Our 60-day forecasting model consistently performs within ±20% variance — up to 30% more accurate than major-label analytics and legacy tools.
Stakeholders see accuracy, variance, and metrics — not buzzwords.
Measured superiority, not perfection. It makes the ±20% claim believable.
Everyone says “AI-powered.” Few show predictive precision. We do.
Anchor for every deck: “Here’s the industry. Here’s us.”
Lower variance means higher confidence. Shorter bars indicate better predictive precision.
| Metric | Industry Average Variance | SoundScope Analytics Variance |
|---|---|---|
| Spotify Streams | ± 25 – 35 % | ± 18 – 22 % |
| Apple/Amazon Streams | ± 30 – 40 % | ± 20 – 25 % |
| Paid Downloads | ± 25 – 30 % | ± 18 – 20 % |
| TikTok Virality | ± 35 – 45 % | ± 25 – 30 % |
| Revenue Forecast | ± 25 – 30 % | ± 20 – 25 % |
We blend modern ML (embedding models for audio/lyrics) with robust baselines and ensemble methods. “AI-powered” is the toolset; precision is the outcome.
Per-prediction explanations identify the top contributing signals so A&R and finance can act on what actually moves the forecast.
Versioned models, audit logs of changes, and cohort monitoring keep variance stable across genres and time.
Customer retains rights to audio, lyrics, and metadata. We use data only to provide services and improve models under contract. We do not sell or share PII.
Access controls, least-privilege principles, and environment isolation. Production data is restricted to authorized personnel for support and monitoring.
Send an emerging artist or a small slate. We’ll return a comparison brief with forecasts, drivers, and next best actions.