Pokemon Go meets environmental data infrastructure. A consumer game that becomes a brand accountability platform and municipal intelligence product.
Every photo a user takes feeds all three layers. The consumer game creates the data. The brand layer monetizes the data. The municipal layer sells the data.
Camera-first. Snap litter, AI classifies it, earn XP. The Snapchat navigation model: swipe between camera, map, feed, and profile.
XP is reputation, not currency. You never spend it. You accumulate it. Higher XP unlocks titles, badges, territory guardian status, and eligibility for brand bounty payouts.
| Action | XP | Why |
|---|---|---|
| Photograph litter | +10 | Base reward for every pick |
| AI identifies brand | +5 | Brand data is the most valuable data point |
| GPS captured | +5 | Location data enables map/heatmap features |
| 3+ day streak active | +5 | Retention mechanic, loss aversion |
| Maximum per pick | 25 | Achievable every time if GPS + brand + streak |
Start as a Progressive Web App. Validate demand. Wrap in a native shell when you hit 1,000+ active users. Here's the exact path.
The pitch is simple: "We have photographic evidence that your products are the #1 litter in [city]. You can either clean it up through our bounty program, or we'll publish the data."
Public, auto-generated rankings of which brands produce the most litter in each city. Updated in real-time from user picks. This is the leverage.
Don't pitch bounties cold. Build the data first, then approach with evidence.
Hi,
I run LitterMap, a mobile app where people photograph and clean up litter. We have 2,400 active users across Tennessee.
We've built a bounty system that pays users to pick up specific brand products. Here's the offer:
You fund a bounty at $0.25/verified pickup. We handle photo verification, GPS logging, and payouts. Your monthly report shows exactly how many products were cleaned up, where, and the reduction trend over time.
The alternative is that this data stays public. We publish monthly city-level brand rankings. Local media has already covered our Nashville data.
Happy to walk you through the dashboard. 15 minutes?
Mitchell Wilson
Founder, LitterMap
Stripe Connect Express handles the hard parts: KYC, 1099s, bank transfers. LitterMap is the marketplace platform. Users are the service providers.
This is the same system Uber, DoorDash, and Etsy use. You are the "platform." Users are "connected accounts." Stripe handles identity verification, tax forms, and bank payouts.
When real money is involved, people will try to game the system. Multiple layers of defense:
| Layer | What it catches | How |
|---|---|---|
| Level gate (L5+) | Drive-by account creation | Must earn 500+ XP with legitimate picks before claiming bounties |
| GPS cooldown | Same-spot farming | Can't claim two bounties within 100m in the same hour |
| Photo hash | Duplicate photo resubmission | Perceptual hash comparison against all prior photos |
| AI verification | Non-litter photos | Vision model confirms the photo actually contains litter of the claimed type and brand |
| Rate limiting | Superhuman picking speed | Max 50 bounty claims per day. Flagged for review above 30. |
| Peer review (L26+) | AI misses | High-level users validate flagged picks. Consensus of 3 needed. |
The biggest liability: someone walks into traffic while snapping litter. This is the Pokemon Go lesson. Every design decision must account for it.
Cities spend millions on litter cleanup with zero data on where it's worst. LitterMap gives them heatmaps, trends, and hotspot alerts for a fraction of one cleanup crew's salary.
| Tier | What they get | Price |
|---|---|---|
| Free | Public Wall of Shame data for their city | $0 |
| Starter | Monthly PDF report (hotspots, trends, brand breakdown) | $200/mo |
| Pro | Live dashboard, API access, custom alerts, heatmap overlays | $500/mo |
| Enterprise | Multi-city, custom integrations, dedicated support | $1,500/mo |
Three growth engines, each feeding the next. Local first, then regional, then viral.
Four revenue streams. Brand bounties first, municipal SaaS second, data licensing third, sponsored challenges fourth.
| Revenue Stream | When | Year 1 Target | Year 2 Target |
|---|---|---|---|
| Brand bounty platform fee (20%) | Month 6+ | $10,000 | $80,000 |
| Municipal SaaS subscriptions | Month 8+ | $6,000 | $60,000 |
| Data licensing (aggregated, anonymized) | Year 2 | $0 | $25,000 |
| Sponsored cleanup challenges | Month 9+ | $4,000 | $20,000 |
| Total | $20,000 | $185,000 |
What to build and when. Validation before features. Revenue before scale.
The app is simple. The moat is the data.
| Risk | Severity | Mitigation |
|---|---|---|
| Nobody downloads it | High | Validate with 500 signups before building. If can't get 500 in 30 days, concept needs rethinking |
| User gets injured | High | Safety UI from day one, ToS liability disclaimer, general liability insurance, no location-specific bounties |
| Brands ignore the Wall of Shame | Medium | Partner with environmental journalists. Public data + media pressure is harder to ignore than a cold email |
| Fraud on bounties | Medium | Multi-layer anti-fraud (level gate, GPS cooldown, photo hash, AI verification, peer review). Start small, iterate |
| Mitchell's time (running Tare full-time) | Medium | 15-20 hrs/week max. Side quest rules apply. Don't let it compete with Tare operations |
| Stripe Connect rejection | Low | Apply early (month 1). LitterMap's model (paying service providers) is standard for Connect. Not a novel use case |
| Apple App Store rejection | Low | Add at least one native feature to avoid "web wrapper" rejection. Push notifications are the easiest |
| Legal challenge from brands | Low | Data is factual and aggregated. "35% of litter is Coca-Cola" is a verifiable statement, not defamation. Get a legal review before publishing |
Built by Mitchell Wilson. Powered by Claude Code.
Internal strategy document. April 2026.