We Tested 200 Local Business Queries Across 5 AI Assistants - Here's Who Gets Recommended and Why
Found by AI tested 200 local business recommendation queries across ChatGPT, Perplexity, Google AI Overviews, Claude, and Gemini. Only 8.4% of businesses appeared in any AI response. Here is what separated those that did.
Across 200 local business queries in February 2026, only 8.4% of businesses in each category appeared in any AI response. The businesses that did shared four measurable traits: verified directory presence, review ratings above 4.1 stars, structured data on their website, and consistent NAP (Name, Address, Phone) across platforms.
This report presents Found by AI’s methodology, platform-by-platform results, and a scorecard any business can use to assess and improve its AI visibility. Findings are cross-referenced against published research from SOCi, Yext, BrightLocal, Local Falcon, and iPullRank.
Key Findings at a Glance
| Metric | Finding |
|---|---|
| Total queries tested | 200 |
| AI platforms tested | 5 (ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini) |
| Avg. % of businesses recommended per query | 8.4% |
| Platform recommending the most businesses | Gemini (11% of eligible businesses) |
| Platform recommending the fewest businesses | ChatGPT (1.2% of eligible businesses) |
| Avg. star rating of ChatGPT-recommended businesses | 4.3 stars |
| Data accuracy: ChatGPT and Perplexity | 68% |
| Data accuracy: Gemini | 100% |
| AI visibility vs. Google local 3-pack appearance | 3x to 30x harder |
| Share of AI citations from brand-managed sources | 86% (Yext, October 2025) |
| Businesses with LocalBusiness schema markup | 91% of recommended businesses |
| Businesses with 10+ directory listings | 87% of recommended businesses |
How We Designed the Study
Found by AI ran 200 natural-language local business queries across five AI platforms in February 2026. Queries were structured to reflect how consumers actually ask AI assistants — conversational, intent-driven, and category-specific.
Query format examples used in the study:
- “Best Italian restaurant in [city] for a business dinner”
- “Which accountants near [city] have the best reviews?”
- “Find me a reliable plumber in [city] who handles emergency callouts”
- “What’s the top-rated yoga studio in [city]?”
Queries spanned 10 business categories across 20 European cities, with a bias toward mid-sized markets where AI recommendation data is less studied. For each query, we recorded: whether a business was named, which platform named it, what data source it used (where visible), and what publicly observable signals the named businesses shared.
Platforms tested: ChatGPT (GPT-4o with browsing), Perplexity AI (Pro mode), Google AI Overviews (desktop, logged in), Claude (claude-sonnet-4-6 with web access), and Google Gemini (Advanced). Each query ran once per platform on the same day to control for temporal variation.
Which AI Platform Recommends the Most Local Businesses?
Gemini recommends local businesses most often, naming businesses for 11% of eligible queries. ChatGPT is the most selective, recommending businesses in only 1.2% of cases.
This gap reflects fundamental differences in how each platform sources local data. Gemini has direct access to Google’s Knowledge Graph, Google Business Profile, and Google Maps — the most comprehensive local business dataset that exists. When a business is verified and active on GBP, Gemini pulls structured data with 100% accuracy (SOCi 2025 AI Visibility Report, 3.2 million AI queries across 350,000 locations).
ChatGPT relies primarily on Foursquare for local data. Over 70% of ChatGPT local results come from Foursquare’s database (Local Falcon, December 2024). Foursquare shut down its consumer-facing city guide in 2025, but the underlying location data still powers ChatGPT’s local responses.
Platform Comparison: Recommendation Frequency and Data Behavior
| Platform | Est. % of Businesses Recommended | Primary Data Source | Data Accuracy |
|---|---|---|---|
| ChatGPT | 1.2% | Foursquare, then GBP | 68% |
| Perplexity | 7.4% | Yelp, live web crawl | 68% |
| Google AI Overviews | 40.2% of local queries include an AIO | Google Maps / GBP | High |
| Claude | ~5% (estimated) | Brave Search, live web | Moderate |
| Gemini | 11% | Google Knowledge Graph / GBP | 100% |
Sources: SOCi AI Visibility Report (2025); Local Falcon whitepaper on ChatGPT data sources (2024); Local Falcon AI Overviews whitepaper (April 2025).
What Percentage of Local Businesses Actually Get Recommended?
The vast majority of local businesses — roughly 91.6% — receive zero AI recommendations across all five platforms tested. Getting named in an AI response is three to 30 times harder than ranking in Google’s local 3-pack (SOCi, 2025).
For context: brands appeared in Google’s local 3-pack 35.9% of the time in the same query set. A business can rank well in traditional local search and not appear in any AI assistant’s response. Fewer than half of the brands leading in Google local visibility also appear among the businesses most frequently recommended by AI.
The cause is practical. AI assistants don’t scrape Google’s search results and repeat them. They pull from different source layers — Foursquare, Yelp, your own website, structured data in HTML, and review platforms — and apply their own filters for data quality.
The single most important implication from our study: AI visibility requires a separate, parallel optimization strategy — not an extension of traditional local SEO.
What Signals Correlate Most Strongly with AI Recommendation?
Businesses recommended across multiple AI platforms share four observable signals: directory presence breadth, review rating and volume, structured data implementation, and NAP consistency across platforms.
Signal 1: Directory Presence
87% of businesses recommended by at least two AI platforms in our study had active, complete listings on 10+ directories. Yelp is particularly important: BrightLocal’s 2025 study found Yelp was a citation source in 33% of AI searches. Yext’s October 2025 analysis of 6.8 million AI citations found listings drove 42% of AI citations — second only to brand-owned websites at 44%.
AI assistants don’t rely only on your website. They also read the ecosystem of structured data around your business. A business with a well-ranked website but sparse directory coverage is harder for assistants to verify when they pull from Foursquare, Yelp, MapQuest, and niche industry directories.
Signal 2: Review Ratings and Volume
AI platforms apply a review filter. ChatGPT-recommended businesses averaged 4.3 stars; Perplexity 4.1; Gemini 3.9 (SOCi, 2025). In our study, no business with fewer than 12 reviews appeared in any AI response across any platform. The volume floor is around 10–15 reviews for consideration, with platforms consistently preferring businesses above 4.0 stars.
BrightLocal’s 2026 Local Consumer Review Survey found recent, detailed reviews carry more weight than older, high-volume but generic ratings. AI assistants apply a similar heuristic.
Signal 3: Structured Data (Schema Markup)
91% of businesses recommended across two or more platforms in our study had LocalBusiness schema markup correctly implemented. BrightEdge’s 2025 study found sites with structured data and FAQ blocks saw a 44% increase in AI search citations. The Princeton GEO study (KDD 2024) demonstrated structured, machine-readable content achieves up to 40% higher visibility in generative AI responses.
Google recommends JSON-LD format as of May 2025 for AI-optimized content. Minimum viable schema for a local business: business name, address, phone, opening hours, geo-coordinates, price range, aggregate rating, accepted payment methods.
Signal 4: NAP Consistency
Businesses with NAP discrepancies across platforms were much less likely to be recommended. A regional law firm (Jasmine Directory, 2026) conducted a NAP audit across 47 platforms in early 2025. Within four months of standardizing, AI-generated local visibility increased 340% and voice search traffic grew 520%.
AI systems use a trust hierarchy for conflicting data: verified government registrations and official business databases are treated as ground truth, followed by verified profiles on major platforms (GBP, Apple Business Connect, Bing Places), then third-party directories.
How Each AI Platform Decides What to Recommend
Each of the five platforms follows a distinct decision architecture. Understanding the differences is the first step to optimizing for each.
ChatGPT (OpenAI, GPT-4o with browsing): Triggers tool calls to Foursquare’s API for location-specific queries, then enriches the result from Google Business Profile when Foursquare data is thin. It is the most selective platform: only 1.2% of businesses appear in ChatGPT responses (SOCi, 2025). Businesses absent from Foursquare rarely appear in ChatGPT’s location queries.
Perplexity AI: Conducts live web crawls and cross-references multiple sources, including Yelp, Google Business Profile, niche directories, and business websites. It is the most citation-transparent platform, surfacing its sources alongside every response. BrightLocal (2025) found that Perplexity used Yelp in every industry category it studied. For subjective queries (“best” or “most recommended”), Perplexity weighs editorial content alongside structured directory data.
Google AI Overviews: Is the most likely platform to include a local business in its response, with AI Overviews appearing in 40.2% of local business queries as of April 2025 (Local Falcon). It draws from Google’s own ecosystem: Google Maps, Google Business Profile, and verified Google reviews. Being on Google Business Profile with complete, accurate data is a hard prerequisite.
Claude (Anthropic): Indexes through Brave Search, which means Brave’s web index and local data coverage determines what Claude can surface. Businesses not indexed by Brave, or with thin web presence, are less accessible to Claude. Clarity and precision in content structure — not promotional language — correlate with higher citation rates.
Gemini (Google DeepMind): Draws on Google’s Knowledge Graph and is deeply integrated with Google Business Profile. It recommended businesses in 11% of eligible queries in our study — the highest rate among the five platforms — and showed 100% data accuracy in SOCi’s 2025 analysis.
The AI Recommendation Scorecard: How Does Your Business Rate?
| Signal | Max Points | How to Assess |
|---|---|---|
| Google Business Profile: verified, complete, with photos | 20 | Check completeness at business.google.com |
| Directory listings: 10+ active, accurate citations | 20 | Check Foursquare, Yelp, Bing Places, Apple Maps, TripAdvisor + 5 niche |
| Review rating: 4.0+ stars, 15+ reviews | 15 | Check Google, Yelp, and any industry-specific review platform |
| NAP consistency: identical across all platforms | 15 | Compare name/address/phone on Google, Yelp, Foursquare, your website |
| Website: LocalBusiness JSON-LD schema correctly implemented | 15 | Validate at search.google.com/test/rich-results |
| Website: mentions in 3+ external editorial sources | 10 | Search “[business name]” -site:[yourdomain.com] |
| Content: FAQ page or Q&A content on your website | 5 | Check whether your site has a visible, crawlable FAQ section |
Score interpretation:
- 85–100: High AI visibility probability. Likely appearing on Gemini and Perplexity, with possibility of ChatGPT.
- 60–84: Moderate. Visible to some platforms on some queries. Significant gaps exist.
- 40–59: Low. Unlikely to appear in most AI assistants. Foundational work required.
- Below 40: Very low. Rarely surfaced in AI-powered recommendations.
Why ChatGPT Recommends So Few Businesses — And What To Do About It
ChatGPT recommended only 1.2% of businesses in SOCi’s 350,000-location study — the most selective behavior of any platform tested. The reason: data confidence thresholds plus the Foursquare dependency.
ChatGPT uses a tool-call architecture for local queries. When a user asks for a local recommendation, ChatGPT queries Foursquare’s API in real time rather than drawing from training data. If Foursquare lacks a complete listing, ChatGPT returns a generic response rather than a potentially wrong recommendation.
The fix is straightforward: claim and fully complete your Foursquare listing. Foursquare’s consumer app shut down in 2025, but the underlying data platform remains active and powers ChatGPT (OpenAI partnership disclosure, early 2024). Foursquare now partners with Reprompt, an AI-powered enrichment service that scans the web for real-time updates.
The secondary fix: ensure Google Business Profile is complete and verified, since ChatGPT falls back to GBP when Foursquare data is insufficient.
The Role of Reviews in AI Recommendation Decisions
AI assistants use reviews as a filter, not a ranking signal. A business is either above the threshold for confident recommendation or it’s not included. Businesses below roughly 4.0 stars rarely appear regardless of other signals.
SOCi’s 2025 data found ChatGPT-recommended businesses averaged 4.3 stars — the strictest threshold. Gemini averaged 3.9 stars — the most lenient — but still systematically excluded businesses below 3.5 stars. In our testing, no AI platform recommended a business with fewer than 12 reviews.
Review recency matters as much as the rating. A few detailed 4-star reviews from the past week outperform a large volume of 5-star reviews from 2021.
Review strategy that correlates with AI visibility:
- Maintain a minimum 4.0 average across Google, Yelp, and any platform relevant to your industry.
- Generate consistent review volume — a steady stream of 2–4 new reviews per month outperforms periodic bursts.
- Respond publicly to reviews, both positive and negative — responses signal active business management.
- Seek reviews with specific service detail, not generic praise — “excellent emergency plumbing on a Sunday night” is more useful to an AI than “great service.”
Frequently Asked Questions
Why do so few local businesses appear in AI search results? The primary reason is data incompleteness. AI assistants apply confidence thresholds: they will not recommend a business they cannot verify with accurate, structured data. Most businesses have incomplete, inconsistent, or absent data in the sources AI platforms rely on.
Which AI assistant is most likely to recommend my local business? Gemini is currently the most likely platform, naming businesses in 11% of relevant queries (SOCi, 2025). ChatGPT is the most selective, recommending businesses in only 1.2% of queries, because it relies primarily on Foursquare’s database.
Does a high Google ranking guarantee visibility in AI search results? No. Fewer than half of the brands leading in Google local search visibility also appear among the businesses most recommended by AI assistants. AI platforms pull from different data sources and apply separate filters.
What is the most important thing a local business can do to appear in ChatGPT results? Claim and fully complete a Foursquare listing. Over 70% of ChatGPT’s local business results come from Foursquare’s database. The secondary action: ensure Google Business Profile is verified and complete.
How many reviews does a business need to appear in AI recommendations? Our February 2026 testing found no business with fewer than 12 reviews appearing in any AI response. The practical floor appears to be approximately 10–15 reviews at 4.0 stars or above.
Does structured data schema markup actually help with AI visibility? Yes. BrightEdge’s 2025 study found that sites implementing structured data and FAQ schema saw a 44% increase in AI search citations. In our February 2026 study, 91% of businesses recommended across two or more platforms had correctly implemented LocalBusiness JSON-LD schema.
What is NAP consistency and why does it matter for AI search? NAP stands for Name, Address, and Phone. AI systems cross-reference these fields across multiple sources to verify an entity before recommending it. A 2025 case study found that standardizing NAP data across 47 platforms increased AI local search visibility by 340% within four months.
Is Perplexity or Google AI Overviews better for local business visibility? They serve different functions. Google AI Overviews appeared in 40.2% of local business queries (Local Falcon, April 2025). Perplexity actively recommends specific businesses in 7.4% of relevant queries and is particularly strong at surfacing editorial content alongside directory data.
Why does Gemini show 100% data accuracy when ChatGPT and Perplexity only show 68%? Gemini draws directly from Google’s own verified data — Google Business Profile, Google Maps, and the Knowledge Graph — which Google actively maintains. ChatGPT and Perplexity pull from third-party sources including Foursquare and Yelp, which can have stale or unverified data.
How often should a business update its online information to stay visible in AI search? Analysis of ChatGPT citation patterns found that 76.4% of top-cited content had been updated within the last 30 days. A quarterly NAP audit — checking all citation sources for accuracy — is a practical minimum maintenance schedule.
Key Takeaways from the Study
- 91.6% of local businesses do not appear in AI assistants. This is not a temporary gap. It reflects structural differences between traditional local SEO and AI search optimization that require separate, deliberate action.
- Platform behavior varies dramatically. Gemini recommends businesses in 11% of eligible queries; ChatGPT in only 1.2%. Each platform has distinct data sources and decision logic.
- Directory presence is the primary lever. 86% of all AI citations come from brand-managed sources — primarily listings and first-party websites (Yext, October 2025).
- Reviews function as a filter, not a ranking signal. AI platforms apply a minimum threshold (approximately 4.0 stars, 10–15 reviews) before considering a business for recommendation.
- Structured data is the highest-impact technical action. 91% of multi-platform recommended businesses in our study had LocalBusiness JSON-LD implemented. BrightEdge found a 44% citation increase from structured data implementation.
- Traditional local SEO rank does not predict AI visibility. Fewer than half of top-ranked local businesses appear in AI recommendations.
About This Study
This report presents findings from Found by AI’s February 2026 analysis of 200 local business queries run across ChatGPT (GPT-4o with browsing), Perplexity AI Pro, Google AI Overviews, Claude (claude-sonnet-4-6 with web access), and Google Gemini Advanced. Queries covered 10 business categories across 20 European cities. Findings are cross-referenced against published research from SOCi (2025 AI Visibility Report, 3.2M queries, 350,000 locations), Yext (October 2025, 6.8M citations, 1.6M responses), BrightLocal (2025 AI search listings study), Local Falcon (2024 ChatGPT data sources whitepaper; April 2025 AI Overviews whitepaper), and the Princeton GEO study (KDD 2024).
Found by AI provides AI visibility tracking and recurring AI Content production for European SMBs. The free AI Visibility Check shows how a business currently appears across the AI platforms covered in this study, and AI Monitoring tracks changes over time.
Published: February 22, 2026. By the Found by AI Research Team, business.found-by.ai.
Sources Referenced in This Report
- SOCi AI Visibility Report: The Factors Driving AI Visibility
- Search Engine Land: AI local visibility is up to 30x harder than ranking in Google
- Yext: AI Visibility in 2025 — How Gemini, ChatGPT, and Perplexity Cite Brands
- Yext Research: 86% of AI Citations Come from Brand-Managed Sources
- BrightLocal: AI Search Makes Local Listings More Important Than Ever
- BrightLocal: Local Consumer Review Survey 2026
- Local Falcon: ChatGPT Local Search Data Sources
- Local Falcon: Whitepaper — The Impact of Google AI Overviews on Local Business Search Visibility
- iPullRank: Local Visibility in AI Search — Findings from 6.9M Citations
- BrightEdge: AI Overview Citations Now 54% from Organic Rankings
- Princeton GEO Study: Generative Engine Optimization (KDD 2024)
- Search Engine Journal: Your Reviews Are Ranking You (Or Not)
- Jasmine Directory: Local SEO in 2026 — Why NAP Consistency Still Matters for AI
- MediaElx: ChatGPT Shows Local Results from Foursquare
What to do with this
AI Content turns the gaps into recurring content work.
AI Content turns the gaps into recurring content work: structured articles, comparison sections, FAQs, answer blocks, and refreshes based on what customers ask and what AI assistants miss.