Local SEO and AI Search: How Local Businesses Get Cited by AI Assistants
AI assistants are increasingly used for local discovery queries. Here's how local businesses can optimize for AI citation alongside traditional local SEO — the signals that overlap and the ones that don't.
How local AI queries work
Local queries ("dentist near me", "best Italian restaurant in Austin") have historically been dominated by Google Maps and the local pack. AI assistants are changing this in a specific way: they're handling pre-visit research and comparison queries, not necessarily the final "navigation intent" queries.
A user might ask Perplexity "what should I look for when choosing a dentist in Austin" or ChatGPT "what are the best Italian neighborhoods in Austin for restaurants" — these are AI-first research queries where your business content, not your map pin, determines whether you're cited.
Where local SEO and AEO overlap
Shared signals (do both)
- +LocalBusiness Schema on your website
- +NAP consistency (Name, Address, Phone)
- +Positive review volume and recency
- +Clear service area identification
- +Website load speed and mobile UX
AEO-specific additions
- +FAQPage Schema on key service pages
- +Educational content about your category
- +Author attribution on blog content
- +Question-phrased H2s on service pages
- +HowTo Schema for process-oriented content
Local Schema markup: the complete stack
Local businesses need a more specific Schema stack than national brands. Here's what to implement on each page type:
Homepage
Critical- +LocalBusiness (with specific subtype: Dentist, Restaurant, etc.)
- +Organization (with sameAs links)
- +sameAs links to Google Business Profile, Yelp, Facebook
Service pages
High- +Service Schema
- +FAQPage Schema for common service questions
- +HowTo Schema for procedural services (e.g., 'How our process works')
Blog / educational content
High- +Article Schema with named author
- +FAQPage Schema for Q&A sections
- +dateModified updates
Location/About page
Medium- +LocalBusiness with GeoCoordinates
- +OpeningHoursSpecification
- +AggregateRating from reviews
Google Business Profile and AI citations
Your Google Business Profile (GBP) is a data source that AI systems — especially Google AI Overviews — use to answer local queries. A complete, active GBP strengthens your AI citation probability in several ways:
- ▸Complete business description with service keywords used in AI answers about your category
- ▸Q&A section in GBP — Google's AI systems use these directly in some answer formats
- ▸Regular GBP posts — freshness signal that correlates with AI citation recency
- ▸GBP URL listed in your website's Organization Schema sameAs array
The GBP Q&A opportunity
Content strategy for local AI citation
The biggest gap for most local businesses is educational content. National brands have content teams producing guides on their category. Local businesses rarely do — creating a significant citation opportunity.
Map your category's pre-research queries
Create one comprehensive guide per question
Add FAQPage Schema to every guide
Link service pages to educational content
How reviews influence local AI citations
AI systems treating local queries often aggregate review data. Google's AI Overviews for "best [business type] in [city]" queries regularly cite aggregate ratings and pull specific review language. Managing your review presence is therefore an AEO action, not just a reputation action:
- ▸Volume: AI systems use aggregate rating data — more reviews (even if not 5-star) provide more data for accurate citation
- ▸Recency: AI systems prefer recent reviews — a 4.8 rating with 200 recent reviews outperforms a 4.9 with 200 old reviews
- ▸Review content: Reviews that mention specific services, qualities, or problems are directly extracted in some AI answers
- ▸AggregateRating Schema on your website that references your GBP/Yelp ratings reinforces this data
Multi-location considerations
For businesses with multiple locations, the challenge is balancing unique local content against brand consistency. Each location page should have:
- ▸Its own LocalBusiness Schema with location-specific NAP data
- ▸Unique content (not just duplicated with city name swapped) — AI systems penalize near-duplicate pages
- ▸Local context: neighborhood descriptions, nearby landmarks, local service variations
- ▸Links to the location-specific Google Business Profile in sameAs