Hiring a plumber, an electrician, an HVAC company, or a general contractor is a specific kind of purchase: it's often urgent, it's usually high-ticket, and getting it wrong is expensive and sometimes dangerous — a bad electrical repair isn't just a bad experience, it's a fire risk. That combination of urgency and stakes shapes how customers search, and it shapes how AI systems answer. The instinct is to assume the moment that matters most is the emergency search — "plumber near me open now." The data on how AI Overviews actually trigger suggests that instinct is aimed at the wrong target.
Here's what published research does and does not show, where Google's AI answers appear most often, and how to check what's currently being said about yours.
Google favors research queries over "near me" — that's not a ChatGPT finding
Whitespark's research — 540 queries across 3 cities and 6 verticals — found that Google AI Overviews trigger for 68% of local searches overall, but that rate splits sharply by query type: informational and cost-comparison queries trigger a Google AI Overview 92-97% of the time, while transactional, location-anchored "near me" queries trigger one only 15% of the time.1
Applied to home services, a query like "emergency plumber near me now" — the one that feels most aligned with how customers behave in a crisis — is among the query types least likely to show a Google AI Overview, while questions like "how much does it cost to replace a water heater" or "how do I know if I need an electrician or a handyman" sit in the bucket that triggers one nearly every time. Whitespark measured Google's AI Overviews specifically; it says nothing about when ChatGPT's own answers appear, so this is not a reason to deprioritize emergency-intent pages. It is a reason to make sure research and cost-comparison content gets the same attention as the urgent pages do — both query types matter to customers, and only one platform's trigger behavior is actually measured here.
Cost and decision-guidance content gets more Google AI Overview real estate than "near me" pages do
A page or FAQ answering "what does it cost to replace a water heater in [city]" or "signs you need an electrician, not a handyman" is competing for a query type that triggers a Google AI Overview 92-97% of the time. A page built purely around "24/7 emergency plumber [city]" is competing for a query type that triggers one only 15% of the time. Build both — this is Whitespark's Google-specific data, not a measurement of ChatGPT, so treat it as a reason to cover research and cost content well rather than a reason to cut emergency pages.
Home-service reputation carries real decision risk
In SOCi's 2026 Local Visibility Index, recommended locations averaged 4.3 stars on ChatGPT, 4.2 on Perplexity and 3.9 on Gemini.2 These are averages, not cutoffs. For home services, compare reputation with the actual local alternatives and verify service area, licensing, emergency availability, and contact details because a wrong recommendation can carry real cost or safety consequences.
That makes representative reviews and accurate operating facts especially valuable. The evidence supports a comparative trust signal; it does not support a universal star-rating gate.
Directory presence: the same gap, a different set of platforms
In Yext's API-derived sample of 6.8 million citations, OpenAI model output drew 48.73% from controllable third-party listings.3 For a home-services business, that makes relevant directory accuracy and coverage worth inspecting. Verify the sources shown in repeated ChatGPT checks.
"The emergency search feels like the moment that matters. In Whitespark's data, Google shows AI Overviews far more often for the cost and decision questions customers ask before the emergency."
Vague credentials don't register — specific ones do
The 2024 GEO (Generative Engine Optimization) paper reports gains of up to 40% more visibility on its own benchmark, varying by domain.4 For home services, this gap tends to show up in exactly the copy meant to build trust. The examples below are illustrative placeholders, not measured results — swap in your own true, checkable facts, and never publish a number you haven't actually measured:
| Vague (low signal) | Specific (high signal) |
|---|---|
| "Quality service you can trust" | "Licensed master electrician, 24/7 emergency response, upfront flat-rate pricing, serving [city] since 2011" |
| "Fast, reliable, affordable" | "[Your measured average dispatch time, if you track it], free written estimate before any work starts" |
| "Full-service plumbing and HVAC" | "Water heater replacement, drain camera inspection, HVAC repair — same-day appointments available" |
"Licensed" and "insured" are words nearly every home services business already uses. What's usually missing is the specific credential — the license type, the number of years, the actual response-time commitment, the pricing structure — that turns a claim into a checkable fact, but only if it's true and verifiable: never publish a response-time or pricing claim you haven't actually measured. The GEO research compared specific and vague phrasing in its own test set; it does not reveal how ChatGPT weighs home-service credentials.
How to check what ChatGPT currently says about your business
Use the method in How to check what ChatGPT says: a fresh session, each question three to five times, then verify the details. For a home-service business, test an urgent question and a research question:
- "Best emergency plumber in [your city]"
- "How much does it cost to replace a water heater in [your city]"
If you appear, check license type, response time and service area. If a competitor appears instead, compare its public facts and cited sources, and fix any verified error in your own listings.
Notes and sources
1 Whitespark, "Case Study: The Prevalence of AI Overviews in Local Search," May 12, 2025. Sample: 540 queries, 3 cities (Houston, Phoenix, Denver), 6 verticals. Tested interface: Google Search / AI Overviews, not ChatGPT. Findings cited: 68% of local searches surfaced a Google AI Overview overall (range 57-80% by industry); about 15% for local-intent ("near me"-type) queries; 92% for informational queries and 97% for hybrid cost/decision queries.
2 SOCi, "2026 Local Visibility Index," January 2026. Dataset: 2,751 multi-location brands, about 350,000 US locations. Benchmarks for ChatGPT, Perplexity and Gemini: share of locations recommended 1.2%, 7.4% and 11.0% (Google 3-Pack: 35.9%); average rating of recommended locations 4.3, 4.2 and 3.9 stars; business-profile accuracy 68.3%, 68.0% and 100.0%, measured against Google Maps data.
3 Yext, "AI Citations, User Locations, & Query Context," Yext Research, Oct 9, 2025. 6.8 million citations from ~1.6 million questions across OpenAI, Gemini and Perplexity APIs, July-August 2025, four industries (finance, food service, healthcare, retail). In its API-derived sample, OpenAI model output drew 48.73% from controllable third-party listings and Gemini drew 52.15% from first-party websites. The study warns API citations can differ from direct user applications.
4 Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan, Deshpande, "GEO: Generative Engine Optimization," submitted November 2023, published KDD 2024. Finding cited: "GEO can boost visibility by up to 40% in generative engine responses" on the paper's own GEO-bench benchmark; the paper states the effect varies by domain.
RaveHQ Insights share our views, based on our research and the sources cited. They are general information, not legal, financial or professional advice; check what applies to your business before acting.