What happened when we ran an AI visibility audit on 200 businesses in the same city

We Audited 200 Businesses in One City for AI Visibility

Introduction

We wanted to stop guessing and start measuring. So we picked a city (Nashville, Tennessee, metro population 2 million) and ran a comprehensive AI visibility audit on 200 businesses across 20 industries.

For each business, we asked ChatGPT, Gemini, and Perplexity: "What can you tell me about [business name]?" and "Who's the best [industry] in Nashville?" We scored every response. We measured every gap. And we mapped the patterns.

The result is the most detailed picture we've assembled of how AI search optimization actually works at a city-wide scale. Not theory. Not single-client case studies. A 200-business dataset showing exactly what separates AI-visible businesses from AI-invisible ones.

Methodology: what we measured and how

We selected 200 businesses: 10 businesses in each of 20 industries. Industries included: dentists, personal injury lawyers, HVAC companies, plumbers, restaurants, real estate agents, financial advisors, med spas, auto repair shops, hair salons, accountants, insurance agents, chiropractors, landscaping companies, marketing agencies, IT service providers, roofing companies, moving companies, wedding venues, and veterinary clinics.

Within each industry, we selected the 10 businesses that ranked highest in Google's local results. These weren't random businesses. They were the Google winners, the businesses that had already invested in traditional visibility.

For each business, we evaluated:

AI Recommendation Status: Were they named in AI responses when someone asked for the "best" in their industry in Nashville? (Tested across ChatGPT, Gemini, and Perplexity.)

AI Description Accuracy: When we asked about them by name, was the description accurate?

Citation Count: How many independent web sources mentioned them?

Entity Consistency Score: How consistent was their business information across web sources? (Scored on a 1 to 10 scale.)

Review Distribution: How many platforms had active reviews?

Structured Data: Did their website have comprehensive schema markup?

Content Authority: Did they publish content that answers AI-style queries?

The top-line numbers

Read that last number again. 54% of the top Google-ranking businesses in Nashville were completely unknown to AI. These are businesses that have invested in SEO, that rank in Google's local pack, that have review profiles and active Google Business Profiles. And more than half of them don't exist in AI's world at all.

Of the 46% that AI did have some information about, only about a third were described accurately. The rest had errors: wrong services, old addresses, confused identities, or descriptions that no longer reflected the business.

Only 4.5% of all 200 businesses had consistent, accurate, favorable AI presence across all three major platforms. That's 9 businesses out of 200.

The industry breakdown: who's visible and who's not

Not all industries performed equally. Here's the industry-by-industry breakdown of AI recommendation rates (percentage of the 10 businesses per industry that were named in at least one AI recommendation query):

• The pattern is stark. Professional services and B2B businesses (marketing agencies, financial advisors, IT services) had the highest AI visibility. Home services (plumbing, HVAC, roofing, landscaping, moving) had zero. Healthcare and personal services fell in between.

The correlation with citation count is visible in the data: industries with higher average citation counts had higher AI recommendation rates. But the causation runs deeper than just counting citations.

The five factors that predicted AI visibility

We ran a regression analysis across all 200 businesses to identify which factors most strongly predicted AI recommendation status. Here's what we found, ranked by predictive strength:

• Factor 1: Citation count on independent sources (strongest predictor).

Businesses with 30+ citations had a 42% AI recommendation rate. Businesses with under 15 citations had a 3% rate. The threshold wasn't linear. There appeared to be a tipping point around 25 to 30 citations where AI confidence crossed a threshold.

This confirms what we've observed in individual case studies: citation depth across independent sources is the foundation of AI visibility.

Factor 2: Entity consistency score (strong predictor).

Businesses scoring 8+ out of 10 on entity consistency had a 38% recommendation rate. Those scoring under 5 had a 4% rate. Even businesses with high citation counts performed poorly when their entity data was inconsistent.

Factor 3: Review distribution across platforms (moderate predictor).

Businesses with reviews on 3+ platforms had a 29% recommendation rate. Those with reviews on only Google had a 9% rate. Review distribution correlated independently with AI visibility even after controlling for citation count.

Factor 4: Published content answering AI-style queries (moderate predictor).

Businesses with 3+ published content pieces targeting question-based queries had a 31% recommendation rate. Those with no published content had an 8% rate. Content alone wasn't enough (without citations, it didn't matter much), but it amplified the effect of strong citation and entity foundations.

Factor 5: Structured data implementation (weak independent predictor, strong amplifier).

Structured data by itself had minimal predictive power for AI recommendations (13% with schema vs. 11% without, when other factors were equal). But when combined with strong citations and entity consistency, businesses with schema performed noticeably better. Schema amplified existing signals rather than creating them, consistent with what we've tested before.

The outliers: what made the 4.5% different

The 9 businesses that were recommended across all three AI platforms shared a specific profile:

• Average citation count: 58 (vs. city average of 19)
• Average entity consistency score: 9.1 out of 10 (vs. city average of 5.4)
• Average review platforms: 4.2 (vs. city average of 1.6)
• All 9 had published content answering industry-specific questions
• 8 of 9 had comprehensive structured data

These businesses weren't necessarily the biggest or the most-reviewed on Google. Three of them had fewer Google reviews than at least one competitor in their industry who was completely invisible to AI. What set them apart was the breadth and consistency of their digital presence across the web, not their depth on any single platform.

The zero-percent industries: what's really going on

The six industries with 0% AI recommendation rates (auto repair, HVAC, plumbing, roofing, landscaping, moving) share three characteristics:

• Extremely thin citation profiles. Average citation count across these industries was 9. Most businesses had nothing beyond a Google Business Profile, a basic website, and maybe an auto-generated Yelp listing. AI tools simply don't have enough data to confidently recommend any specific business.
• High entity inconsistency. Business names and descriptions varied wildly across directories. Many home service businesses operate under informal names ("Bob's Plumbing" on Google, "Robert Johnson Plumbing LLC" on their contractor license, "R. Johnson Plumbing Services" on Angi). AI can't resolve these into a single entity.
• Zero published content. Not one of the 60 home service businesses in our sample (10 per industry x 6 industries) had published a single blog post or resource article. Their websites were brochures, not content platforms.

This isn't because these businesses are bad at what they do. It's because their marketing has been entirely Google-centric: a website, a Google Business Profile, Google reviews, maybe Google Ads. That stack works for Google. It produces nothing for AI.

The opportunity here is massive. In Nashville, the first plumber, HVAC company, or roofer to build a real AI presence will face literally zero competition. The home services market in AI search is wide open in almost every city in the country.

Want to see the full picture for your city and industry? Run your free AI visibility audit at yazeo.com and find out where you stand against your local competitors across ChatGPT, Gemini, Perplexity, and every other major AI platform. The patterns we found in Nashville hold true in virtually every US metro we've tested.

What this means for you

If you're in the 84.5% of businesses that aren't recommended by AI, you're in the majority. But being in the majority isn't a strategy. It's a vulnerability.

The 15.5% that are being recommended are capturing referral-quality leads at zero per-click cost, from a channel that's growing every quarter. They didn't get there by accident. They got there by building the specific signals AI tools evaluate: citations, entity consistency, distributed reviews, published content, and structured data.

And because AI recommendations compound (being recommended generates more signals that lead to more recommendations), the gap between the 15.5% and the 84.5% widens every month.

The question isn't whether you should invest in AI visibility. The data answers that clearly. The question is whether you start while the competition is still near zero in most industries, or whether you wait until the field fills up and the cost to enter multiplies.

Key findings

• 54% of top Google-ranking businesses in Nashville were completely unknown to AI tools.
• Only 4.5% had consistent, accurate, favorable AI presence across all three major platforms.
• Citation count was the strongest predictor of AI visibility, with a tipping point around 25 to 30 independent citations.
• Six home service industries had 0% AI recommendation rates, representing the largest open opportunity in AI search.
• The 9 businesses recommended across all platforms averaged 58 citations, 9.1/10 entity consistency, and 4+ review platforms, far above city averages.
• Google ranking had no meaningful correlation with AI visibility when controlling for citation count and entity consistency.

Frequently asked questions

You're in one of two groups

After auditing 200 businesses, the picture is binary. You're either building AI visibility or you're invisible. There's almost no middle ground.

The 15.5% that are recommended didn't get there by chance. They built the signals. The 84.5% that aren't visible didn't fail. They just haven't started.

The data tells you exactly what to build and in what order. Citations first. Entity consistency second. Review diversification and content third. Structured data fourth. The businesses that follow this sequence get results. The ones that skip steps or ignore the data stay invisible.

Run your free AI visibility audit at yazeo.com and find out exactly where your business stands across ChatGPT, Gemini, Perplexity, and every other major AI platform. See whether you're in the 15.5% or the 84.5%. Then use the data to move from one group to the other.