Marketing Systems · Automation · 2026
Demand-generation engine for a home-services contractor
An end-to-end acquisition system: landing pages, paid search, and an automated CRM funnel with closed-loop tracking.
CampaignsLast 14 days
CTR
6.2%
▲ vs 2.6% ind.
CPA
$38
▼ 12%
Booked
214
▲ 28
Conversion funnel
Impressions
48,200
Clicks
2,990
Leads
410
Booked
214
Representative UI, abstract, with no client data.
45+
programmatic SEO/conversion landing pages (service × city)
Closed-loop
Google Ads + GA4 + Meta Pixel with offline-conversion sync back into bidding
~2.4×
industry click-through rate, cost-per-acquisition below average
How it works
1Landing pages
45+ programmatic service × city pages, schema + message match
↓→
2Google Ads CLI
plans, creates & optimizes campaigns from verified keyword data
↓→
3Conversion tracking
client-side tag + hourly offline-conversion backfill from the CRM
↓→
4CRM funnel
speed-to-lead SMS/email, pipeline stages, nurture
↓→
55-layer diagnostics
targeting, arrival, engagement, form and pipeline, graded
Architecture
Frontend
45+ landing pages (Next.js)
↓→
Backend
Google Ads CLI
Conversion sync
5-layer diagnostics
↓→
Data
PostgreSQL
GoHighLevel CRM
↓→
External
Google Ads
GA4
Meta Pixel
Clarity
By the numbers
Live campaign performance vs. industry
Click-through rate, this system~2.4×
Click-through rate, industry average1×
Conversions recovered by offline syncmeasured per account
Context
A residential contractor needed a repeatable way to generate and convert leads across multiple services and cities, without leads falling through the cracks between ads, the website, and follow-up.
What I did
- Built a programmatic set of 45+ SEO/conversion landing pages across services and locations, each with schema markup and message-matched hero copy.
- Wrote a Python Google Ads CLI that plans, creates, monitors and optimizes campaigns from data, verifying every keyword's volume and bid via the Keyword Planner API.
- Wired closed-loop tracking (Google Ads, GA4, Meta Pixel) plus an offline-conversion backfill so real CRM outcomes feed bidding, not just form fills.
- Built a five-layer diagnostic engine covering targeting, arrival, engagement, form and pipeline, fusing Ads, Clarity, GA4 and the CRM into graded reports.
Outcome
- A single system takes a click to a tracked, followed-up lead, with no manual handoffs.
- Offline conversions recover conversions that client-side tags miss, so Smart Bidding optimizes on complete signals.
- The diagnostic engine caught a consent banner intercepting ~40% of mobile form taps before it burned budget.
Under the hood
Programmatic landing pages
- 45+ live SEO pages generated across service × city, each with schema markup, message-matched hero copy, and multi-step lead forms.
- New service/city pages and campaigns clone from a template instead of being rebuilt.
Closed-loop conversion tracking
- Dual Google Ads actions, a client-side tag plus an hourly CRM offline-conversion backfill, recover conversions that client-side tracking alone misses.
- Full click-to-deal attribution via gclid and UTM capture means Smart Bidding optimizes on real revenue signals.
Diagnostics that catch regressions
- A 5-layer audit engine fuses Google Ads, Microsoft Clarity, GA4 and the CRM into graded, prescriptive reports.
- It caught and flagged a consent banner intercepting approximately 40% of mobile form taps, a silent conversion leak, before it wasted spend.
Stack
Next.jsGoogle Ads APIGA4Meta PixelGoHighLevel CRM