AI engines resolve local entities differently than national brands. A verified NAP, an optimized Google Business Profile, and LocalBusiness schema give a local HVAC company or accountant a citation footprint that Fortune 500 brands cannot easily replicate. This guide covers the exact steps, in order of citation impact.
By William Bouch · Last updated September 27, 2026
Standard AEO focuses on getting cited for informational queries — definitions, how-tos, comparisons. Local AEO targets a different trigger: geographic intent queries. When AI engines handle "near me" or city-name queries, they pull from a different data layer than their general knowledge base.
AI engines use entity resolution to confirm a business is real. They cross-reference your name, address, and phone number (NAP) across multiple sources. If your NAP is inconsistent across directories, the AI cannot confidently resolve your entity — and you don't get cited.
NAP stands for Name, Address, Phone. Every mention of your business across the web needs to use exactly the same format. "St." vs "Street", "Suite 100" vs "#100", "(828) 555-0100" vs "828-555-0100" — these variations cause AI entity resolution to fragment your business into multiple conflicting entities, suppressing citation probability.
Pick one NAP format and never deviate
Your website's LocalBusiness JSON-LD is one of the most authoritative NAP sources AI engines read — they trust machine-readable structured data over inconsistent directory text. Add this to every page of your site, or at minimum your homepage and contact page.
Replace the placeholder values. Use your exact GBP NAP format. The @id should be your homepage URL + #localbusiness.
{
"@context": "https://schema.org",
"@type": "LocalBusiness",
"@id": "https://yoursite.com/#localbusiness",
"name": "Your Business Name",
"description": "One sentence: what you do, where, and for whom.",
"url": "https://yoursite.com",
"telephone": "+1-555-000-0000",
"email": "hello@yoursite.com",
"address": {
"@type": "PostalAddress",
"streetAddress": "123 Main St",
"addressLocality": "Your City",
"addressRegion": "ST",
"postalCode": "00000",
"addressCountry": "US"
},
"geo": {
"@type": "GeoCoordinates",
"latitude": 35.5951,
"longitude": -82.5515
},
"openingHoursSpecification": [
{
"@type": "OpeningHoursSpecification",
"dayOfWeek": ["Monday","Tuesday","Wednesday","Thursday","Friday"],
"opens": "09:00",
"closes": "17:00"
}
],
"priceRange": "$$",
"hasMap": "https://maps.google.com/?q=YOUR+BUSINESS+NAME",
"sameAs": [
"https://www.google.com/maps?cid=YOUR_CID",
"https://www.yelp.com/biz/your-business",
"https://www.facebook.com/yourbusiness",
"https://linkedin.com/company/yourbusiness"
],
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.9",
"reviewCount": "47",
"bestRating": "5",
"worstRating": "1"
}
}
Key fields for AI engines: sameAs links your entity across platforms. aggregateRating makes your review score citable. geo enables spatial queries ("nearest X to Y"). Remove fields that don't apply.
Schema.org has 200+ LocalBusiness subtypes. Using the most specific type increases semantic relevance — AI engines can match your entity to a category, not just a name.
Your Google Business Profile (GBP) is the single most important data source for AI local citations. Google AI Overviews, ChatGPT (which uses Bing, which mirrors Google Maps data), and Perplexity all draw heavily from GBP for local answers. An incomplete or outdated GBP profile is the most common cause of local AEO failure.
The GBP Q&A section is publicly indexed and regularly scraped by AI training datasets. Adding 5–10 real questions with thorough answers creates additional direct Q&A pairs that AI engines can cite. Use the same questions you'd put in your FAQPage schema — this creates a consistent, cross-referenced answer layer across your website and your GBP simultaneously.
When an AI engine is asked "is [business name] good?" or "top-rated [service] in [city]," it's reading your review profile — not just counting stars. The volume, recency, and keyword content of reviews all feed AI citation decisions.
AI engines weight recent reviews more heavily than old ones. A business with 12 reviews in the last 6 months will outperform a competitor with 80 reviews from 3 years ago. Aim for a consistent review acquisition cadence (2–4 per month minimum).
Reviews that mention your service category and city are more valuable than generic 5-star reviews. When requesting reviews, remind customers to mention what service they used and where. "Best HVAC repair in Asheville" in a review is a signal AI engines extract.
Add AggregateRating to your LocalBusiness schema. This makes your review score machine-readable. When an AI engine asks "how many stars does X have?", the schema provides the answer directly — citation probability increases when the AI has a machine-verified fact rather than having to infer from text.
Create content that answers local questions directly. AI engines cite local businesses most readily when the business's own website answers the question the user is asking — not just when the business exists in a directory.
Ranked by impact on AI local citation probability. Do these in order.
AEOfix audits NAP consistency across 40+ directories, tests your business entity across all 4 AI engines, and delivers a prioritized local AEO fix list. See exactly where you're invisible and what to do about it.