Local SEO Meets AEO: How to Get Your Local Business Cited by AI Search Engines

The AI Search Shift for Local Businesses

Something fundamental has changed in how people find local businesses. Instead of typing "dentist near me" into Google and scrolling through a list of blue links, a growing number of people are asking ChatGPT, Claude, Perplexity, or Google's AI Overviews the same question — and getting a direct answer with specific recommendations.

This matters enormously for local businesses. When someone searches Google, you compete for one of ten spots on page one. When someone asks an AI, you compete for one of three to five businesses that get mentioned in a single answer. The bar is higher, but the reward is greater — AI recommendations carry more weight because they feel like personal advice, not ads.

The numbers are hard to ignore. ChatGPT has over 400 million weekly active users. Perplexity processes millions of queries daily. Google AI Overviews now appear on the majority of search results. And local queries — "best Italian restaurant in Chicago," "emergency vet open now," "estate lawyer in Miami who speaks Spanish" — are among the fastest growing categories in AI search.

Yet almost no local businesses are optimizing for AI search. They are still focused exclusively on traditional SEO and Google Maps rankings. This creates a massive opportunity. The local businesses that start optimizing for AI search now will build a compounding advantage that becomes harder to catch over time.

This is where Answer Engine Optimization (AEO) comes in. AEO is the practice of optimizing your online presence so that AI search engines cite and recommend your business. And for local businesses, it requires specific strategies that go beyond what you will find in generic AEO guides. This article gives you the complete local AEO playbook.

How Do AI Search Engines Handle Local Queries?

To optimize for AI search, you need to understand where AI models get their local business information. Unlike traditional search engines that primarily use their own crawled index, AI search engines aggregate data from multiple sources and synthesize it into a single answer. Here are the primary sources AI models use for local queries.

Google Business Profile

Your Google Business Profile (GBP) is the single most important data source for local AI search. AI models — including ChatGPT with browsing enabled, Perplexity, and Google's own AI Overviews — pull business names, addresses, hours, phone numbers, categories, and descriptions directly from GBP. If your profile is incomplete, outdated, or unverified, AI models have less data to work with and are less likely to recommend you.

Review Platforms

Reviews on Google, Yelp, TripAdvisor, Healthgrades, Avvo, and other platforms serve as trust signals for AI models. When AI answers a query like "best Thai restaurant in Portland," it does not randomly pick a restaurant. It weighs review volume, average ratings, recency of reviews, and the specific content of reviews. A restaurant with 500 Google reviews averaging 4.6 stars will almost always be cited over one with 30 reviews at 4.2 stars.

Local Business Directories

AI models cross-reference data from directories like Yelp, Yellow Pages, Better Business Bureau, industry-specific directories, and local chamber of commerce listings. This cross-referencing serves two purposes: it verifies accuracy and it fills in gaps. If your business hours are missing from your website but present on Yelp, AI will use the Yelp data. This is why consistency across directories matters so much.

Your Website

AI crawlers visit your website and extract information from your content, your About page, your services pages, and your contact page. They also look at how your content is structured. A website that answers common questions clearly and uses proper headings gives AI models exactly what they need to cite you in response to relevant queries.

Structured Data (Schema Markup)

This is where local businesses have the biggest untapped advantage. Schema markup is machine-readable code on your website that explicitly tells AI models your business name, type, address, phone number, hours, services, price range, and more. Without schema, AI has to infer this information from unstructured text. With schema, you are handing AI the exact data it needs in the exact format it prefers.

Understanding these sources is the foundation for the seven optimization steps that follow. Each step targets one or more of these data sources to maximize your visibility in AI answers.

7 Steps to Get Your Local Business Cited by AI Search Engines

Step 1: Claim and Optimize Your Google Business Profile

Your Google Business Profile is the foundation of local AEO. Every AI model that handles local queries either directly accesses Google's data or indirectly relies on it. An incomplete or unoptimized GBP is like having a storefront with no sign — people walk right past it.

What to do:

• Claim and verify your listing if you have not already. Go to business.google.com and follow the verification process. Verification signals to AI models that your business is legitimate.
• Fill in every single field. Business name, address, phone, website, hours (including holiday hours), business category, secondary categories, business description, service area, attributes (wheelchair accessible, LGBTQ+ friendly, outdoor seating, etc.), and products or services. Every empty field is a missed signal.
• Write a detailed business description that naturally includes your services, location, and what makes you different. This description is directly scraped by AI models. Write it for AI: be specific, factual, and comprehensive.
• Add photos regularly. Businesses with 100+ photos get significantly more engagement. AI models factor in photo count and recency as freshness signals.
• Post Google Business updates weekly. These show AI models that your business is active and current. A business with recent posts looks alive. A business with no posts since 2024 looks abandoned.
• Use the Q&A feature. Add and answer common questions on your GBP. AI models mine this Q&A data heavily because it is already in question-and-answer format — exactly what AI needs to answer user queries.

Step 2: Add LocalBusiness Schema to Your Website

LocalBusiness schema is structured data that tells AI exactly what your business is, where it is, and what it offers. This is the most impactful technical change you can make for local AEO. While generic schema markup matters for any website, LocalBusiness schema is specifically designed for businesses with a physical location or service area.

Here is an example of LocalBusiness schema for a dental practice. You can generate your own using our free schema generator tool:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Dentist",
  "name": "Austin Family Dental",
  "image": "https://austinfamilydental.com/office.jpg",
  "url": "https://austinfamilydental.com",
  "telephone": "+1-512-555-0199",
  "email": "hello@austinfamilydental.com",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "1234 Congress Ave Suite 200",
    "addressLocality": "Austin",
    "addressRegion": "TX",
    "postalCode": "78701",
    "addressCountry": "US"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": 30.2672,
    "longitude": -97.7431
  },
  "openingHoursSpecification": [
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": ["Monday","Tuesday","Wednesday","Thursday"],
      "opens": "08:00",
      "closes": "17:00"
    },
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": "Friday",
      "opens": "08:00",
      "closes": "14:00"
    }
  ],
  "priceRange": "$$",
  "servesCuisine": "",
  "areaServed": {
    "@type": "City",
    "name": "Austin, TX"
  },
  "hasOfferCatalog": {
    "@type": "OfferCatalog",
    "name": "Dental Services",
    "itemListElement": [
      {"@type": "Offer", "itemOffered": {"@type": "Service", "name": "General Dentistry"}},
      {"@type": "Offer", "itemOffered": {"@type": "Service", "name": "Cosmetic Dentistry"}},
      {"@type": "Offer", "itemOffered": {"@type": "Service", "name": "Emergency Dental Care"}},
      {"@type": "Offer", "itemOffered": {"@type": "Service", "name": "Pediatric Dentistry"}}
    ]
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.8",
    "reviewCount": "347"
  }
}
</script>

Notice how specific this is. It includes the exact business type (Dentist, not just LocalBusiness), geo coordinates, opening hours, services offered, price range, and aggregate ratings. AI models love this level of detail because it eliminates ambiguity. Use the most specific Schema.org type for your business: Restaurant, Dentist, Plumber, LegalService, RealEstateAgent, HealthClub, and so on.

Step 3: Build Consistent NAP Across All Directories

NAP stands for Name, Address, and Phone number. NAP consistency means your business information is identical — not similar, not close, but identical — across every platform where your business appears. This is one of the most overlooked aspects of local AEO, and it directly impacts whether AI models trust your business enough to cite it.

AI models cross-reference multiple sources. When they find consistent information everywhere, confidence goes up and citation probability increases. When they find inconsistencies — your website says "123 Main St" but Yelp says "123 Main Street, Suite A" — confidence drops.

Where to check and fix your NAP:

• Your website (header, footer, contact page)
• Google Business Profile
• Yelp
• Facebook Business Page
• Apple Maps
• Bing Places
• Yellow Pages
• Better Business Bureau
• Industry-specific directories (Healthgrades for doctors, Avvo for lawyers, HomeAdvisor for contractors, TripAdvisor for restaurants)
• Local chamber of commerce
• Your schema markup (must match everything above)

Common NAP mistakes: Using "St" on one site and "Street" on another. Listing a tracking phone number on directories instead of your main number. Having an old address on forgotten directory listings. Using a DBA name on some sites and your legal name on others. Fix every inconsistency you find. Set a calendar reminder to audit your NAP quarterly.

Step 4: Get Reviews on Multiple Platforms

Reviews are the social proof that AI models use to evaluate local businesses. When AI answers "best pizza in Brooklyn," it is not guessing. It is synthesizing review data from Google, Yelp, TripAdvisor, and other platforms to identify which businesses are genuinely well-regarded.

A single platform is not enough. AI models cross-reference reviews across multiple sites. A business with 200 Google reviews but zero Yelp reviews looks less trustworthy than one with 150 Google reviews and 80 Yelp reviews. Multi-platform review presence signals that real customers are consistently satisfied across different channels.

Your review strategy should include:

• Google Reviews — The most important platform. Aim for consistent volume (a few reviews per week is better than 50 reviews in one month then nothing).
• Yelp — Still heavily cited by AI for restaurants, home services, and local retail.
• Industry-specific platforms — Healthgrades and Zocdoc for healthcare providers, Avvo and Martindale-Hubbell for lawyers, HomeAdvisor and Angi for contractors, TripAdvisor for hospitality and travel businesses.
• Facebook Recommendations — Often overlooked, but AI models do reference Facebook business data.

How to get more reviews: Ask at the point of service. Send a follow-up text or email with a direct link to your review page. Make it easy — a QR code at checkout, a link in your email signature, a card with your receipt. Respond to every review, positive and negative. AI models factor in response rate as a signal of an active, engaged business.

Step 5: Create Location-Specific Content in Q&A Format

This is where most local businesses leave the biggest opportunity on the table. Your website content should directly answer the questions that people ask AI about your type of business in your location.

Think about how people query AI for local businesses. They do not type keywords — they ask questions:

• "What is the best dentist in Austin for kids?"
• "Is there a plumber in Dallas that works on weekends?"
• "Which Italian restaurants in Chicago have outdoor seating?"
• "Can you recommend a real estate agent in Miami who specializes in condos?"
• "What is the best gym in Denver with a pool?"

Your website should have content that directly answers these types of questions. Create pages and blog posts that combine your location, your service, and common qualifiers. Use question-based headings. Lead with the answer, then provide supporting detail. This is the core principle of AEO — structure your content so AI can extract and cite it easily.

Content ideas for local businesses:

• A services page with a Q&A section for each service ("Do you offer emergency dental care on weekends?" "Yes, Austin Family Dental offers emergency dental appointments every Saturday from 9am to 1pm.")
• A neighborhood or area guide ("Dental Care in Downtown Austin: What You Need to Know")
• Blog posts targeting specific local queries ("5 Things to Look for in an Austin Pediatric Dentist")
• A detailed FAQ page covering pricing, insurance, hours, parking, accessibility, and other common concerns

Every piece of location-specific content is another opportunity for AI to cite your business when someone asks a relevant local question. Learn more about how AI models evaluate and extract content in our guide to how AI search engines work.

Step 6: Add FAQ Schema Answering Local Questions

FAQ schema is structured data that marks up your frequently asked questions in a format that AI models can parse directly. While creating Q&A content on your pages is important (Step 5), adding FAQ schema makes that content machine-readable — it is the difference between AI having to find and interpret your answers versus having them handed over in a structured format.

For local businesses, your FAQ schema should cover the questions customers actually ask — not generic industry content, but specific, location-relevant questions. You can generate FAQ schema instantly with our free FAQ schema generator.

Here is an example for a local plumbing company:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "Do you offer emergency plumbing in Dallas on weekends?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Yes. We provide 24/7 emergency plumbing services throughout the Dallas-Fort Worth area, including weekends and holidays. Call 214-555-0199 for immediate service."
      }
    },
    {
      "@type": "Question",
      "name": "How much does a plumber charge in Dallas?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Our standard service call is $89, which includes the first 30 minutes of labor. Most common repairs (faucet replacement, drain clearing, toilet repair) range from $150-$400. We provide free estimates for larger jobs."
      }
    },
    {
      "@type": "Question",
      "name": "What areas do you serve in the Dallas-Fort Worth area?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "We serve Dallas, Fort Worth, Arlington, Plano, Irving, Garland, Grand Prairie, Frisco, McKinney, and surrounding communities within a 40-mile radius of downtown Dallas."
      }
    }
  ]
}
</script>

Notice how each question includes the location and specific details. This is not generic FAQ content — it is locally targeted, specific, and directly useful. AI models prioritize FAQ schema because it provides ready-made answers they can cite with confidence. Read our complete AEO checklist for more on how FAQ schema fits into a comprehensive optimization strategy.

Step 7: Create an llms.txt File Describing Your Business

An llms.txt file is a plain text file at your website's root (yourdomain.com/llms.txt) that gives AI models a structured summary of your business. Think of it as a cover letter to every AI search engine — here is who we are, what we do, where we are, and why you should recommend us.

For local businesses, llms.txt is especially powerful because you can include information that AI models might not find elsewhere: your service area, specialties, languages spoken, certifications, parking details, accessibility information, and more.

Here is an llms.txt template for a local business:

# Austin Family Dental

> Austin Family Dental is a family-owned dental practice in downtown Austin, Texas, providing comprehensive dental care for patients of all ages since 2015.

## Location
- Address: 1234 Congress Ave Suite 200, Austin, TX 78701
- Phone: (512) 555-0199
- Service Area: Austin, Round Rock, Cedar Park, Georgetown, Pflugerville

## Hours
- Monday-Thursday: 8:00 AM - 5:00 PM
- Friday: 8:00 AM - 2:00 PM
- Saturday: 9:00 AM - 1:00 PM (emergencies only)
- Sunday: Closed

## Services
- General Dentistry (cleanings, exams, fillings)
- Cosmetic Dentistry (veneers, whitening, bonding)
- Emergency Dental Care (same-day appointments available)
- Pediatric Dentistry (ages 2+)
- Orthodontics (Invisalign certified provider)

## Key Pages
- [Homepage](https://austinfamilydental.com): Overview and booking
- [Services](https://austinfamilydental.com/services): Full service list
- [About](https://austinfamilydental.com/about): Our team and story
- [Contact](https://austinfamilydental.com/contact): Location and hours
- [FAQ](https://austinfamilydental.com/faq): Common patient questions
- [Blog](https://austinfamilydental.com/blog): Dental health articles

## Insurance
- Accepts Delta Dental, Cigna, Aetna, MetLife, Guardian
- In-network with most major PPO plans
- Financing available through CareCredit

## Languages
- English, Spanish

## Credentials
- Dr. Sarah Chen, DDS — UT Health San Antonio School of Dentistry
- Member: American Dental Association, Texas Dental Association
- 4.8 stars on Google (347 reviews)

This single file gives AI models everything they need to accurately recommend your business for relevant local queries. Most local businesses do not have an llms.txt file, so creating one gives you an immediate edge. For the complete setup guide, read our article on what llms.txt is and why your website needs one.

Also make sure your robots.txt allows AI crawlers like GPTBot, ClaudeBot, and PerplexityBot to access your site. If AI cannot crawl your site, none of these optimizations matter.

Which Local Business Types Benefit Most from AEO?

Every local business benefits from AI search optimization, but some categories see outsized returns because of how frequently they are queried in AI search. Here are the local business categories where AEO has the highest impact. Organizations like nonprofits and community foundations face their own distinct challenges — see our nonprofit AEO guide for strategies tailored to mission-driven organizations.

The common thread across all these business types: customers ask AI specific, qualified questions. They do not ask for a generic list — they ask for businesses that meet specific criteria (location, hours, specialties, insurance, languages, price range). The businesses that provide this specific information in structured formats win the AI citation.

No matter your business type, start by scanning your site with Vida AEO to see where you stand. The audit checks your schema markup, structured data, and AI accessibility — all critical factors for local businesses.

Common Mistakes That Keep Local Businesses Out of AI Results

Even businesses that are doing some SEO work often make specific mistakes that tank their AI visibility. Here are the most common ones we see.

No Schema Markup at All

The majority of local business websites have zero schema markup. No LocalBusiness schema, no FAQ schema, no Organization schema. This forces AI models to guess your business details from unstructured text — and AI guesses wrong more often than you think. A restaurant without schema might get its hours wrong. A dentist without schema might not get cited for the specific services they offer. Fix this first. Use our free schema generator to create your LocalBusiness schema in minutes.

Inconsistent NAP Information

We covered this in Step 3, but it bears repeating because it is so prevalent. When your name, address, or phone number differs across directories, AI models lose confidence and may skip your business entirely. The most common culprit: old directory listings with a previous phone number or address that were never updated after a move or phone change.

No Review Strategy

Many local businesses treat reviews as something that happens to them rather than something they actively manage. They do not ask for reviews, they do not respond to reviews, and they have reviews on only one platform. AI models weight review signals heavily for local queries. A proactive review strategy across multiple platforms is not optional — it is foundational.

Blocking AI Crawlers

Some website templates and hosting providers block AI crawlers by default in robots.txt. If GPTBot, ClaudeBot, or PerplexityBot are disallowed, your website is invisible to those AI search engines — no matter how good your content is. Check your robots.txt file right now. Our robots.txt guide for AI search shows you exactly what to look for and how to fix it.

Generic Content with No Local Specificity

A dentist whose website says "We offer comprehensive dental services" gives AI nothing to work with for local queries. A dentist whose website says "Austin Family Dental offers same-day emergency dental appointments in downtown Austin, TX, with Saturday hours and in-network coverage for Delta Dental, Cigna, and Aetna" gives AI exactly what it needs. Be specific. Include your city, neighborhood, service area, differentiators, and qualifiers. That specificity is what gets you cited when someone asks a qualified local question.

No llms.txt File

This is the easiest win on this entire list, and almost no local businesses have done it. Creating an llms.txt file takes less than an hour and gives AI models a direct, structured summary of your business. Read our complete llms.txt guide and get it done today.

Frequently Asked Questions

Do local businesses need to worry about AI search optimization?

Yes. AI search engines like ChatGPT, Claude, and Perplexity are already answering local queries — "best dentist in Austin," "plumber near me that works weekends," "Italian restaurant in Chicago with outdoor seating." If your local business is not optimized for AI, you are invisible to a growing segment of potential customers who are using AI instead of Google to find local services. The shift is happening now, not in the future.

What is LocalBusiness schema and why does it matter for AI search?

LocalBusiness schema is structured data markup (JSON-LD code) that tells AI models exactly what your business is, where it is located, what hours you operate, and what services you offer. AI models use this structured data to provide accurate, detailed answers about local businesses. Without it, AI has to guess based on unstructured text, which often leads to errors or your business being skipped entirely. You can create yours with our free schema generator.

How do AI search engines find information about local businesses?

AI search engines pull local business information from multiple sources: Google Business Profile, review platforms like Yelp and industry-specific directories, your website content, schema markup on your site, local business directories, and files like llms.txt. The more consistent and structured your information is across these sources, the more likely AI will cite your business accurately. Read our guide on how AI search engines work for a deeper understanding of AI's data sources and ranking signals.

What is NAP consistency and why does AI search care about it?

NAP stands for Name, Address, and Phone number. NAP consistency means your business name, address, and phone number are identical across every online directory, your website, Google Business Profile, Yelp, and all other listings. AI models cross-reference multiple sources to verify business information. If your NAP is inconsistent — different phone numbers on different sites, a slightly different business name, or an old address on some directories — AI models lose confidence in your data and are less likely to cite your business.

Should local businesses create an llms.txt file?

Absolutely. An llms.txt file is a plain text file at your website root that gives AI models a structured summary of your business — what you do, where you are located, your services, your hours, and your service area. For local businesses, this is especially valuable because it provides AI with verified, first-party information about your location and services. Most local competitors do not have one yet, so creating one gives you an immediate advantage.

How long does local AEO take to implement?

Most local businesses can implement the seven steps in this guide within one to two weeks. Claiming and optimizing your Google Business Profile takes a few hours. Adding LocalBusiness schema takes an afternoon if you use a schema generator tool. Building NAP consistency across directories takes a few days of research and updates. Creating location-specific content and FAQ schema can be done in a weekend. The llms.txt file takes under an hour. Start with your Google Business Profile and schema markup for the biggest immediate impact.

Your Local Competitors Are Not Doing This Yet

That is the opportunity. AI search for local businesses is in its earliest stages. The vast majority of restaurants, dentists, plumbers, lawyers, real estate agents, and other local businesses have done zero AEO work. They have no LocalBusiness schema, no llms.txt file, inconsistent NAP data, no FAQ schema, and generic content that gives AI nothing specific to cite.

Every step you implement from this guide puts distance between you and your competitors. And unlike traditional SEO, where ranking improvements can take months, some of these changes can improve your AI visibility within weeks. Schema markup, llms.txt, and Google Business Profile optimizations are picked up relatively quickly by AI crawlers.

Start with the highest-impact steps first. Optimize your Google Business Profile (Step 1) because it is the most-referenced data source for local AI queries. Add LocalBusiness schema (Step 2) because it makes your business information machine-readable. Create an llms.txt file (Step 7) because it takes under an hour and almost no local competitor has one.

Then build out the remaining steps: NAP consistency, review strategy, location-specific content, and FAQ schema. Each step compounds on the others. Together, they create a local AEO foundation that makes your business the obvious choice when AI answers local queries.

Want to see where your local business stands right now? Scan your site free with Vida AEO and get your AI visibility score in under 60 seconds. See exactly which optimizations you need and in what order to prioritize them.