FaceKit
🔥MRRdeals Score · 80/100 · Top 2%What this SaaS is
FaceKit analyzes users’ faces and provides looksmaxxing assessments through a consumer mobile app.
- Face analysis
- Looksmaxxing assessments
- Backend user data
- Founded <12mo ago— Less than 12 months of operating history. Retention is unproven.
Numbers that matter
Mobile app
Apple and Google keep 15–30% of subscriptions: check whether the revenue and margin above are before or after the store commission, and plan the transfer of the app and its subscriptions through App Store Connect or Google Play.
Tech stack
Score breakdown
How the composite score above splits across seven independent signals. Each axis is graded 0-100. Hover for details.
Payback at the stated margin, asking multiple vs the category median, and profit margin. The heaviest axis: what you pay for what it earns.
Revenue trend over the last ~90 days from our daily snapshots (30-day figure when history is short), capped so one spike can't dominate, minus a penalty for erratic revenue.
Paying customers, revenue scale and traffic (log scales), plus live-site health (reachable pricing page, core pages, maintained site).
AI-disruption risk, organic search presence, recurring B2B revenue; penalties for thin AI wrappers and no-code lock-in.
How turnkey the takeover is: diversity of marketing channels, Merchant-of-Record status, team.
Higher = safer. Business age, breadth of the customer base (concentration risk), recurring vs one-off revenue, known payment provider.
Structured market read across TAM, saturation, 3-year trend, and hype cycle, blended with our category momentum signal.
Market read
- TAMmid
The looksmaxxing niche has a moderate user base, indicating a mid-sized total addressable market.
- Saturationgrowing
The market is still developing with few strong competitors, suggesting a growing saturation level.
- 3y trendgrowing
Consumer interest in personal appearance apps has increased, indicating a growing trend over the past three years.
- AI disruptionvulnerable
The app's reliance on unique data makes it somewhat vulnerable to competitors who could replicate features easily.
- Hype cycleearly
The concept is still emerging, placing it in the early stage of the hype cycle.
Run the numbers
Before you make an offer
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