Lumotia/docs/brief/success-metrics.md

9. Success Metrics

Business metrics

Milestone	Target
Beta testers recruited	10–15
Beta feedback: "same complaints repeating" threshold	Signal to stop beta, ship v1.0
Waitlist signups pre-launch	100+
First paid sale	Within 2 weeks of public launch
Revenue target (6 months)	£2K MRR (mix of lifetime + cloud subscriptions)
Revenue trigger to evaluate CORBEL roll-up	£500/month sustained

Neuro-inclusive product metrics

Standard SaaS metrics like Daily Active Users (DAU) or unbroken streaks must be avoided — they encourage the exact shame spiral Kon is designed to prevent. Track these instead:

Metric	What it measures	Why it matters
Time-to-capture	Seconds from app open to completed brain dump	Measures friction. If this exceeds 10 seconds, the thought is gone. The lower this number, the better Kon serves its core purpose.
Grace day recovery rate	% of users who return and complete a task after 1+ days of inactivity	Proves Kon has beaten the abandon-shame cycle. This is the single most important product metric. If users come back after missing days without guilt, the design is working.
Micro-step completion rate	Completion rate of AI-decomposed tasks vs. manually entered abstract tasks	Validates that micro-stepping actually works. If AI-generated steps have higher completion rates than user-entered tasks, the feature is earning its keep.
Brain dump → task conversion	% of voice transcription content that converts into actionable tasks	Measures AI quality. Low conversion means the AI isn't parsing well; high conversion means the core loop works.
Return after lapse	Median days between last session and next session for users who go inactive	Measures stickiness without punishing breaks. A user who returns after 2 weeks is a success, not a failure.