All Case Studies · AI Product Development

TradesSnap.US

An AI-powered marketing engine that converts a contractor's voice note and job site photos into three publish-ready SEO assets — automatically, in under two minutes. Conceived, built, and launched in Ohio.

Project TradesSnap.US
Industry Home Services · Local SEO · AI
Published 2026
My Role AI Architect · Designer · Developer

$5K

Projected MRR per client cohort

5+ hrs

Admin hours saved per contractor, per week

3

SEO-ready marketing assets per job, automated

~$0

Marginal cost per new client added

Invisible by default

The American trades industry employs millions of skilled professionals — plumbers, roofers, HVAC technicians, electricians — who build, fix, and maintain the physical infrastructure of every community in this country. Most of them are nearly invisible online, not because they lack work, but because they lack time.

I know this firsthand. Before building TradesSnap.US, I spent years inside the industry — in HVAC distribution, electrical manufacturing, and residential roofing. I watched excellent contractors lose jobs to worse competitors simply because those competitors had a fresher Google Business Profile or a few more reviews. The gap between doing great work and being found for it was costing real businesses real money, every single week.

The core diagnosis

A skilled contractor finishing a burst pipe repair at 6pm has zero interest in writing a 500-word SEO blog post. The barrier isn't motivation — it's friction. TradesSnap.US was built to eliminate that friction entirely.

Two audiences, one system

TradesSnap.US serves two audiences simultaneously. The first is the contractor — the paying customer, who needs a frictionless tool that fits into a job site workflow. The second is the homeowner — the contractor's customer, who is often on a phone, often stressed, and making a high-stakes hiring decision in real time.

There is a third "audience" that most contractors never think about: the Google Local algorithm. Every piece of content the system generates is built to satisfy all three at once.

The Contractor

The Paying Customer

  • Wants to finish the job and go home
  • No time for marketing or content creation
  • Needs results without learning new tools

The Homeowner

The End Consumer

  • On a phone, often in a stressful moment
  • Needs local proof: "Have you done this near me?"
  • Builds trust through before/after photos and location specificity

The Algorithm

Google Local Search

  • Needs "Service + City" keyword density
  • Rewards fresh, unique, hyper-local content
  • Reads structured JSON-LD schema for rich results

One input. Three outputs. Zero friction.

The core design decision was to make the contractor's ask as small as humanly possible: a rough voice note and two photos. Everything else — transcription, jargon translation, geo-tagging, copywriting, schema markup, formatting — is handled by the pipeline.

The AI system operates under a strict proprietary ruleset I architected from the ground up: every technical specification must be translated into a homeowner benefit, the location must appear in the headline and first paragraph of every piece, the Problem–Agitate–Solve copywriting framework must structure every case study, and no details may be invented or assumed.

How it works

Input

🎙 Voice Note
📸 2 Job Photos

AI Engine

Claude API

Transcription · Jargon Translation · Geo-tagging · PAS Copywriting · JSON-LD Schema

3 Outputs

Local SEO Case Study
Google Business Profile Post
Social Media Caption
Hub-and-Spoke CMS
  • Local SEO Case Study — Full website post with JSON-LD structured data schema injected into the page head for Google rich result eligibility
  • Google Business Profile Update — Sub-100-word post with local hashtags and a direct call-to-action, signaling freshness to Google Maps ranking
  • Social Media Caption — Blue-collar, community-first voice: transformation hook, job narrative, engagement question
  • Hub-and-Spoke CMS — Every new project auto-populates the relevant Service page and Location page, with dynamically generated CTAs by city

The strategic insight

A mid-size marketing agency charges $2,000–$4,000/month for a fraction of this output, produced by humans working on multiple clients simultaneously. TradesSnap.US delivers the same result with consistency no human team can match — and the marginal cost of each new client is near zero.

How it was built

01

Research & Architecture

Industry insight to system design

Years of firsthand experience in HVAC distribution, electrical manufacturing, and residential roofing became the product brief. I mapped the contractor workflow, identified every friction point, and designed the data schema: three interconnected collections — Services, Locations, and Project Case Studies — with relational logic to power the Hub-and-Spoke CMS.

02

AI Pipeline & Prompt Engineering

Building the content engine

Architected the full AI content pipeline using Claude Code as the development environment. Engineered the system prompt with strict rules: zero hallucination constraints, mandatory jargon-to-benefit translation, geo-tagging requirements, PAS copywriting structure, and JSON-LD schema output. Integrated OpenAI Whisper for audio transcription capable of handling job-site noise and trade terminology.

03

Front-End & CMS Build

Platform development and mobile-first UX

Built the full front-end in HTML, CSS, and JavaScript with a mobile-first design — sticky "Call Now" header, before/after image slider, thumb-friendly navigation. Structured all data in JSON with JSON-LD schema auto-injected into each project page head. Wired the backend pipeline in Python with REST API integrations for publishing and distribution.

04

Automation & Launch

Multi-channel distribution and go-live

Configured Make.com automation for multi-channel publishing: website CMS, Google Business Profile, and social media simultaneously. Launched TradesSnap.US live and indexed in Ohio — ready to onboard the first contractor cohort.

Tools & platforms

Every component was selected for reliability, scalability, and low marginal cost per client. The pipeline is fully automated — adding a new subscriber does not require additional human labor.

AI Development & Content Generation

Claude Code Anthropic Claude API OpenAI Whisper API

Backend & Data

Python JSON / JSON-LD Schema REST APIs

Front-End

HTML5 CSS3 JavaScript

Automation & Distribution

Make.com Zapier Google Business Profile API Buffer

Marketing as a revenue generator

TradesSnap.US operates as a productized subscription service. Contractors subscribe, connect their workflow, and receive publication-ready content without hiring a copywriter, SEO agency, or social media manager. The product delivers more output per dollar than any human team at this price point — with perfect consistency every time.

The unit economics are designed for scale: the pipeline is fully automated, so adding clients increases revenue without proportionally increasing cost. This is marketing infrastructure that pays for itself — and then generates profit.

Revenue Model

Subscription tier — Starter Monthly recurring
Subscription tier — Professional Monthly recurring
Marginal cost per new client Near zero
Projected MRR (initial cohort) $3,000 – $5,000

The value comparison

A regional marketing agency charges $2,000–$4,000/month to produce a fraction of this content volume, on a slower cadence, with inconsistent local specificity. TradesSnap.US produces more, faster, with hyper-local accuracy — at a price point every independent contractor can justify.

What it's built to do

TradesSnap.US is live, indexed, and built for scale. The system produces a constant stream of hyper-local, long-tail keyword content — exactly the type Google rewards with Local Map Pack placement. Every project a contractor completes becomes a permanent SEO asset, compounding over time.

The long-tail impact is the real story: a contractor with 50 published case studies across 10 neighborhoods isn't just ranking today — they're building a content moat that gets harder for competitors to close every single week.

$3–5K

Projected monthly revenue, initial cohort

5+ hrs

Admin time saved per contractor, per week

Scalability — zero marginal cost per new client

The bottom line

TradesSnap.US is proof that AI, applied with domain expertise and genuine user empathy, generates real revenue — not as a novelty, but as an operational product. This is marketing as a revenue generator. Built from the ground up by one person, with direct industry knowledge, in Ohio. Live at tradessnap.us

See it in action

The full TradesSnap.US value proposition — in 60 seconds.

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