For HVAC and home services

We wrote down what AI would do to this category two days before we measured it.

Committed to the record on June 9: Claude would cite AC companies' own websites under 5 percent of the time, and the web-searching engines would clear 35. Measured on June 11: 2 percent, and 47. The ways the forecast could fail were written down too. That is the standard your category gets measured to.

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12-firm Honolulu cohort · 18 hash-locked questions · 6,218 citations · runs finalized June 11, 2026 · the full teardown
The called shotA forecast with a way to be wrong

Most measurement is a story told after the data. This one was dated before it.

Anyone can explain a number once it exists. A forecast committed to the record before the first run, with its own kill criteria attached, is a different kind of evidence. Here is the one we made for this category, and what the measurement returned.

Registered · before any HVAC data existed
June 9, 2026
Claude, own-site citation share
predicted under 5%
Web-searching engines, same questions
predicted at or above 35%
Falsifiers, on the record
Claude at 10% or higher, or the web engines below 35%, and the forecast fails. Written down with the prediction, so there was a real way to be wrong.
Measured · 3 clean runs, 6,218 citations
June 11, 2026
Claude, own-site citation share
measured at 2%
Four AI-answer web engines, pooled
measured at 47%
Forecast held · neither falsifier triggered

The prediction was committed to a timestamped record on June 9, 2026, before a single HVAC query had run. The reasoning, also on the record: home services is an editorially thin local trade, so individual AC companies barely exist in Claude's training data. HVAC is the third unrelated category where that collapse held, after CPA firms across three geographies and med spas. Full account in teardown 09.

Why this matters to an AC company deciding whether to believe any vendor's numbers: a measurement practice that publishes dated forecasts with kill criteria cannot quietly move the goalposts when the data lands. You are not being asked to trust a story. You are being shown a prediction that was allowed to fail, and did not.

The open fieldWhat makes this category different

Hotels and real estate sit behind an aggregator wall. Your category is still up for grabs.

In the markets we measured, Hawaii hotels hold 11 percent of their own citations and Honolulu real estate firms hold 14, because the portals and booking sites own the answer. Honolulu HVAC is different: on the five web-searching engines, AC companies' own websites carry 40 percent of the citations.

Review directories drew only 7 percent of mentions in this category, and the cohort was built with Angi, HomeAdvisor, and Home Depot excluded by rule, the way the teardown documents. There is no dominant national brand sitting on the answer. When a Honolulu buyer asks AI about AC repair or installation, the citations mostly land on actual AC companies' own sites or on editorial content, which means the citation is genuinely contested. Somebody in your market is going to hold it.

That is the practical difference between this page and our hotels and real estate pages: those categories are fighting a wall. Yours is a race. Cross-market comparison at the cross-category teardown.

The splitSame questions, opposite answers

Two thirds of ChatGPT search citations went to AC companies' own sites. On Copilot, none did.

The same eighteen questions, the same days, the same twelve firms, across seven AI surfaces: five that search the live web and two that answer from model memory. The share of citations reaching an AC company's own site ran from 66 percent down to zero depending only on which tool the buyer opened.

AI surfaceAC-company-owned shareThird-party shareMentions
ChatGPT search66%34%935
Gemma (model memory)63%38%432
Gemini grounded45%53%1,674
Google AI Overviews45%43%302
Perplexity38%59%1,477
Claude (model memory)2%98%606
Microsoft Copilot (Bing)0%91%792

Two readings worth taking seriously. Copilot cited an AC company's own site 0 percent of the time across 792 mentions, so nobody in the cohort holds that surface today. The teardown calls it the first-mover opening, and it is sitting there unclaimed. And Claude's 2 percent against Gemma's 63 on identical questions means even the two model-memory engines disagree completely. A company can be the answer on one surface and absent on the next, which is the reason a single-engine tool cannot tell you where you stand, and the reason we run all seven.

The boundaryWhy an independent count is worth anything

We never touch your website, and we never grade our own work.

Home services marketing is crowded with vendors who do the work and then report their own results. We are the other thing: the count that stays honest because we have no work in the race.

An optimization vendor

  • Edits your pages, your schema, and your profiles
  • Needs write access to your site and listings
  • Reports the results of its own changes
  • Quotes the lift it expects to produce

The scorekeeper

  • Never touches your website, systems, or accounts
  • Observes the seven AI surfaces from the outside
  • Reports what they cite, either way the number lands
  • Promises the measurement, never the outcome

The questions are locked by hash before we look, the method is documented in full at /methodology/, and every published number is dated and tied to the run that produced it on the claims record. Your team or your marketing partner executes the punch list. The called shot above is what that discipline looks like when it is real.

Run a home-services marketing agency? This is the largest agency-served local vertical there is, and we sit upstream of your team. We measure, you execute, you keep the client. For agencies →
The engagementWhat an AC company actually gets

A locked baseline, then the same questions asked again, run after run.

Kickoff
$4,500, one time. The researched question panel for your service area, locked by hash before the first run. Competitor cohort discovery. Baseline measurement across all seven surfaces, the baseline memo, and the prepared punch list.
Then
$1,500 per month, per category. Repeated runs against the frozen baseline, a monthly research memo, the prioritized punch list, and the readiness cross-map. Three month initial term, month to month after that.
Extra panels
$1,500 per month each, no second kickoff. A second service line or a second market, reusing the competitor cohort the kickoff established.
The boundary
Measurement and analysis only. Your team or your agency executes. Fees are for the research and are not contingent on any citation, ranking, or revenue outcome.

Honolulu is where this cohort was measured. The method itself is geography blind. Lock the questions your buyers ask, run the surfaces, count the names. It reads the same from Oahu as it does from Phoenix, Dallas, or Tampa.

Find out which surfaces name you and which ones have never heard of you.

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Prefer a hand-built diagnostic of your market and comp set? Email Lance@hi.neverranked.com.