Street View OCR: the automated sign-writer v2 experiment

The person who painted the phone number onto every tradesman's van holds a de-facto contact list of our exact target. The automated equivalent: Google Street View, shopfront signage and Maps Business entries frequently show the painted number on the storefront or van, and Vision OCR can read it. This is the lowest-priority, sharpest-cornered channel: it works, but it must be built carefully. Official APIs and manual capture only, never bots.

Maps APIStreet View Static + Places
Vision OCRreads the painted number
Postal-onlyoutput, QR-to-claim
๐ŸŸ v2, lowest priority

The idea: Google Maps Street View API

What we discussed

Use the official Google Maps Platform APIs (the Street View Static API and Places API) to pull imagery of shopfronts and vans in a target patch. Many local trades paint their mobile number straight onto the signage. Run each image through Vision OCR to lift business name + number, then feed it into the same pipeline as every other channel.

This is the machine version of the sign-writer channel: instead of a human referral partner, the storefront itself becomes the data source.

Why it's attractive

No worker to recruit, no board to physically visit: a desk-based sweep of a postcode. Once built, it scales across towns for API cost only.

It's the automated twin of the Noticeboard mechanical-turk model: same output (name + number โ†’ postal), different capture.

The pipeline

1 Define patch

Pick a postcode / high-street run. Query Places API for businesses; get lat,lng for each frontage.

2 Pull imagery

Street View Static API: official, paid, ToS-clean. Grab the storefront view at each point.

3 OCR

Google Vision reads painted signage โ†’ candidate name + number strings.

4 Parse + validate

LLM extracts a plausible business name + UK/DE mobile; low-confidence โ†’ manual review, never auto-accept.

5 Dedupe โ†’ CRM

Hash against existing CRM; store only name + number + source + town (minimisation).

6 Postal + QR

Each new lead โ†’ one Stannp A-pile postcard with QR-to-claim. The prospect self-initiates. ๐ŸŸข

The sharp corner: compliance (get this right)

PointRuleVerdict
Data sourceUse official Maps Platform APIs (Street View Static, Places), paid, licensed. No logged-in scraping of Google.๐ŸŸ  API only
Nature of the numberA sole trader's mobile is personal data under UK/EU GDPR, even painted on a van.๐ŸŸ 
Lawful basisLegitimate interest + a written LIA, data minimisation (name + number + source + town only), privacy notice, easy erasure.๐ŸŸ 
Use of the numberPostal touch โ†’ QR-to-claim only. Prospect self-initiates. No cold call, no cold SMS.๐ŸŸข postal-only
Cold call / SMS to the numberPECR (UK) / UWG ยง7 (DE): a painted number is not consent.๐Ÿ”ด avoid
Bots / scraping GoogleToS breach + GDPR.๐Ÿ”ด avoid

Verdict from the strategy: ๐ŸŸ  Street View OCR โ†’ postal: treat as a v2 experiment, lower priority than the human channels. The referral partnership with a real sign-writer stays ๐ŸŸข cleanest of all; this is its automated, more-constrained cousin.

Where it sits in the priority order

On the cheapest-to-test ranking it's #6 of 6: behind inbound FB posts, classifieds, the noticeboard turk, sign-writer referral, and ads. Build cost + GDPR care = lowest priority. Prove the free claim-flow first; automate with OCR at scale only once everything upstream is working.

Klaudius ยท Street View OCR ยท source outreach/lead-sourcing-strategy.md ยง4 ยท v2 experiment ยท official APIs, no bots, postal-only