AI Demo Feedback & A&R Scout
Inspiration:
Fiverr hosts many "professional song feedback" gigs—artists pay for objective critique. Simultaneously, label A&R teams are swamped by demo submissions.
Target Customers:
Two-sided: indie musicians wanting expert feedback & exposure; label A&R managers seeking high-potential tracks.
Pain Points:
- Artists: Hard to get unbiased, high-quality feedback; friends are too polite, paid reviews vary wildly; zero pathways to labels.
- A&R: Manually listening to thousands of demos is inefficient and subjective fatigue causes missed gems.
Solution (Micro-SaaS):
AI-powered song analysis & filtering hub.
- For artists: Upload a track and receive a "health report" covering structure, production quality (mix/master), lyric depth, plus a market-based "hit potential" score and actionable tips.
- For A&R: A dashboard to set filters (e.g., "pop potential > 80, female-vocal Billie-Eilish vibe") and instantly surface matching demos.
MVP Core Features:
- Song upload & analysis for artists.
- Visualised report with sections & scores.
- A&R filter dashboard with genre/potential sliders.
- Anonymous preview before contacting artists.
Development Effort (Tech Implementation): High—building a reliable "hit potential" model is tough.
- Lyrics: GPT-4/Claude for thematic analysis.
- Audio:
librosa
for BPM, loudness, harmony; traditional ML or small CNNs for production quality. - NLP:
transformers
for report generation.
Traffic Acquisition & Validation (SEO Enhanced):
- Step 1 – Validation: Build a small invite-only artist pool; demo the dashboard to 3–5 A&R managers.
- Step 2 – SEO Growth: Head terms: "AI song feedback", "demo submission platform"; blog with success stories.
Competitor Analysis: SoundCloud submissions, LABELRADAR, human review gigs.
Our edge: scalable AI triage, objective scoring, and fast lane to the right ears.