diff --git a/docs/strategy/CANONICAL_STRATEGY.md b/docs/strategy/CANONICAL_STRATEGY.md new file mode 100644 index 0000000..1200c3b --- /dev/null +++ b/docs/strategy/CANONICAL_STRATEGY.md @@ -0,0 +1,372 @@ +# geolocal.io — Canonical Strategy + +> **Status:** Refined GM strategy (2026-07-18) +> **Source of truth for vision:** `docs/geolocal-copilot-conversation.md` +> **This document:** Condenses, stress-tests, and operationalizes that vision with current market evidence. +> **Supersedes:** Fractured narratives in older GTM/investor/engineering docs where they conflict. + +--- + +## 1. One-line company definition + +**geolocal.io is the business-owned MCP infrastructure that makes local service businesses discoverable, interpretable, bookable, and measurable inside every AI assistant — the Shopify Storefront MCP equivalent for the long tail of local services.** + +Not a destination site. +Not a chatbot sold to SMBs. +Not a Yelp/Google clone. +Infrastructure that AI agents use, that businesses own, that partners and tourism boards distribute. + +--- + +## 2. The problem (evidence-checked) + +### 2.1 Demand side: consumers already moved + +- BrightLocal’s 2026 Local Consumer Review Survey: **~45% of consumers use AI tools for local business recommendations** (ChatGPT is the leader among tools cited). +- BrightLocal and secondary coverage also reference a much lower prior-year figure (~6%); treat the directional leap as real, but do **not** overclaim a perfect YoY methodology match in investor materials without footnoting survey differences. +- X / practitioner discourse (2026): local discovery is collapsing into **1–3 named recommendations**, not a page of links — “if you’re not named, you’re invisible.” + +### 2.2 Supply side: AI is radically selective + +- SOCi 2026 Local Visibility Index (≈350k locations / 2,751 multi-location brands): + - **ChatGPT recommended ~1.2% of brand locations** + - Gemini ~11%, Perplexity ~7.4% + - vs ~36% appearance in Google local 3-pack +- Locations recommended by ChatGPT skew high-trust (**~4.3★ average**). +- BrightLocal research: **Yelp is a frequent source** in AI local answers (~1/3 of searches in one study); listings/citations regained importance under LLMs. + +**Implication:** Traditional local SEO is necessary but insufficient. Structured, machine-actionable presence is becoming the bottleneck. + +### 2.3 Structural gap incumbents will not fill for SMBs + +| Player | What they are building | What they are NOT building | +|--------|------------------------|----------------------------| +| **Shopify** | Storefront MCP live on every store (`/api/mcp`); UCP with Google; Catalog MCP | MCP for non-Shopify local service businesses | +| **Yelp** | Official open-source **Yelp MCP** over Fusion AI — *their* data for agents | Business-owned endpoints businesses control | +| **Google** | Maps Grounding / Merchant MCP (alpha); AI in Maps/Search; UCP commerce | Neutral, multi-tenant “own your AI presence” for long-tail SMBs | +| **Cal.com** | Full **booking MCP** (create/reschedule/cancel/availability) | Discovery, story, genre primitives, tourism aggregation | +| **OpenAI / Anthropic / others** | Agent platforms + data licensing | Local service graph for the 98%+ long tail | + +**Thesis (validated):** Incumbents build MCP for *their* platforms and *their* data. The long-tail service economy (Bob’s Garage, local charters, salons, tourism boards) has no Shopify-equivalent on-ramp. That vacuum is geolocal.io. + +--- + +## 3. North Star (from the copilot conversation — preserved) + +**Make AI give the most relevant and helpful local recommendation — and fulfill it — for local service businesses.** + +Helpfulness (not mere relevance) is the optimization target: clear services, specialization, pricing signals, availability, booking path, trust, and **repeatable success** so AI engines prefer the same path next time. + +--- + +## 4. Four business models (do not collapse these) + +The copilot conversation defines **four stacked models**. Earlier repo docs mostly documented Model 1. That fracture is fixed here. + +| # | Model | Who pays / who adopts | What geolocal provides | Horizon | +|---|--------|------------------------|------------------------|---------| +| **1** | **Endpoint enablement** | Individual SMBs (self-service) | Hosted multi-tenant MCP + `/.well-known` pointer + Self-Service Portal (SSP) + diagnostics + reports | Day 0 | +| **2** | **Intermediate enablement** | Tourism boards, chambers, visitor bureaus | Aggregating MCP for destinations/members; member onboarding; municipal ROI narratives | V1 GTM wedge | +| **3** | **Industry trust layer** | Standards / partnerships / platforms | Quality primitives, decommissioning, genre norms — become a preferred discovery surface AI engines learn to trust | 12–24 mo | +| **4** | **Service graph** | Data products / licensing | Network of related services, specialties, demand signals, competitive intelligence (“Citysearch 2.0, AI-native”) | After critical mass | + +**Rule:** Product decisions must state which model they serve. Do not build Model 4 features before Model 1–2 work. + +--- + +## 5. Product definition (what we actually sell) + +### 5.1 What we sell + +**AI-readiness infrastructure for local services:** + +1. **Hosted multi-tenant MCP** — structured tools AI agents call (story, services, hours, booking path, related businesses, genre primitives). +2. **Dead-simple discovery pointer** — business drops a tiny well-known JSON / path on their site that points at geolocal (Shopify pattern: endpoint on *their* domain, logic hosted). +3. **Self-Service Portal (SSP)** — the real product surface for SMBs (see §5.2). +4. **Orchestration, not reinvention** — Cal.com (booking MCP already exists), Stripe (payments). We do not replace them. +5. **Telemetry + optimization reports** — “how often AI hit you, what they asked, what your site failed to answer, what local demand looks like.” +6. **Partner / intermediate surfaces** — agencies, SEO shops, tourism boards, chambers. + +### 5.2 Self-Service Portal (SSP) — primary product experience + +From the founder narrative (canonical UX): + +1. Business lands on geolocal.io, describes business → **genre-aware onboarding** (auto repair vs surf shop vs charter). +2. **Initial site scrape** → reflect back what the system already “sees.” +3. **Live “phone + chat” simulation** — show ChatGPT-style flow: recommend the business, list services, book a time (e.g. Thursday 3pm transmission filter). Instant aha: *pre-qualified, scoped, calendar-aligned demand*. +4. Install **tiny pointer** on site. +5. **Preflight / test run** in-browser against *their* MCP — if AI can’t see services, they fix content or portal data before going live. +6. **Upstream guidance** (discovery: GBP, NAP, FAQ, plain-text city+service) + **downstream guidance** (MCP content quality). +7. Optional **partner referral** for website help. +8. **Weekly/monthly reports** — interaction counts, intents, local demand signals. + +**Critical clarification (founder):** We are **not** selling them a chatbot for their customers. The portal’s HTML chat is a **test harness** wired to their MCP so owners can see how *external* AIs will interpret them. + +### 5.3 Genre-specific primitives + +Generic `get_business_info` is MVP scaffolding only. Differentiator is **genre systems**: + +- Auto: makes/models, specialties (Korean transmissions), emergency flags +- Beauty: services, duration, stylist notes +- Home services: service radius, emergency, estimate vs fixed price +- Tourism activities: seasonality, capacity, weather sensitivity +- Intermediate (tourism board): member directory + category routing + +Roadmap must version **genre packs**, not only generic tools. + +### 5.4 What we explicitly do NOT build (V1–V2) + +- Consumer destination app +- Competing with Calendly/Cal.com/Square booking engines +- Competing with Stripe/Square payments +- Replacing Google Business Profile +- Building a Yelp review network +- Boiling the ocean on travel (AirBNB/Kayak space) — stay complementary + +--- + +## 6. Positioning + +### 6.1 Category + +**AI-readiness infrastructure / agentic local commerce infrastructure** + +Analogies that work in sales: + +| Analogy | Why it lands | +|---------|----------------| +| **Shopify Storefront MCP for local services** | Best single analogy; founders and partners get it immediately | +| **Stripe for AI discovery/booking presence** | Infrastructure, not UI | +| **Twilio for local service tools** | Agents call APIs; business doesn’t rebuild stack | + +### 6.2 Messaging (use this) + +- **Owner:** “Make every AI assistant understand and book your business.” +- **Tourism board:** “Turn lodging tax dollars into AI-discoverable local experiences your members own.” +- **Agency/partner:** “Add AI-readiness as a productized line — not another chatbot retainer.” +- **Investor:** “Neutral MCP layer for the 98%+ of local services AI currently skips, sold via self-serve + municipal distribution.” + +### 6.3 Anti-messaging (do not say) + +- “AI chatbot for your website” +- “Replace Google / Yelp” +- “SEO tool with AI features” (we can *include* discovery guidance, but category is infrastructure) + +--- + +## 7. Go-to-market (refined) + +### 7.1 Primary V1 wedge: tourism / destination intermediaries + +**Why (copilot + market logic):** + +- Hotel/lodging taxes create **mandated promotion budgets**. +- Boards often **must spend** and openly solicit ideas — confused buyers with money. +- One intermediate win → **dozens/hundreds of endpoints** (members). +- Travel has high AI referral growth narrative (industry reporting of strong AI travel referral growth 2024–2025). +- Physical brochure racks prove the *intent* for local discovery; geolocal is the AI-native equivalent. + +**Motion:** + +1. Pick **1–2 destination markets** (illustrative: coastal FL tourism board style markets already used in founder narrative). +2. Sell **board-level pilot**: destination MCP + member onboarding SSP + simple ROI dashboard (member AI hits, category demand). +3. Fund via tourism marketing budgets / innovation RFPs / “AI visitor experience” framing. +4. Members get free/discounted endpoint for pilot period → convert to paid. + +### 7.2 Parallel motion: self-service SMB endpoint + +- Verticals for first genre packs: **auto repair, beauty, home services** (home services align with high-intent AI queries; tourism activities if destination wedge). +- Price band (direction from copilot pricing discussion, infrastructure framing): + - **Starter ~$49/mo** + - **Core ~$129/mo (anchor)** + - **Pro ~$249/mo** +- Position above DIY “chatbot” tools; below enterprise multi-location AI visibility platforms (SOCi class). + +### 7.3 Secondary motion: partners (agencies, SEO, web shops) + +- Not the *product* owner narrative; they are **distribution** and **implementation**. +- Partner marketplace when SSP shows “your website needs work — self-serve or partner?” +- Commission / wholesale pricing TBD after first 50–100 endpoints. + +### 7.4 Explicit non-wedge + +- Do not lead with “compete in national multi-location brand AI visibility” (SOCi’s world). +- Do not lead with pure e-commerce (Shopify already owns that MCP). +- Do not lead with pure B2B / non-local. + +--- + +## 8. Competitive strategy + +### 8.1 Who fills the vacuum? + +| Actor | Likely path | Our response | +|-------|-------------|--------------| +| **Yelp** | Become default AI source of truth via MCP + licensing | Offer **business-owned** data + booking path Yelp doesn’t control; complementary where agents need owner truth | +| **Google** | Maps + Merchant + UCP | Stay complementary; deep GBP guidance; don’t fight Maps for UI | +| **Shopify** | Expand agentic commerce | Partner pattern, don’t compete; copy their **well-known endpoint on merchant domain** UX | +| **Cal.com / Square / Vagaro** | Booking MCPs | Integrate; own discovery + genre + intermediate + graph | +| **AI visibility SaaS (SOCi, BrightLocal AI tools)** | Measure/optimize multi-location | Different buyer (enterprise brands); we own long-tail endpoints + tourism | +| **Local agencies** | Manual AEO/GEO retainers | Make them partners; productize what they can’t scale | + +### 8.2 Moats (in order of build) + +1. **Endpoint density** in target geos/genres (critical mass for Model 3–4) +2. **Genre primitive quality** AI engines prefer (helpfulness repeatability) +3. **Telemetry flywheel** (demand signals → better recommendations → more attach) +4. **Intermediate contracts** (tourism/chambers lock distribution) +5. **Trust/quality enforcement** (decommission bad actors; freshness) + +Freshness moat vs Foursquare: demand is continuous booking/intent from the service economy, not social check-ins. + +--- + +## 9. Pricing principles (SMB self-serve) + +| Tier | Monthly | Includes (V1 intent) | +|------|---------|----------------------| +| Starter | ~$49 | MCP endpoint, SSP test page, monthly report, basic diagnostics | +| Core | ~$129 | Full MCP, live SSP preflight, weekly reports, local demand insights, partner access | +| Pro | ~$249 | Multi-site, advanced telemetry, competitor signals, priority support | + +**Add-ons later:** partner install, advanced analytics, multi-location. +**Tourism board:** separate enterprise/pilot pricing (per-destination + per-member), not SMB list price. + +**Do not** price as chatbot usage; price as **infrastructure + BI**. + +--- + +## 10. Success metrics (what GM tracks) + +### 10.1 90 days + +| Metric | Target (planning bar) | +|--------|------------------------| +| Public multi-tenant MCP (HTTP) live | Yes | +| SSP MVP (onboard + scrape reflection + preflight sim + pointer install) | Yes | +| Live endpoints | 100 | +| Tourism board / destination pilots | 1 signed LOI or pilot | +| Genre packs | 1–2 (e.g. auto + tourism activity) | +| Booking path | Cal.com link or Cal.com MCP orchestration (not rebuild) | +| Paying | First $ ARR even if small — proves willingness | + +### 10.2 180 days + +| Metric | Target | +|--------|--------| +| Endpoints | 1,000 | +| Genres | 3 | +| Related-businesses handshake in production | Yes | +| Intermediate dashboards | 3+ boards/chambers active | +| Agent telemetry usable for reports | Yes | + +### 10.3 360 days + +| Metric | Target | +|--------|--------| +| Endpoints | 10,000 | +| Major CoC / tourism partnerships | 3+ | +| Early DaaS / anonymized demand product | In market or beta | +| Evidence AI engines prefer geolocal paths in pilot geos | Case studies | + +--- + +## 11. Product / technical priorities (strategy-level only) + +Aligned to copilot “user stories before architecture”: + +**P0 — Prove Model 1** + +1. HTTP MCP transport (agents are remote; stdio is not the product) +2. Multi-tenant routing by business slug/domain +3. SSP: signup → scrape → simulation → pointer → preflight +4. Manifest / well-known generator +5. Seed genres + real pilot businesses +6. Cal.com path (redirect first; API/MCP next) + +**P1 — Prove Model 2** + +7. Intermediate (tourism) MCP + member aggregation +8. Board dashboard: members, hits, categories +9. Pilot paperwork + data agreements + +**P2 — Feed Models 3–4** + +10. Telemetry pipeline + owner reports +11. Related businesses tool + quality rules +12. Genre pack expansion +13. Partner marketplace + +**Explicit defer:** white-label everything, OAuth complexity beyond need, public developer platform, full DaaS, WordPress plugins (until attach rate demands them). + +--- + +## 12. Risks (steelman) + +| Risk | Severity | Mitigation | +|------|----------|------------| +| Yelp/Google become “good enough” AI local sources | High | Own business truth + booking + genre depth; intermediates; owner control narrative | +| SMBs don’t care until bookings prove ROI | High | SSP aha demo; tourism funded pilot; reports show demand; partner installs | +| MCP / discovery standards shift | Medium | Follow Shopify/Yelp well-known patterns; multi-path discovery | +| Market stats overstated in pitch | Medium | Cite SOCi/BrightLocal carefully; separate “multi-location study” vs “all SMBs” | +| Scope creep into chatbot / marketplace | High | North Star discipline; weekly “are we infrastructure?” review | +| Technical overbuild before SSP | High | No new tools without SSP path to value | +| Tourism procurement slow | Medium | Parallel self-serve SMB + short pilot contracts | + +--- + +## 13. Document governance (end the fracture) + +| Document | Role | +|----------|------| +| `docs/geolocal-copilot-conversation.md` | Foundational founder narrative (historical truth) | +| **`docs/strategy/CANONICAL_STRATEGY.md` (this file)** | **Operating strategy — team rallies here** | +| `NORTH_STAR.md` | Short public/internal compass — must match this file | +| `docs/gtm/*` | Execution detail — must not invent a different company | +| `docs/investors/*` | External packaging of *this* strategy | +| `docs/engineering/*` | Build plan for P0–P2 above | +| `code/` | Implementation of P0 | + +**Rule:** If a doc conflicts with this file, this file wins until the GM revises it. + +--- + +## 14. Near-term decisions for the leadership team + +1. **Adopt this document** as the single operating strategy. +2. **Rewrite NORTH_STAR.md** to include four models + tourism wedge + SSP (not partner-dashboard-first only). +3. **Retire or mark “stale”** any GTM doc that makes partner dashboard the only product or collapses four models to one. +4. **Lock V1 markets:** choose destination pilot shortlist + 1 SMB vertical for genre pack. +5. **Lock pricing experiments:** Core $129 anchor A/B later; don’t block launch on pricing perfection. +6. **Engineering charter:** 30-day sprint = HTTP MCP + SSP spine + 10 real pilot endpoints (not more roadmap prose). +7. **Legal:** tourism pilot data agreement + business ToS + MCP telemetry privacy (lightweight now, not full DaaS). + +--- + +## 15. GM summary + +**The copilot version is the right company.** The repo version got flattened into “partner MCP for SMBs with Cal.com” and lost the multi-model ambition, the SSP product, the tourism wedge, and the service-graph endgame. + +Market evidence in 2026 **supports** the urgency: + +- Consumers are using AI for local discovery at scale. +- AI recommendation is extremely selective. +- Shopify proved the pattern for *commerce* MCP on merchant domains. +- Yelp/Google/Cal.com prove MCP is real — and each protects *their* layer. +- Nobody is Shopify for local services’ AI presence. + +**Our job as a funded planning team:** freeze this strategy, realign all docs, and execute the SSP + tourism pilot path until the vacuum starts filling under *our* brand — not Yelp’s. + +--- + +## Research sources (selected) + +- BrightLocal LCRS AI trust / local consumer research (2026) — consumer AI usage for local recommendations +- SOCi 2026 Local Visibility Index / PR coverage — 1.2% ChatGPT recommendation rate, selectivity vs Google 3-pack +- Shopify Storefront MCP docs / industry writeups — merchant-domain MCP, agentic commerce +- Yelp Fusion AI MCP (github.com/Yelp/yelp-mcp) — official local data MCP +- Google Cloud / Merchant API MCP materials — Maps grounding, Merchant MCP +- Cal.com MCP docs — booking lifecycle tools for agents +- X discourse (2026) — agentic commerce, AI local discovery, SMB invisibility narrative + +*Stats should be re-verified at each external pitch; do not invent precision beyond sources.*