Results

The system, proven layer by layer.

Every number below comes from a real client account. Names are held back here and shared on the call, where the accounts get opened live.

$14

cost per lead on Meta, live right now

65

leads into one pipeline in 30 days

6x

tracked return on ad spend, and undertracked

4.9★

from under 4 stars, on 80 reviews

500+

Google reviews generated across client accounts

+500

followers in 3 weeks, organic, 3 viral posts

The full system, live

A lawn care company in Palm Beach County. Full build: video ads, funnel, custom pipeline, three AI nurture flows, review engine. In the first month: a $14 cost per lead, 65 leads into the pipeline, and over $6,000 closed on roughly $1,000 in ad spend. That is a tracked 6x return, and the real number runs higher: the client logs close values slower than the jobs come in. Reviews went from 180 to 260 in the same stretch. The artifacts below are that account, untouched.

The live client pipeline with 61 opportunities moving toward estimate sent
A real conversation: the AI setter answers in seconds, books the call, and follows up on the estimate
The same client's review dashboard: 4.94 average rating, reviews climbing

Layer by layer, across accounts

Attention

A landscape design brand

Organic content engine only, no ad spend yet: 500 new followers in three weeks and three posts gone viral. The creative stops the scroll before a dollar of media goes behind it.

Conversion

A custom construction builder

A state-of-the-art website with motion graphics, scroll-scrubbed build stories, and time-lapses, the same craft as the site you are on. The work finally looks like the work.

Reputation

A pool builder

Started at 14 reviews under 4 stars. The review engine took them to almost 80 reviews at 4.9 stars, ranking on Google, and now booked so solid they have not needed to turn ads on.

Compounding

A commercial painting company

No website, no profile, 80 percent government work. After the foundation build and review engine: hundreds of reviews and residential, the high-margin side, doubled to half the business.

The ads behind the numbers

Sound on. These run as real campaigns today.

Landscape design, brand film
Commercial landscaping, client story
Custom construction, walkthrough ad
Estate build, reveal ad
Racquet club, top of funnel
Lawn care, lead gen ad
Land clearing, project story

The numbers those ads produce

$25,000

in estimates sent, first month on a client account

61

open opportunities working through one client pipeline

4.94

average Google rating across 248 reviews on a client profile

3-5x

the return on ad spend range the system is built to hit

The pipeline, mid-flight

A live client board: 61 opportunities moving from new lead to estimate sent, worked by AI setters at every stage. Names and amounts are hidden for privacy. Everything else is untouched.

A live client sales pipeline with 61 opportunities moving toward estimate sent

The conversation that did the work

A real thread from that account. The lead came in from a Meta ad, got a text back in seconds, booked the call, and got the estimate follow-up the next day. His last message: yes, everything is great.

A real CRM conversation showing the AI setter booking and following up with a lead

Reputation, compounding

Review reactivation on a client Google Business Profile: past customers asked for the reviews they never left, new customers asked automatically when jobs close. The result is a 4.94 average across 248 reviews, with sentiment running strongly positive.

A client review dashboard showing a 4.94 average rating across 248 Google reviews

The work behind the numbers

These systems run today for landscape design, lawn care, construction, fitness, racquet clubs, and event venues across South Florida. Full walk-throughs of the accounts, with the numbers that matter for your niche, happen on the strategy call.

The stake

If the system does not hit a tracked 3x ROAS in your first 90 days, we work free until it does.

Terms defined together on the call and put in writing. That is how sure we are the machine does what this page says.

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