Music Virality

Chart prediction grounded in listener and creator behavior.

Identify tracks that will hit before they chart. Surface signal from streaming, short video, and creator platforms in one calibrated index.

Start free with Music ViralitySee pricing

How it works

The exact thing your team is trying to call.

Probability a track enters the top 200 within 28 days of release, with a separate forecast for short-video adoption velocity. KPIs ship with confidence chips when evidence is thin.

  • Cross-platform virality index spanning DSPs and short video
  • Creator-led adoption tracking by audience size tier
  • Genre-conditioned analog matching
  • Geographic spread prediction by market
  • Sync and licensing fit scoring

Signal sources

What feeds the music virality model.

  • 01NewsAPI music coveragelive
  • 02Reddit music subredditslive
  • 03Google News RSSlive
  • 04Spotify and Apple Music listener panelsplanned
  • 05TikTok and Reels sound usageplanned
  • 06YouTube Shorts track adoptionplanned
  • 07Shazam discovery signalplanned
  • 08Genius lyric search activityplanned
Sample entities tracked:Indie Pop SingleHip-Hop Album CutLatin Crossover

Use cases

What teams actually do with Music Virality.

  • Greenlight reviews for music virality

    Run scoring on a portfolio of candidates and surface the ones whose music virality signals diverge most from their internal narrative.

  • Continuous monitoring

    Subscribe via webhook and receive a payload only when the score crosses a threshold you defined. No dashboards required.

  • Cross-vertical analysis

    Pull the same entity into other verticals to see whether the signals agree or disagree. Disagreement is often where the alpha is.

  • Backtesting before commitment

    Score the last 24 months of decisions against the model and compare hit rates. The calibration_bucket field tells you how much to trust the model in the bands you care about.

API

Calibrated, explainable, ready for production.

Catalogue calls return 40 realistic KPIs grounded in real evidence, each with a confidence chip (high / medium / low / unknown). Every prediction also ships with the nearest historical analogs the model leaned on.

Available via REST and a typed TypeScript SDK.

See full API reference
GET /v1/catalogue/music-virality/{entityId} — 40 realistic KPIs
{
  "entityId": "trk_98fd2",
  "kpiCountScored": 40,
  "pTop200": 0.67,
  "ci95": [
    0.51,
    0.81
  ],
  "shortVideoVelocity": 142,
  "kpis": [
    {
      "id": "creator_adoption_rate",
      "value": 0.12,
      "confidence": "medium",
      "citations": 4
    },
    {
      "id": "save_to_play_ratio",
      "value": 0.08,
      "confidence": "low",
      "citations": 0
    },
    {
      "id": "genre_freshness_index",
      "value": 0.05,
      "confidence": "high",
      "citations": 9
    },
    {
      "id": "label_marketing_spend",
      "value": 0.04,
      "confidence": "low",
      "citations": 0
    },
    {
      "id": "competitor_release_window",
      "value": -0.03,
      "confidence": "medium",
      "citations": 2
    }
  ],
  "analogs": [
    "trk_3a18c",
    "trk_7bc02",
    "trk_d4e91",
    "trk_22f0a",
    "trk_8c113"
  ],
  "asOf": "2026-05-10T00:00:00Z"
}

Compared to

How Music Virality differs from what is already out there.

VendorHow SignalGrid is different
ChartmetricProbability of charting in 28 days, not only retrospective dashboards.
SoundchartsShort-video adoption velocity built in as a primary signal.
ViberateGenre-conditioned analog matching with confidence intervals.

Try Music Virality on your own entities.

Start free during the public beta. We will pre-select music virality for you on signup.

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