HVAC company · competitive metro market

Background

An established HVAC company with steady demand from search and referrals, but no read on how AI assistants represented it when prospective customers asked for a recommendation.

The challenge

Its presence in AI answers was unstable: named in one run, gone the next, across ChatGPT, Claude, Perplexity, and Google AI. It sat just outside the top group, and two competitors were steadily pulling ahead. Without a stable, repeatable measurement, there was no way to tell whether any change was actually working.

What we did

We treated AI visibility as a measurable system, not a one-off check:

• Locked down consistent business facts, services, service areas, and hours everywhere the models read them
• Added structured service and service-area data so each offering was machine-readable
• Built content answering the exact “best [service] near me” and comparison questions buyers ask AI
• Tracked a fixed prompt set every week to separate real movement from run-to-run noise
• Benchmarked share of voice against the specific competitors AI named instead

Results

Over four months the company's AI visibility rose about five points and settled into the top three across all four models, while the average competitor's visibility fell about five points. Figures are rounded measured estimates, not exact daily rankings. Results vary by market, model, prompt set, and implementation.

Measurement & evidence

Market:

HVAC company · competitive metro market

Period:

4 months

Measurement:

Fixed buyer-prompt panel, repeated across ChatGPT, Claude, Perplexity, and Google AI.

Primary metric:

AI Visibility — the share of relevant answers, across repeated runs of the fixed prompt panel, that name the business. How this is measured

Starting point → latest measurement:

19% → 24%

Actions completed:

Locked down consistent business facts, services, service areas, and hours everywhere the models read them; Added structured service and service-area data so each offering was machine-readable; Built content answering the exact “best [service] near me” and comparison questions buyers ask AI; Tracked a fixed prompt set every week to separate real movement from run-to-run noise; Benchmarked share of voice against the specific competitors AI named instead.

Disclosed here:

Category and market type, the measurement window, the metric definition, the provider set the prompt panel was run across, the before/after values, and the source-level work completed.

Withheld:

The client's name and domain, the verbatim prompt panel, and per-run answer text — the first because clients ask for anonymity, the last two because an engagement-specific panel would identify the client. Clients receive all three in their own reporting.

Interpretation:

Measured association after the completed work; not a guarantee that every change caused the full movement.