →

How to scout emerging artists on Spotify every week — without a $150 seat

A step-by-step tutorial for A&R scouts, indie labels, playlist curators and bookers: turn "artists like the ones I already love" into a ranked, explained shortlist of emerging artists with Spotify Artist Scout on Apify — https://apify.com/rich_minds/spotify-artist-scout-ai

Owner note (delete before publishing): post on dev.to and Hashnode with the canonical URL set to

https://apify.com/rich_minds/spotify-artist-scout-ai, then record the post URL in brief.json → marketing.links.

Every figure marked "estimate" is from the worked example, not a measured live run — replace it with the first

live run's OUTPUT numbers before you publish, or keep the word "estimate".

The problem: the Monday spreadsheet

Every Monday an A&R scout at an indie label runs the same loop. Open ten Spotify artist pages. Copy monthly listeners and followers into a sheet. Compare them with last week's column. Check when each artist last released something. Read each bio for a label name, a manager or a "self-released". Then write a first message to the two or three that look like they are breaking.

For 50 artists that is most of a morning — and it still misses every artist nobody sent a link to. The two tools the industry uses for this, Chartmetric (Premium, $150 a month per seat, chartmetric.com/pricing, checked 2026-09-27) and Soundcharts (PRO, $129 a month, soundcharts.com/pricing, checked 2026-09-27), cover many more platforms than Spotify and are excellent at it. But a two-person label, a playlist curator or a regional promoter rarely pays a seat price for one person's weekly Spotify scouting.

Spotify's official Web API does not return monthly listeners at all, so a sheet with an API script is not an answer either. The numbers live on the public artist page.

What Spotify Artist Scout does

It is an Apify Actor that does the Monday loop for you:

Discovery. You paste 1–5 artists you like. Their "Fans also like" artists are collected (eduair94/spotify-scraper), and so can be playlists, a country's Viral 50 or artist names.
The scan. Each candidate's public artist page is read by Spotify Play Count Scraper (beatanalytics/spotify-play-count-scraper) — monthly listeners, followers, top-10 tracks with streams, top cities, releases, socials and the bio. Both source Actors run on your Apify account, capped by a spend limit you set.
Free filters. Artists outside your listener band (default 1,000–500,000), with no release in the last year, outside your target countries or already delivered to you are dropped before anything is charged.
A scout score you can read. 0–100 from band fit, momentum (listeners vs followers), growth since your last run, release cadence, catalogue depth, socials and the verified mark — with the breakdown and risk flags such as one_hit or inflated_listeners.
Signing status with evidence. independent, signed or unknown, with the label line or the bio sentence that decided it.
An AI scouting note and pitch line (optional). Career stage, fit to your brief, bio facts quoted verbatim from the bio, a two-sentence note and a first DM that names a real track or city.

You pay per qualified artist, not per scanned row: $0.004 with rules only, $0.01 with the AI verdict, and the first 25 artists on every account are free.

Step by step

1. Run the free demo (30 seconds, $0)

Open https://apify.com/rich_minds/spotify-artist-scout-ai and click Try it. The form is pre-filled with 8 fictional sample artists, so the first run searches nothing and charges nothing. The demo finishes in seconds (measured 2026-09-27: 3.1 s, 6.1 s with the AI on). Our local run of it with the AI on — labelled sample verdicts, since the demo spends no tokens — returned these ranked rows:

Artist (sample)	Score	Tier	Monthly listeners	Growth	Top city	Signing
Maren Holt	91	hot	84,200	+36.9 %	London	independent
Nadia Okafor	78	hot	41,800	+15.8 %	London	unknown
Saoirse Vale	62	warm	6,900	first snapshot	Dublin	independent
The Lowlight Parade	58	warm	23,400	+6.8 %	Leeds	signed
Juno Park	52	warm	312,000	+7.6 %	Seoul	signed
KAYO & The Night Bus	34	cold	142,000	first snapshot	London	unknown

The artists are fictional and every row says so (isSample: true). The point is to see the columns before you spend anything.

2. Point it at your own taste

Replace the sample with 1–5 Spotify artist links in Artists like… (seedArtistUrls). If you have no seeds, pick a niche in preset (indie label UK / IE, playlist curator, booking agent) or write only scoutBrief — the markets and the artists it names become the seeds. Set the spend cap maxDiscoveryChargeUsd (default $0.50; five seeds reach it).

{
  "seedArtistUrls": ["https://open.spotify.com/artist/7Ln80lUS6He07XvHI8qqHH"],
  "scoutBrief": "Unsigned UK indie acts with a release in the last 6 months",
  "yourOffer": "Indie label in London",
  "targetCountries": ["GB", "IE"],
  "maxDiscoveryChargeUsd": 0.5
}

scoutBrief is what the AI scores each artist against; yourOffer is how the pitch line introduces you — used exactly as you wrote it.

3. Start, then read the Shortlist view

The dataset's Shortlist view is sorted best first: score, tier, listeners, growth, top city, signing status and the scouting note. Momentum & risks shows the listener / follower ratio, cadence and the one-hit share. Outreach puts the contact route (Instagram first, then TikTok, website, X, Facebook, YouTube, the Spotify page) next to the pitch line.

This is the top sample row with the AI verdict — the same shape your own artists get:

{
  "name": "Maren Holt (sample)", "fitScore": 91, "tier": "hot", "careerStage": "emerging",
  "monthlyListeners": 84200, "listenersGrowthPct": 36.9, "signingStatus": "independent",
  "scoreReasons": ["listenersGrowthPct +36.9 since the last snapshot", "primaryCity London — the brief's UK market"],
  "summary": "Self-releasing London alt-pop writer whose monthly listeners grew 36.9% in a week on the back of Glasshouse. Independent, releasing every two months and strongest in London, Manchester and Dublin.",
  "generatedText": "Hi Maren, Glasshouse has been on repeat here, and it is great to see London catching on. We're an indie label in London that signs and develops alt-pop acts - we fund recording and radio plugging. Open to a coffee?"
}

The AI is grounded: a bio fact needs a verbatim quote from the bio, a sentence with a number the data does not contain is removed, and cold artists get no pitch at all.

4. Schedule it weekly

After your first real run, open the saved task (OUTPUT.scheduleTaskUrl), click Schedule → weekly, and put your address into notifyEmail. With dedupeAcrossRuns on, every Monday you receive only new artists and growth alerts — artists you already have whose monthly listeners grew 20 % or more since the last run. A scheduled run also rolls up to five of last week's hot / warm artists in as new seeds, so week 3 explores new "Fans also like" ground instead of re-reading week 1. slackWebhookUrl or discordWebhookUrl post the same digest to your team channel.

What a run costs

Worked example (estimate — the live funnel is measured on 2026-10-15): five seeds give ≈ 100 related artists. The source Actors charge your account ≈ $0.10 for discovery and ≈ $0.40 for the scan (capped by maxDiscoveryChargeUsd). About 1 in 4 passes a typical band + momentum filter, so ≈ 25 qualified artists:

rules only: 25 × $0.004 = $0.10 here → ≈ $0.60 all in
with the AI: 25 × $0.01 = $0.25 here + ≈ $0.15 of tokens → ≈ $0.90 all in

The first 25 qualified artists on every account are free, so the first real run costs only the source scan. Weekly with the AI that is ≈ $3.60 a month. Artists below your minScore, outside a filter or already delivered are never charged by the Actor.

How that compares, fairly: the Spotify scrapers next to it in the Apify Store charge a median $0.00425 per scanned artist — about the same number, but for a raw row. One qualified artist here replaces ≈ 4 scanned rows you would sort by hand. If you only need raw counts for a known list of URLs, a raw scraper is the cheaper tool; this one is for finding and ranking.

Use it from code, n8n or an AI agent

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("rich_minds/spotify-artist-scout-ai").call(run_input={
    "seedArtistUrls": ["https://open.spotify.com/artist/7Ln80lUS6He07XvHI8qqHH"],
    "scoutBrief": "Unsigned UK indie acts with a release in the last 6 months",
    "maxQualified": 50,
    "maxDiscoveryChargeUsd": 0.5,
}, timeout_secs=3600)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["name"], item["score"], item["tier"], item["url"])

Upsert rows into your sheet or CRM on dedupeKey (id: + the Spotify artist ID), so a growth alert updates the artist's record instead of creating a duplicate. For Claude, ChatGPT or Cursor, add https://mcp.apify.com/?actors=rich_minds/spotify-artist-scout-ai as an MCP server and ask it to run the Actor with {} first (free) and then with your seed artists. An importable n8n workflow (Monday 08:00 → run → append to Google Sheets) is on the Store page's Integrations section.

Limits worth knowing

Public artist pages only: no login, no fan data, no guessed e-mail addresses. Not affiliated with Spotify.
Spotify shows the top 10 tracks and top 5 cities; play counts read 0 below 1,000 streams.
Growth needs a previous snapshot, so it appears from the second run on (or when you paste one in list mode).
The live scout runs two Store Actors on your Apify plan. On any plan you can still paste rows (sourceMode: list).
Signing status is unknown when neither the release label nor the bio says — followReleases reads the labels.

Try it

The demo is free on any Apify plan and your first 25 qualified artists are free: https://apify.com/rich_minds/spotify-artist-scout-ai — paste three artists you like and see who their fans are listening to next.

Spotify Artist Scout – Monthly Listeners, Play Counts, AI Score on the Apify Store →