Why Doesn't AI Mention My Contracting Business?

The shift: from “plumber near me” to “ask the AI”

Home services have always been a referral-driven industry. Homeowners ask neighbors, check Google Maps, or call the number on the truck they saw parked on their street. But the starting point of that journey is changing — and faster than most contractors realize.

“Plumber near me” searches grew over 600% in the past decade according to Google Trends data. But something new is happening: Gartner forecast in February 2024 that traditional search engine volume will drop 25% by 2026 due to AI chatbots and virtual agents. Homeowners are starting to ask ChatGPT “How much does it cost to replace a water heater?” or tell Perplexity “Find me a licensed electrician for a panel upgrade in Austin.”

ChatGPT surpassed 5.8 billion monthly visits by mid-2025, making it one of the top 10 most-visited websites globally. Pew Research Center found that 23% of US adults had used ChatGPT by early 2024, rising to 43% among adults aged 18–29. The National Association of Home Builders (NAHB) reported in 2024 that 78% of homeowners research contractors online before making contact, and the shift from search engines to AI assistants is accelerating.

The query pattern is fundamentally different. Instead of typing “plumber near me” into Google and getting a map pack with local businesses, a homeowner asks ChatGPT: “What should I look for in a plumber?” or “How much should a bathroom remodel cost?” or “What’s the best way to find a reliable HVAC contractor?” The AI responds with a narrative answer — mentioning specific platforms and sometimes specific brands — and the homeowner follows that path without ever seeing your business in a local search result.

The traditional funnel — Google search → map pack → website click → phone call — is being bypassed. And the home services industry, where over 80% of businesses have fewer than 10 employees (Bureau of Labor Statistics, 2024), is particularly exposed.

Who AI actually recommends for home services

We tested it systematically. Across hundreds of queries to ChatGPT, Perplexity, Gemini, Claude, and Grok, using homeowner-intent prompts like “How do I find a good plumber?” “What are the best home service companies?” and “I need an electrician — where should I look?” — the same names dominate:

* AI mention rate based on Metricus internal testing across ChatGPT, Perplexity, Gemini, Claude, and Grok using 200+ homeowner-intent queries (2026).

The pattern is clear: AI recommends the platforms, not the contractors. Angi — the result of IAC’s merger of Angie’s List and HomeAdvisor into ANGI Homeservices (now Angi Inc., NASDAQ: ANGI) — dominates AI responses because it generates enormous web content: millions of contractor profiles, cost guides, project articles, and review pages. Thumbtack, which has raised over $700 million in venture funding, follows the same playbook.

Individual contractors, who actually do the work, are almost never mentioned by name. Not the master plumber with 30 years of experience. Not the electrical company with 500 five-star Google reviews. Not the HVAC technician who services 2,000 homes a year. AI doesn’t know they exist.

This isn’t a bug. It’s how the systems work. And for an industry where the vast majority of businesses are small, independent operators, the consequences are severe.

Why your contracting business is invisible to AI

AI chatbots generate recommendations based on patterns in their training data — billions of web pages, articles, Reddit threads, review sites, and forum discussions. The entities that appear most frequently and authoritatively in that data are the ones AI recommends.

Consider the math:

• Angi generates approximately 50–70 million monthly website visits (SimilarWeb, 2024), with millions of individual contractor profile pages, cost guide articles, and project content pieces that create a massive web footprint.
• HomeAdvisor (now part of Angi) historically generated 40–60 million monthly visits and maintains a vast archive of indexed content.
• Thumbtack receives approximately 20–30 million monthly visits with extensive service-category content.
• The average independent plumber, electrician, or HVAC company website receives 100–1,500 monthly visits, has no news coverage, and appears on perhaps 5–10 third-party sites (Google Business Profile, Yelp, BBB, maybe a trade directory).

That’s a 10,000x–100,000x gap in web presence. And web presence is what AI systems learn from.

Three specific factors determine whether AI mentions your home services business:

1. Corpus frequency: How often your brand appears across the web. Angi has millions of indexed pages. A local plumber might have 30–100 total web mentions. AI weights entities by their frequency in training data — and the gap between a lead gen platform and an independent contractor is larger than in almost any other industry.
2. Source authority: AI weights authoritative sources more heavily. Angi gets covered in the Wall Street Journal, Forbes, CNBC, and Barron’s (it’s publicly traded). A local electrician gets mentioned in the neighborhood Facebook group and maybe a Nextdoor thread — which AI typically can’t see.
3. Content structure: The Princeton/Georgia Tech GEO study (Aggarwal et al., 2023) found that content with statistical citations and structured factual claims was up to 40% more likely to be cited by generative AI systems. Most contractor websites have unstructured marketing copy (“quality service since 1998,” “licensed and insured”) with no data AI can extract and cite.

Most contractor websites fail on all three dimensions. They have low corpus frequency, virtually no authoritative third-party mentions, and brochure-style content with no structured data, transparent pricing, or statistical claims that AI can extract and cite. To understand these dynamics more broadly, read our guide on how brands show up in AI recommendations.

What AI gets wrong about contractors

Even when AI does discuss home services, the error rate is staggering. Our testing found that AI provides incorrect or misleading information in approximately 40–55% of home-services-specific queries. In an industry where a wrong estimate can swing by thousands of dollars and an unlicensed contractor can create genuine safety hazards, accuracy isn’t optional. For more on this problem, see our deep dive on fixing AI hallucinations about your brand.

Pricing and cost estimates

Home service costs vary enormously by geography, material costs, and project complexity. HomeAdvisor’s own data shows that a water heater replacement ranges from $800 to $3,500+ depending on tank type, fuel source, and location. The Bureau of Labor Statistics reports that construction labor costs vary by up to 80% across metro areas. AI routinely cites national average costs that can be off by 50–200% from actual local pricing. A homeowner in San Francisco asking “How much does it cost to rewire a house?” gets a national average that might be half what the actual job costs in that market.

Licensing and insurance

Contractor licensing requirements vary dramatically by state and trade. The National Association of State Contractors Licensing Agencies (NASCLA) documents that licensing requirements differ across all 50 states, with some requiring state-level licenses, others using municipal licensing, and some having no licensing requirements for certain trades. AI frequently provides incorrect licensing information — telling homeowners a contractor is licensed when they aren’t, or failing to mention that a specific trade requires licensing in their state.

Platform vs. contractor confusion

One of the most damaging AI errors in home services: AI often recommends lead generation platforms as if they are contractors. When a homeowner asks “Who should I hire to fix my roof?” AI frequently says “Angi” or “Thumbtack” as if those platforms will show up at your house with a ladder. This confuses homeowners about who will actually do the work and sends them through a lead gen funnel rather than directly to qualified local contractors.

Service area and availability

AI has no concept of a contractor’s actual service area, current workload, or availability. It may recommend a roofing company that doesn’t serve the homeowner’s zip code, or suggest contacting a business that has a 6-week backlog. During peak seasons — HVAC in summer, plumbing in winter — this disconnect between AI’s static recommendations and the dynamic reality of contractor availability creates real problems for homeowners.

Certifications and specializations

AI frequently fabricates or misattributes trade certifications. It may claim a plumber holds ASSE (American Society of Sanitary Engineering) certifications they don’t have, or state that an HVAC company is a Carrier Factory Authorized dealer when they’re not. For electricians, AI sometimes confuses journeyman and master electrician designations or invents NFPA (National Fire Protection Association) certifications.

The $600 billion market AI is reshaping

The US home services and improvement market is enormous — and the financial stakes of AI visibility are correspondingly high:

• The Joint Center for Housing Studies of Harvard University estimated US homeowner spending on improvements and repairs at $603 billion in 2024, a figure that has grown steadily from $472 billion in 2019 (JCHS “Improving America’s Housing” report, 2024).
• The NAHB reports that the average homeowner spent $8,484 on home improvements in 2024, up from $7,560 in 2022.
• Angi Inc. generated $1.69 billion in revenue in 2023 (annual report) primarily from contractor leads and advertising. That revenue comes directly from contractor marketing budgets.
• The Bureau of Labor Statistics counts over 780,000 plumbing, HVAC, and electrical contracting establishments in the US as of 2024, the vast majority being small businesses with fewer than 10 employees.
• HomeAdvisor data (now Angi) shows the average contractor pays $15–$100+ per lead through their platform, with some high-value trades like roofing and HVAC paying over $150 per lead.

The lead generation economics create a specific vulnerability. Contractors already spend heavily to acquire customers through platforms like Angi, Thumbtack, and Google Local Services. If AI further consolidates homeowner discovery through these same platforms, contractors face a double squeeze: higher lead costs from platforms that AI is driving even more traffic to, and zero organic discovery through AI channels themselves.

For a roofing company where a single job averages $8,000–$15,000, every lead matters. If even 5–10% of homeowner discovery shifts to AI, and AI sends every one of those homeowners to Angi rather than to local contractors directly, the revenue impact compounds fast. For more on why this dynamic matters across industries, see why B2B SaaS brands are invisible in ChatGPT.

Google Local Services, AI Overviews, and the phone call problem

Google itself is reshaping how homeowners find contractors — and AI is at the center of it.

Google Local Services Ads (LSAs) launched in 2015 and now cover over 70 service categories across the US. Unlike traditional Google Ads (pay-per-click), LSAs are pay-per-lead: a homeowner clicks “call” or “message” directly from the search results, and the contractor pays $15–$100+ per contact. Google’s “Google Guaranteed” badge — which requires background checks and license verification — has become a trust signal that influences homeowner decisions. According to Google’s own data, LSAs now generate tens of millions of leads annually for home service providers.

But the real disruption is Google’s AI Overviews, which rolled out broadly in 2024–2025. When a homeowner searches “how much does it cost to install central air conditioning,” Google now generates an AI-synthesized answer at the top of the page — pulling data from multiple sources, including HomeAdvisor cost guides, contractor websites, and even data Google has collected directly.

Here’s what many contractors don’t realize: Google has been observed calling businesses directly to verify pricing, hours, and service details, then using that information in AI-generated responses. If Google calls your office and asks “How much do you charge for a drain cleaning?” that data may end up in an AI Overview that thousands of homeowners see. The problem: you have no control over how that information is presented, contextualized, or updated.

The JCHS reports that homeowner spending on maintenance and repairs alone — separate from improvements — was $91 billion in 2024. That’s the emergency plumber, the furnace repair, the electrical fix — exactly the kind of urgent, high-intent searches where AI Overviews increasingly intercept the homeowner before they ever reach a contractor’s website.

How AI disrupts the lead gen model

The current home services ecosystem has a clear structure: homeowners discover contractors through lead gen platforms (Angi, Thumbtack), review sites (Yelp, Google), and referrals. Contractors pay the platforms for leads. The platforms profit from the spread between advertising revenue and lead acquisition costs.

AI introduces three disruptions to this model:

1. AI commoditizes the platforms

When a homeowner asks ChatGPT “How do I find a reliable plumber?” AI says “Check Angi, Thumbtack, or Yelp.” But increasingly, AI also provides direct guidance: “Look for state licensing, ask for proof of insurance, get three written estimates, check references.” The platform recommendation becomes just one line in a longer, more useful answer. If AI can provide the same guidance the platforms provide — cost estimates, quality signals, vetting criteria — the platforms’ value proposition erodes.

2. AI can recommend contractors directly

As AI systems integrate real-time web search (Perplexity already does this, ChatGPT added it in 2024), they can pull Google reviews, licensing data, and website information for specific local contractors. A homeowner asking “Find me a licensed plumber in Scottsdale with 4.5+ stars” can get a direct answer that bypasses the platform entirely. But only for contractors whose data is structured, consistent, and findable.

3. AI creates a new “zero-click” discovery path

Similar to how Google’s featured snippets reduced click-through rates to websites, AI provides complete answers that reduce the need to visit any platform at all. The NAHB reports that 62% of homeowners who use AI assistants for home improvement questions feel they got a “good enough” answer without visiting a contractor’s website. For contractors, this means your website’s content needs to be the source AI cites, not just a destination homeowners visit after the fact.

The gap between Google Local Services (where local contractors can compete) and AI chatbot responses (where they can’t) is wider in home services than almost any other industry. On Google Maps, a well-reviewed local plumber wins. In ChatGPT, the same plumber doesn’t exist. Learn more about how we measure AI visibility across these channels.

What actually works: the AI visibility playbook for contractors

The good news: AI visibility is a solvable problem for home service businesses. And because almost no one in the trades is working on it yet, early movers have a disproportionate advantage. Here’s what works, based on our research into turning AI visibility data into action.

1. Audit what AI currently says about you

Before fixing anything, you need to know what’s broken. Query ChatGPT, Perplexity, Gemini, and Claude with prompts your customers would actually use:

• “Who is the best plumber in [your city]?”
• “How much does it cost to [your service] in [your city]?”
• “Tell me about [your business name]”
• “Is [your business name] licensed and insured?”
• “Best HVAC companies near [your area]”

Document every mention (or absence), every error, and every competitor or platform that appears instead of you. Or run a Metricus AI visibility report that does this across hundreds of query variations automatically. For a quick start, try our free AI visibility check.

2. Publish transparent pricing content with real numbers

This is the single highest-impact action for contractors. AI systems cite content that contains specific, structured, data-rich claims. The GEO research from Princeton/Georgia Tech found that content with statistical citations was up to 40% more likely to be cited by generative AI — and implementing schema markup boosted citation rates by 25–40%.

For home services, this means:

• Service-specific pricing pages with actual cost ranges for your market, not “call for a free estimate.” Example: “Drain cleaning in Phoenix: $125–$350 depending on access and blockage severity. Emergency after-hours rate: $175–$450. Updated March 2026.”
• Local cost guides: “What does a new roof cost in Denver in 2026? Our data from 200+ recent projects shows $8,500–$22,000 for asphalt shingle roofs on 1,500–2,500 sq ft homes, compared to the national average of $9,000–$18,000 per HomeAdvisor.”
• Project breakdowns with material costs, labor hours, and permit fees that AI can extract as structured data points.

3. Implement comprehensive schema markup

Structured data is the single most underutilized tool in the contractor’s digital arsenal. Implement:

• HomeAndConstructionBusiness or LocalBusiness schema with your specific trade type (Plumber, Electrician, HVACBusiness, RoofingContractor)
• Service schema for each service you offer, with priceRange and areaServed
• FAQPage schema for common customer questions (cost, timeline, licensing, warranty)
• Review and AggregateRating schema
• OpeningHoursSpecification including emergency/after-hours availability
• GeoCoordinates and serviceArea for precise coverage mapping

The Princeton/Georgia Tech GEO study found that adding structured data markup to content increased AI citation likelihood by 25–40%. For contractors, this means the difference between AI knowing you exist and AI not knowing you exist.

4. Build citations on authoritative third-party sources

AI reads everything about you across the web. The sources that carry the most weight for home services:

• Google Business Profile with complete information, service categories, photos, and active review management (aim for 100+ reviews for trades)
• Better Business Bureau (BBB) — AI heavily weights BBB data for contractor trust signals
• State licensing board — ensure your license number and status match your website exactly
• Manufacturer directories (Carrier, Trane, Rheem for HVAC; Kohler, Moen for plumbing; etc.) — manufacturer-authorized dealer/installer status is a strong AI signal
• Trade association directories (PHCC for plumbing, NECA for electrical, ACCA for HVAC)
• Nextdoor business pages — Nextdoor is increasingly crawled and carries neighborhood-level authority
• Yelp, Angi, and Thumbtack profiles — complete and accurate even if you don’t pay for leads, because AI reads them

5. Create educational content that AI wants to cite

Contractors have a unique advantage: deep expertise that lead gen platforms don’t. A 30-year master plumber knows more about pipe materials than any Angi cost guide writer. Turn that expertise into content AI can cite:

• “When to repair vs. replace your water heater: a plumber’s guide with cost data”
• “Electrical panel upgrade costs in [your city]: 2026 data from 150 recent projects”
• “HVAC sizing guide: what size AC does a [your region] home need?”
• “Roofing material comparison: asphalt vs. metal vs. tile for [your climate zone]”

Every piece of content should include specific numbers, date stamps, geographic context, and your credentials. This is what makes it citable by AI systems that are looking for authoritative, factual, structured claims.

6. Fix errors at their source

If AI is getting your pricing, licensing, service area, or certifications wrong, the error is coming from somewhere. Usually it’s an outdated Angi profile, stale Yelp information, an old HomeAdvisor listing, or inconsistent data across your own web properties. Find the source, fix it, and the AI corrections will follow over time as models retrain on updated data.

The case for auditing your AI visibility now

The home services market is at an inflection point. The JCHS projects that homeowner improvement spending will remain above $550 billion annually through 2027, driven by aging housing stock (the median US home age is now 41 years per Census Bureau data), rising home values that unlock equity for renovations, and persistent underbuilding of new homes. The contractors who capture this demand will increasingly be the ones that AI recommends — or at least knows about.

At the same time, the labor shortage in skilled trades is intensifying. The BLS projects that the construction industry will need to hire 546,000 additional workers annually through 2032 just to meet demand and replace retirements. Associated Builders and Contractors (ABC) estimated the industry was short approximately 501,000 workers in 2024. This means fewer contractors chasing more demand — and the contractors who are visible to AI-driven discovery will command more of that demand and the pricing power that comes with it.

The cost of AI invisibility is concrete. A plumbing company that averages $500 per service call and handles 20 calls per week generates roughly $520,000 in annual revenue. If 5% of potential customers now start with AI (a conservative estimate), and AI never mentions that company, that’s potentially $26,000 in annual lost revenue from one discovery channel alone. For an HVAC company where a single system replacement averages $8,000–$15,000, losing even a few AI-influenced leads per quarter means $50,000–$100,000+ in annual revenue at risk.

The contractors who are building AI visibility now — while competitors are still exclusively relying on Angi leads and Google Maps — will have a structural advantage that compounds over time. Every piece of authoritative, data-rich, locally-specific content you publish today enters the training data that shapes AI recommendations for years.

Sources: Joint Center for Housing Studies of Harvard University, “Improving America’s Housing” report (2024); National Association of Home Builders (NAHB) homeowner spending survey (2024); Bureau of Labor Statistics, Occupational Employment and Wage Statistics (2024); Bureau of Labor Statistics, Employment Projections (2024); Associated Builders and Contractors (ABC) workforce shortage analysis (2024); HomeAdvisor / Angi cost data (2024); Angi Inc. 2023 annual report; National Association of State Contractors Licensing Agencies (NASCLA, 2024); Gartner search prediction (Feb 2024); Pew Research Center AI adoption survey (2024); Princeton/Georgia Tech GEO study (Aggarwal et al., 2023); SimilarWeb traffic estimates (2024); US Census Bureau housing stock data (2024). AI mention rates based on Metricus internal testing across ChatGPT, Perplexity, Gemini, Claude, and Grok (2026). Learn more about how we measure AI visibility.

Related reading

• The 5-step AI visibility action plan — the general framework for turning audit findings into fixes.
• Fixing AI hallucinations about your brand — the deep dive on correcting factual errors at their source.
• What is AI visibility? — the complete explainer on how brands appear in AI.
• Why B2B SaaS brands are invisible in ChatGPT — the same dynamic in a different industry, with transferable strategies.
• Free AI visibility check — run a quick manual check before ordering a full report.
• AI visibility scores explained — how Metricus measures and benchmarks AI visibility.