strategy: rewrite section 13 milestones to board-distribution model

Replace stale timeline targets with Ty's direction: prime the pump
through a Chamber of Commerce or Tourism Board partnership, use
member businesses as the first customer segment, and make the
conversational SSP the compelling wow experience that wins
returning customers.

Old milestones assumed a form-wizard portal and endpoint counts
(100, 1000, 10000) that predated the conversational SSP pivot and
the refined MVP scope. New milestones track distribution-first
activation through board trust, then prove the loop, then scale.

Signed-off-by: Ty <tybala@outlook.com>
Co-authored-by: Ty <tybala@outlook.com>

docs/strategy/CANONICAL_STRATEGY.md

@@ -1,6 +1,6 @@
 # geolocal.io — Canonical Strategy
 
-**Status:** Final draft (2026-07-18; revised same day for strategic depth and local-retail scope)  
+**Status:** Final draft (2026-07-18; revised 2026-07-29 for conversational SSP, §13 milestones aligned to board-distribution model)  
 **Role:** The document the team plans, builds, and sells against. When other docs disagree with this one, update them — or update this one deliberately. Do not leave the conflict hanging.
 
 This is an operating strategy, not a product brochure. The Self-Service Portal matters, but it is one activation surface. The company is the platform underneath.
@@ -352,32 +352,40 @@ Tourism board deals use separate pilot or enterprise pricing. Do not block launc
 
 ## 13. What success looks like
 
-### First 90 days
+### First 90 days — prime the pump
 
-- Public multi-tenant MCP over HTTP  
+Distribution before direct sales. Land one Chamber of Commerce or Tourism Board partnership and use their member businesses as our first customer segment. The board is the trust signal; the messages come from us and them:
-- Portal spine good enough to activate real owners (scrape, simulation, pointer, preflight)  
-- About 100 live endpoints  
-- One tourism or destination pilot at LOI or live pilot  
-- One or two genre packs  
-- Booking path via Cal.com (link first is acceptable)  
-- First dollars of ARR  
-- Explicit quality rules written (even if enforcement is still manual)
 
-### By 180 days
+- **Services:** "Make every AI assistant understand and book your business."
+- **Retail:** "Make sure AI can tell people what you actually carry and why you're worth the stop."
 
-- About 1,000 endpoints  
+**Concrete targets:**
-- Three genres  
+- One Chamber or Tourism Board at pilot (LOI signed, member list in hand)
-- Related-businesses handshake in production  
+- Conversational SSP live and shippable — the **wow experience** owners feel on first interaction
-- Several intermediate dashboards active  
+- First cohort of member businesses activated through the board (not cold outbound)
-- Telemetry useful for real owner reports  
+- HTTP MCP transport in production with multi-tenant routing
-- First decommission or quarantine decisions made with a documented standard
+- Enough live endpoints to show a working registry, not just a demo
+- First dollars of ARR from the pilot
 
-### By 360 days
+The SSP is the win moment. Owners arrive from the board, describe their business in a chat, and within one session see a visual simulation of an AI assistant recommending them — services listed, booking path found, details correct. That experience is what makes them stay.
 
-- About 10,000 endpoints  
+### 180 days — prove the loop
-- Several major chamber or tourism partnerships  
+
-- Early anonymized demand or data product in beta or market  
+- Second Chamber or Tourism Board partnership (different geo or vertical)
-- Case studies showing assistants prefer geolocal-backed paths in pilot geos  
+- Self-serve SMB motion running in parallel (not just board-distributed)
+- Telemetry showing agents prefer geolocal-backed paths in pilot geos
+- Owner reports that drive returning visits — "here's what changed, here's what to fix"
+- Quality standards documented and first decommission or quarantine decisions made
+- Genre packs for at least two verticals (services first, retail next)
+- Booking path deeper than redirect (Cal.com or peer integrated)
+
+### 360 days — scale the model
+
+- Several major chamber or tourism partnerships active
+- Service graph effects visible — related businesses, demand patterns, competitive context
+- Telemetry and quality enforcement (including decommissioning) as a trust moat
+- Early anonymized demand or data product in beta
+- Case studies showing assistants prefer geolocal-backed paths  
 
 ---