retention-lab
Your retention data,
decoded.
Deconstruct any YouTube video's retention patterns with AI. Draft hooks and outlines calibrated to the retention shape of what actually works in your niche.
Open source · today
Local CLI. Finds top videos on a topic, builds a proxy retention curve from public signals, compares your draft, outputs timestamped edit notes. Proxy — not real retention. GitHub →
Hosted · coming
OAuth your channel. Real retention curves from YouTube Analytics. Copilot that drafts hooks and edits against your actual audience's drop-off patterns. Waitlist →
Live demo
What the tool actually outputs.
Analyzed with retention-lab v0.1 (open source). Input: one YouTube URL.
Veritasium · 20:57 · 18.4M views
The Surprising Secret of Synchronization
Retention shape (proxy)
Key moments
- 0:00-0:15
hook
Opens with a stated impossibility — viewer wants to see the resolution. Classic hook pattern.
- 3:45
retention dip
Retention dips ~8% here — matches a slow mathematical explanation. Consider a visual metaphor or callback.
- 8:20
recovery
Reveal moment + camera cut to reaction shot recovers retention.
Edit suggestions
- Tighten 3:30-4:15 by 20%. The math detour loses ~8% of viewers with no recovery until 8:20.
- Add a visual callback to the opening impossibility at 6:00 to re-anchor the narrative thread.
- Your cold-open works — replicate the 'stated impossibility → reveal' pattern in your next video.
Run it yourself: pip install retention-lab && retention-lab deep-dive <url>
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Pricing (planned)
Simple, creator-friendly.
Free
$0
- · Local CLI forever
- · Community support
- · Open source
Pro
$29/mo
- · Real retention curves
- · AI Copilot drafts
- · Web workspace
- · Email support
Studio
$99/mo
- · Everything in Pro
- · Managed agents (later)
- · Unlimited channels
- · Priority queue