What the model cites decides who it names, and in the trades that means recent reviews, local mentions, reputable directories and clear proof of licensing and quality work, not a slick site alone. The engines lean on third-party proof they can quote, so a contractor with a wall of recent reviews describing real jobs and a few credible local mentions gets written into the recommendation, while one with only a self-published profile is passed over.

It is worth separating this from the sibling disciplines. Classic contractor SEO chases the map pack and rankings; answer engine optimization chases the featured answer box; AI search optimization is the umbrella across every surface. Generative engine optimization is the citation layer specifically, getting your name and your sources quoted inside the recommendation the model writes, which is where a homeowner's shortlist really forms.

The scoreboard we hold ourselves to is AI-attributed jobs and quote requests, never impressions. Each month you see which recommendations in your area now name your business, which sources the engines cite to justify it, how you compare to the contractors cited alongside you, and how many calls traced back to an AI answer, so the investment is judged by the jobs it books.

Emergency and planned work generate different recommendations, and we build for both. An urgent search, a burst pipe, storm damage, prompts an answer weighted to availability and recent reviews, while a planned remodel prompts one weighted to quality proof and credentials, so we earn the specific citable evidence, the reviews, the local coverage, the licensing proof, that gets you named in each, prioritising the higher-value considered jobs.

This fits trades and home-service businesses of every kind, roofers, plumbers, electricians, HVAC, remodelers and general contractors, that want to be the name the AI writes into its recommendation, especially the higher-value work homeowners research before they call. If homeowners arrive already naming a competitor the AI cited, the engines are writing your area's shortlist without you, and generative engine optimization for contractors is how you earn your way into that answer, service by service.

We work with contractors from a single-truck operation earning a first AI citation to a multi-crew business defending its market, across the United States and North America. The promise is narrow and honest: your name written into the AI's hiring recommendations and your sources cited to support it, measured in AI-attributed jobs rather than a chart that never fills the schedule.

Because citations are earned, not bought, we sequence the work to compound. We start with the service and neighbourhoods you most want, earn the reviews and local mentions the engines quote there, prove you are being named in those recommendations, and widen from there, because a genuine citation base compounds faster than a thin push everywhere at once. And because the engines re-read their sources, we keep reviews and coverage fresh so a recommendation you earn stays written in your favour, and we make licensing proof clear because homeowners and models both look for it.

Citation and recommendation research. We capture the hiring recommendations the engines already write for homeowners in your area, record which contractors are named and which sources, reviews, local mentions, directories, are cited, and where you are absent, so the work targets the exact citations that get a business written into the answer.

Reviews the models quote. Generative recommendations lean on recent reviews the model can quote, so we build a compliant cadence for earning reviews that describe real jobs, because specific, quotable reviews are among the sources the engines cite most when they name a contractor.

Local editorial and citable mentions. The engines cite third-party sources, so we earn genuine local mentions and reputable directory presence the models can quote when recommending a contractor, the off-profile proof that separates a named business from an overlooked one.

Citable service and licensing proof. Models quote clear proof of what you do and that you are licensed and insured, so we build extractable service and credential content, so when the engine explains why it named you it can cite your qualifications and quality as the source.

Entity and authority signals. We make you an unambiguous entity the models trust, consistent identity, services and areas across the sources the engines read, so when a recommendation is written the model is confident it is citing the right contractor for that job and area.

AI-attributed job tracking. You get reporting that ties citations to calls, quote requests and jobs, not vanity counts. We track which recommendations now name your business and connect them to the work that follows, so you can see whether the GEO work is booking jobs, and we shift effort toward the services that convert.