What schema markup is most important for local AI search?

For local AI search, the most important schema types are LocalBusiness (with complete address, phone, areaServed, and openingHours), Service (for each service offered), FAQPage (on service and content pages), and GeoCoordinates (for precise location). PostalAddress with correct formatting and consistent use of the same address format across all pages is also critical.

How do I know if I am appearing in AI search for local queries?

Test your AI search visibility by running your target queries in ChatGPT, Perplexity, and Google (for AI Overviews). Record whether your business is mentioned by name, cited as a source, or included in any business list. Also check Google Search Console for AI Overview impressions. This manual audit gives you a baseline citation rate you can track over time.

Local SEO and AI Search: How AI Handles Local Queries Differently to Google Maps

Q: What does 'near me' mean in AI search?

'Near me' in AI search context depends on which system is handling the query. Perplexity and Google AIO use the searcher's location data to localise results, similar to Google Maps. ChatGPT in standard mode has no location data unless the user provides it explicitly. For AI search, businesses are better served by explicitly naming their service areas in content and schema rather than relying on proximity detection.

Q: Do I still need traditional local SEO if I optimise for AI search?

Yes. Traditional local SEO (Google Maps pack, citations, review signals) remains the foundation. AI search engines build on top of these signals, not instead of them. A business with strong Google Maps visibility and strong AI content optimisation captures both the Maps pack audience and the AI answer audience. The two are complementary.

Q: What are the 3 types of local AI visibility?

The three types of local AI visibility are: (1) Maps pack citations - appearing in the local business results that may be shown alongside or within AI answers; (2) AI Overview citations - being referenced in Google's AI-generated summary that appears above the Maps pack and organic results; (3) Chatbot citations - being mentioned by name in ChatGPT or Perplexity answers to local queries. Each type has different optimisation requirements.

Q: How important is Google Business Profile for AI search?

Google Business Profile (GBP) remains critical for local AI visibility. Google AI Overviews pull business data directly from GBP. Perplexity uses GBP data for entity verification. ChatGPT's training data includes GBP information from before its knowledge cutoff. A complete, accurate, regularly-updated GBP is the single most important local AI visibility signal.

The core change. When someone searches “best movers near me” on Google, they see a Maps pack. When they ask ChatGPT or Perplexity the same question, they get a synthesised answer that may recommend specific businesses, explain what to look for, give price ranges, and compare options. These are fundamentally different surfaces, and most local businesses are only visible on one of them.

We run AI visibility audits for local businesses. The pattern we see constantly: strong Google Maps performance, near-zero AI chatbot visibility. The skills that got you into the Maps pack do not automatically carry you into AI answer citations. This guide explains the difference and what to do about it.

Why AI search handles local queries differently

Google Maps is a directory. It stores structured data about local businesses - location, category, hours, reviews, photos - and retrieves the most relevant listings based on proximity, relevance, and authority. The searcher’s intent is implicitly “show me a list of nearby options”. The system delivers that list.

AI search engines handle local queries differently because their architecture is different. They are not retrieving from a structured business directory. They are synthesising an answer from a combination of indexed web content, real-time search results, and (for systems like ChatGPT without browsing) training data about the world.

When someone asks Perplexity “who are the best movers in Austin”, Perplexity does not pull from a business database. It reads web pages that discuss movers in Austin - local review aggregators, directory listings, comparison articles, individual mover websites - and synthesises an answer. The businesses that appear in that answer are the ones whose content is most prominently represented in those sources.

This distinction has major practical consequences:

Google Maps rewards:

Proximity (how close you are to the searcher)
Review volume and rating
GBP completeness (categories, attributes, photos, hours)
Local citation consistency
Engagement signals (calls, direction requests)

AI search rewards:

Content authority (do your pages answer the questions being asked)
Entity consistency (are you clearly identifiable as a legitimate business across the web)
Structured data (does your site have schema markup that AI systems can parse)
Third-party mentions (are you referenced on other authoritative sites)
Review quality and specificity (not just volume, but what reviews say)

The overlap is meaningful - entity consistency, review signals, and GBP data help both. But the divergence is large enough that a business can be in the top 3 of the Maps pack and invisible in AI search, or vice versa.

What “near me” means in AI search

“Near me” queries are the bread and butter of local search. “Plumber near me”, “moving companies near me”, “dentist near me” - these drive enormous volumes of local search intent.

In Google Maps and traditional Google search, “near me” triggers geolocation. Google uses your device location (if permitted) or your IP address to determine your location and show nearby businesses. The results are inherently local.

In AI search, “near me” is handled differently by each system:

Perplexity

Perplexity uses location signals when available. If you are searching on a mobile device with location permissions enabled, Perplexity will use that location data to localise its answer. It may explicitly acknowledge this (“Based on your location in Austin…”). It also uses Bing’s localised search index, which returns geographically relevant results.

For businesses: ensure your Bing Webmaster Tools profile is complete and your Bing Places listing is accurate. Perplexity’s location-aware answers pull from Bing-indexed content.

Google AI Overviews

Google AI Overviews use the same location signals as Google Search. If the query is location-enabled, the AIO will incorporate local business data from Google’s local index, including GBP information. A business that is well-established in Google’s local index (strong GBP, consistent citations, good review signals) has a better chance of appearing in local AIOs.

For businesses: treat Google AIO visibility as an extension of your Google Maps optimisation, with additional emphasis on content structure and schema.

ChatGPT

Standard ChatGPT (non-browsing mode) does not have location awareness. It does not know where the searcher is. When someone asks “best movers near me”, ChatGPT in standard mode may ask for clarification, make a general recommendation, or default to mentioning well-known national brands. It cannot localise without the user providing location context.

ChatGPT with browsing enabled can use Bing’s localised results, which provides some location awareness, but it is less reliable than Google or Perplexity for hyper-local queries.

The implication for local businesses: Do not rely on “near me” proximity detection in AI search. Instead, explicitly name your service areas in your content and schema. A page that says “We serve Dallas, Plano, Frisco, McKinney, and Allen within a 30-mile radius” gives AI systems the geographic information they need to include you in relevant local answers - regardless of whether the searcher’s location is being detected.

The 3 types of local AI visibility

Local AI visibility is not a single thing. There are three distinct surfaces where a local business can appear in AI-assisted search, and each has different optimisation requirements.

Type 1: Maps pack citations (AI-adjacent)

The Google Maps pack (the 3-business block with a map that appears for local queries) sits alongside or within AI-generated answers. Google AIO often appears above the Maps pack, with the Maps pack still visible below it. Some AIOs reference Maps pack businesses directly.

The Maps pack is not AI-generated - it is Google’s traditional local ranking. But it appears in the same visual space as AI content, and AI Overviews may pull from or reference Maps pack businesses.

How to check Maps pack visibility:

Search your target queries on Google from a browser in your service area (or a VPN location matching your service area)
Note your position in the Maps pack (or your absence from it)
Use Google Search Console local search appearance data for broader coverage

What drives Maps pack visibility:

GBP completeness: all categories, attributes, services, and photos filled in
Review signals: volume (100+ is competitive in most niches), recency (last 90 days), and rating (4.5+)
Local citation consistency: consistent NAP across directories
On-page local signals: city and service area named on website
Proximity: a signal you cannot change, but can compensate for with strong other signals

Type 2: AI Overview citations

Google AI Overviews appear above the Maps pack on queries where Google’s system determines a synthesised answer would be useful. For local queries, this often means questions about cost, process, comparison, or advice - not just “show me nearby options”.

An AI Overview citation for a local business looks like: the AIO mentions your business name, describes what you do, or cites your webpage as a source within the synthesised answer.

How to check AI Overview visibility:

Run test queries in Google (incognito browser) and note which queries trigger AIOs
For queries with AIOs, check whether your business or website is cited
In Google Search Console, check Performance > Search type > Web > and filter for “AI Overview” appearance type

What drives AI Overview citations:

Organic ranking (pages in top 10-20 are most likely to be cited)
Content structure: direct-answer opening paragraphs, clear H2/H3 structure
Schema markup: FAQPage, HowTo, LocalBusiness, Service
E-E-A-T signals: named author or professional, specific experience statements, credentials
Content freshness: recently updated pages are preferred for time-sensitive queries

Type 3: Chatbot citations

ChatGPT, Perplexity, and Claude can mention specific local businesses by name when answering local queries. This is the highest-value AI search surface because it is a direct recommendation from an AI system that many users now trust as much as or more than a Google search result.

Getting cited in chatbot answers requires the combination of entity authority (the AI system “knows” your business exists and is trustworthy) and content authority (your pages contain information the AI system can use to form an answer).

How to check chatbot citation visibility:

Run 20 test queries in ChatGPT (browsing mode) and Perplexity for your target services and locations
Note whether your business name or website appears in any answers
For queries where competitors are named but you are not, note which competitors appear and examine their online presence

What drives chatbot citations:

Entity authority: GBP, major directories, local press, professional associations
Review volume and quality: specific, detailed reviews that describe real experiences
Content directness: answer capsules and FAQ sections on key pages
Structured data: FAQPage and LocalBusiness schema
Geographic specificity: explicit service area declarations in content and schema

Priority order for a local business

Given limited time and budget, which of the three types of local AI visibility should a local business prioritise?

Priority 1: Maps pack (foundation)

The Maps pack is still where the majority of local commercial search traffic goes in 2026. A business that is not in the Maps pack for its core queries is missing the most significant volume. Fix this first.

The investment: Google Business Profile optimisation, review generation, local citation building. These are also foundational to types 2 and 3.

Priority 2: AI Overviews (extension)

AI Overviews appear above the Maps pack and are becoming a significant share of first-page real estate for local queries. Optimising for AIOs builds on your Maps work by adding content and schema layers.

The investment: content rewrites (answer capsules), FAQPage schema, HowTo schema for process pages. This work also helps with Perplexity citations, so it serves multiple purposes.

Priority 3: Chatbot citations (compounding authority)

Chatbot citations drive less immediate traffic volume but build the highest form of local AI authority. When ChatGPT or Perplexity recommends your business by name in a conversational answer, the conversion rate is high because the recommendation comes with apparent AI endorsement.

The investment: third-party mention building (press, associations, partnerships), review quality improvement, entity consistency across platforms. This is slower to build but compounds over time.

The right order for most local businesses: get solid on Maps first (2-4 months of work if you are starting from scratch), then layer in AI Overview optimisation (2-4 weeks of content and schema work), then build toward chatbot authority as an ongoing program.

How to check each type of visibility

Here is the manual audit process for each type. Total time: 3-4 hours for a thorough baseline.

Maps pack audit (45 minutes)

Search your top 10 target queries in Google from within your service area
Record your Maps pack position (1-3 if present, or “not showing”)
Check Google Search Console > Performance > Local Pack appearances
Run a NAP consistency check: search your business name and verify the name, address, and phone number match exactly across Google, Yelp, BBB, and any 10 other major directories
Count your review total and note your average rating and the date of your most recent review

What you are measuring: Maps pack position, NAP consistency score, review health

AI Overview audit (60 minutes)

Search 15-20 queries in Google (incognito) that include informational and local intent: “how much does [service] cost [city]”, “best [service] [city]”, “what to look for in [service provider] [city]”
For each query that triggers an AIO, record whether your website is cited as a source
For queries with AIOs where you are not cited, note which sources are cited and visit those pages
Check Google Search Console for AI Overview appearance data

What you are measuring: AIO citation rate, gap analysis vs cited competitors

Chatbot audit (90 minutes)

Build a list of 20 queries your ideal client would ask in a chatbot
Run each query in ChatGPT (browsing mode) and Perplexity separately
Record: (a) does your business appear by name, (b) is your website cited, (c) which businesses are mentioned instead
Calculate separate ChatGPT and Perplexity citation rates
For queries where competitors are cited but you are not, visit those competitor pages and note what they do differently (answer capsule, FAQ section, schema, specific data points)

What you are measuring: ChatGPT citation rate, Perplexity citation rate, competitor gap analysis

Schema markup priority list for local AI search

If you can only add schema to 5 pages this month, this is the priority order:

Page 1: Homepage

LocalBusiness (complete with address, phone, geo coordinates, areaServed listing every city you serve, openingHoursSpecification)
Organization (name, logo, contactPoint, sameAs links to GBP, Yelp, LinkedIn)

Page 2-4: Top service pages

Service (serviceType, provider, areaServed, description)
FAQPage (5+ Q&A pairs for common questions about that service)
HowTo (if the page explains a process)

Page 5: About or team page

Person (for each named professional: name, jobTitle, affiliation, credentials)
LocalBusiness (secondary block tying the team to the business)

All pages:

BreadcrumbList (schema and HTML breadcrumbs)
WebPage (basic type declaration)

The LocalBusiness block on the homepage is the single most important schema element for local AI visibility. Many of the businesses we audit either do not have it at all or have it with incomplete areaServed fields that name only the headquarters city and miss every suburb and satellite city the business actually serves.

Local SEO and AI search: what is the same, what is different

To close, a direct comparison of what carries across from traditional local SEO and what is new for AI search:

What carries across:

Google Business Profile completeness - critical for both
Review volume and rating - important for both
NAP consistency across directories - important for both
Website speed and technical health - foundational for both
On-page mention of city and service area - helpful for both

What is new for AI search:

Answer capsule opening paragraphs (replaces generic descriptions)
FAQPage and HowTo schema (rarely done for traditional local SEO)
Explicit service area declarations in schema (areaServed in LocalBusiness)
Content freshness with visible update dates
Third-party mention quality (not just link quantity)
E-E-A-T signals on service pages (named professionals, specific outcome data)

The businesses that will dominate local search over the next 24 months are the ones doing both. They have strong Maps pack presence from traditional local SEO, and they are layering in the content and schema work that earns AI search citations. The businesses doing only traditional local SEO will maintain their Maps pack positions but become invisible in the AI layer that is growing on top of it.

FAQ

How does AI search handle local queries differently to Google Maps?

Google Maps ranks local businesses primarily on proximity, relevance, and prominence. AI search engines synthesise answers that may include business recommendations, cost information, and comparisons - not just a ranked list of nearby businesses. AI search rewards content authority, structured data, and entity consistency in addition to traditional Maps signals.

What does “near me” mean in AI search?

It depends on the system. Perplexity and Google AIO use the searcher’s location data. ChatGPT in standard mode has no location awareness. For AI search, explicitly naming service areas in content and schema is more reliable than relying on proximity detection.

Do I still need traditional local SEO if I optimise for AI search?

Yes. Traditional local SEO (Maps pack, citations, reviews) is the foundation. AI search builds on top of it, not instead of it. The two are complementary.

What are the 3 types of local AI visibility?

Maps pack citations (traditional local ranking that sits alongside AI content), AI Overview citations (Google’s AI-generated summaries that may reference your business), and chatbot citations (ChatGPT or Perplexity mentioning your business by name in conversational answers).

How important is Google Business Profile for AI search?

Very important. Google AI Overviews pull data directly from GBP. Perplexity uses GBP for entity verification. ChatGPT’s training data includes GBP information. A complete, accurate, regularly-updated GBP is the most important local AI visibility signal.

Published by Vespio. We deliver local SEO and AI ranking for service businesses across the US and Canada. Our AI Visibility Snapshot tells you your current citation rate across ChatGPT, Perplexity, and Google AI Overviews for your target queries.