4d04a4a65a
- Strategy §1a: brick-and-mortar services + local retail in scope - Pure online e-com remains out (Shopify lane) - ICP, NORTH_STAR, README, product docs aligned - Add UC-03 general store (toothbrush / chicken strips case)
3.8 KiB
3.8 KiB
ICP Definition – geolocal.io
Single source of truth for who we sell to. Aligns with Canonical Strategy §1a.
Last updated: 2026-07-18
Primary ICP (Tier 1 – best fit)
| Attribute | Description |
|---|---|
| Business type | Independent, locally owned SMBs with a physical location or clear local service radius. Includes services and local retail. |
| Typical verticals | Services: wellness, personal care, home services, auto repair, tourism activities. Local retail: general stores, hardware, pharmacies, gift/outfitter shops, specialty food. Hybrid: bike shops, marinas, bakeries that sell and serve. |
| Employees | 1–15 (solo operators to small teams). |
| Revenue | Roughly $50k–$1M annual gross (directional, not a hard gate). |
| Tech maturity | Has some web presence (even thin). May use booking tools, POS, or neither. No dedicated AI/engineering team. |
| Pain point | AI assistants cannot reliably describe them, recommend them, or complete a next step (book, visit, buy/pickup). They lose the “named recommendation” moment. |
| Motivation | Want AI to tell the truth about what they do or carry — without learning a new craft stack. Will pay if it drives visits, calls, bookings, or sales. |
Illustrative retail case: A general store in Athol, Idaho should be able to make ChatGPT-class assistants answer: we carry toothbrushes; the chicken strips are a local favorite; here are hours and how to get here — from the store’s own structured truth, not a guess.
Secondary ICP (Tier 2)
| Attribute | Description |
|---|---|
| Business type | Multi-location local brands or regional operators (a handful to ~20 locations). |
| Typical verticals | Multi-site auto, dental, tutoring, small retail chains with local stores. |
| Motivation | Standardize AI-readiness across locations with light ops burden. |
Intermediate ICP (distribution, not the end SMB)
| Attribute | Description |
|---|---|
| Type | Tourism boards, visitor bureaus, chambers of commerce. |
| Job | Fund and aggregate member AI-readiness; improve destination helpfulness. |
| See | UC-02 |
Shared fit signals
- Place-based: consumers ask about them with a location in mind
- Owner or store manager can decide (not only enterprise procurement)
- Willing to put a small discovery pointer on a site or landing page
- Some path to value: appointments or walk-in/pickup/retail demand or both
- Often already spending something on ads, SEO, or web help (not mandatory)
Buying signals
- “ChatGPT / AI doesn’t know we exist” or recommends a competitor
- Phone and foot traffic still matter; online presence is weak or outdated
- Agency or chamber asking about AI search / AI visitor experience
- Tourism or main-street context where “what’s here / what do they have” is the job
Anti-ICP (do not target)
- Pure e-commerce with no meaningful local footprint (Shopify’s world)
- Enterprise with large dedicated engineering teams building their own agent stack
- Pure B2B with no consumer or visitor discovery motion
- National marketplaces and travel packagers (Airbnb/Kayak class) as primary customers
Note: “Does not take online appointments” is not automatic anti-ICP. Many strong retail fits will not be booking-led.
How to use this file
- GTM: lead scoring and partner briefs
- Product/engineering: genre packs and data model must support services and local retail primitives
- Investors: wedge is long-tail local businesses, not “appointments SaaS only”
Update this file first when ICP changes, then propagate.