Local SEO AI Search: How Local Businesses Win on Google and AI Engines

Local SEO has always been about showing up where your customers are looking. For the past decade, that meant Google Maps and the local pack. In 2025, it means something broader: AI engines like ChatGPT, Perplexity, and Google’s own AI Overviews are now answering “best plumber near me” and “dentist in [suburb]” queries directly, without sending users to a map. The businesses getting named in those answers are not always the ones ranking highest in traditional local search.

The good news is that the foundations overlap heavily. Strong Google Business Profile signals, consistent citations, and a well-structured website still drive both traditional local rankings and AI visibility. But AI engines pull from additional sources that traditional local SEO largely ignores, including industry-specific directories, data aggregators, and review platforms beyond Google. Getting both right requires understanding where they diverge.

This guide covers the practical steps for local businesses: what Google still controls, where AI engines source their local recommendations, and how to build a presence that appears across both surfaces.

How Google’s local ranking algorithm works

Google ranks local businesses using three factors: relevance (how well your profile matches the query), distance (proximity to the searcher), and prominence (how well-known your business is across the web). According to Google’s own documentation, there is no way to pay for a better local ranking — it is entirely algorithmic.

Relevance comes from your Google Business Profile category, attributes, and the keywords used in your business description and service listings. Distance is calculated based on the user’s location at query time, which means a business 2km away will often beat one 10km away even with better reviews. Prominence draws on website authority, the volume of mentions across the web, and your review profile — specifically the number of reviews and their average rating.

The practical implication: filling out your GBP completely (hours, services, photos, Q&A) and earning genuine reviews are the highest-leverage activities for traditional local rankings.

What changes when AI engines answer local queries

AI engines construct local recommendations differently from Google Maps. Research by BrightLocal across 20 searches in 10 industries found that all major LLMs — ChatGPT, Gemini, and Perplexity — use directories and citations as their primary source of business information, not just Google Business Profile data.

The sourcing breaks down by platform. Perplexity consistently uses Yelp across all industries tested. ChatGPT used business websites as a source in 58% of searches in BrightLocal’s study, and between 60% and 70% of local results on ChatGPT come from Foursquare’s city guide listings — particularly for smaller or niche businesses. Yelp appeared as a source in 33% of overall LLM searches. Google’s own AI surfaces draw heavily from GBP data.

The critical shift: a business with a strong GBP but thin directory presence may dominate the local pack yet be invisible in ChatGPT results. Conversely, a business that has invested in Yelp, industry-specific directories, and data aggregators will have an advantage in AI-generated recommendations that traditional local SEO metrics won’t show.

The directory and citation layer that AI depends on

For local businesses, local citations are the connective tissue between your business data and AI engines. A citation is any online mention of your business name, address, and phone number (NAP). Inconsistent NAP data — different phone numbers on different directories, an old address still listed on a third-party site — creates conflicting signals that both Google and AI engines struggle to resolve.

The directories that matter most for AI visibility are:

General platforms: Google Business Profile, Yelp, Facebook, Apple Maps, Foursquare. These are the sources AI engines pull from most frequently, and they cross-feed each other through data aggregator networks.

Data aggregators: Services like Foursquare, Data Axle, and Neustar distribute business information to hundreds of downstream platforms, including voice assistants and AI systems. Getting your data right in these aggregators creates a multiplier effect.

Industry-specific directories: BrightLocal’s research found that AI engines favour vertical directories for professional services queries. Dental searches pulled from Toprateddentist.com, legal queries used Superlawyers.com and Findlaw.com. A plumber or electrician appearing in trade-specific directories is more likely to be named in relevant AI answers.

NAP consistency is non-negotiable. If ChatGPT is pulling your address from Foursquare and it says “Suite 3” while your website says “Unit 3,” the model either reconciles the discrepancy (dropping confidence in your listing) or cites you incorrectly. Run a citation audit before investing in new directory submissions.

Reviews as AI ranking signals

Reviews now influence two distinct surfaces: traditional local pack rankings and AI-generated summaries. According to BrightLocal’s 2026 Local Consumer Review Survey, 82% of consumers read AI-generated review summaries, and 45% now use ChatGPT or AI tools when researching local businesses — up from just 6% in 2025.

AI engines synthesise review sentiment to form their recommendations. A business with 200 reviews averaging 4.7 stars sends a much stronger signal than one with 20 reviews at 4.2, even if both businesses appear in the local pack. The content of reviews also matters — customers who mention specific services, staff names, or location details in reviews create richer data for AI to summarise.

For Google’s traditional local rankings, review quantity, rating, and recency all factor into prominence. The 2026 BrightLocal survey found that 74% of consumers prioritise reviews posted within the last three months, and 31% will only use businesses with 4.5 or higher star ratings. These consumer preferences are directionally aligned with what the algorithms reward.

Responding to Google reviews also matters. It signals active management of your profile, which feeds back into the prominence signal.

Local schema markup for AI visibility

Local schema markup tells both Google and AI crawlers exactly what your business is, where it operates, and when it is open. The LocalBusiness type on schema.org is the relevant vocabulary, and Google’s structured data documentation lists it as high-impact for local search eligibility.

The properties that do the most work:

name, address, and telephone are the minimum viable set. These should exactly match your GBP listing.
geo (latitude and longitude) strengthens the distance signal.
openingHoursSpecification allows precise hours including seasonal variations, which AI engines use to answer “is [business] open now?” queries.
aggregateRating surfaces your review score to AI crawlers that may not be reading your review platform directly.
areaServed is valuable for service-area businesses that do not operate from a single physical address.

Implement the schema in JSON-LD format within a <script> tag on your location page, validate it through Google’s Rich Results Test, then request reindexing via Search Console. This does not guarantee AI citation, but it removes a barrier: AI systems that encounter ambiguous business information are more likely to skip a listing than to guess.

Google AI Overviews and the local pack

Google AI Overviews sometimes appear above the local pack for query types like “best [service] in [city].” When they do, the Overview pulls from sources Google’s models consider authoritative — typically high-domain-authority review sites, local guides, and GBP data.

To give your business the best chance of appearing in or near an AI Overview for local queries, the factors that work for traditional local rankings carry over: a complete GBP, strong review volume, structured data, and a website that clearly describes your services and location. Where AI Overviews diverge from the local pack is in their use of editorial content. A local guide article naming “the best [service] in [city]” can get cited in an AI Overview without the businesses in it having any GBP signals at all.

This creates an opportunity. Getting your business mentioned in local editorial content — city guides, neighbourhood blogs, local news sites — directly feeds AI Overview sourcing. Local link building is no longer just a domain authority play; it is an AI citation strategy.

How Perplexity and ChatGPT handle local queries differently

Understanding where each AI engine sources local recommendations helps you prioritise. Perplexity functions like a real-time search engine and will crawl live sources including your website, Yelp, and industry directories. Because Perplexity uses web retrieval, a well-optimised website with clear NAP data and service pages is cited directly. Keeping your site fast and indexable matters here.

ChatGPT (in its default mode) relies more on its training data, which skews toward high-distribution directories. Foursquare’s data coverage of 60-70% of local ChatGPT results reflects how thoroughly Foursquare has seeded the training corpus. For ChatGPT, getting into data aggregators is the higher-leverage activity.

Gemini draws from the broader Google ecosystem — GBP data, Google Maps reviews, and web search results. For businesses already investing in traditional local SEO, Gemini is the AI engine that rewards existing work most directly.

The practical implication: you cannot optimise for one platform and win everywhere. A diversified local citation strategy covering GBP, major directories, data aggregators, and a structured website serves all three surfaces.

Building for dual-surface visibility: a prioritised checklist

Local businesses that want to rank in traditional search AND appear in AI answers should work through these in order:

Complete your Google Business Profile — every field, correct categories, current hours, service listings, and fresh photos. This is foundational for Google Maps, AI Overviews, and Gemini.
Audit and fix NAP consistency — check your business name, address, and phone number across Yelp, Facebook, Apple Maps, Foursquare, and any industry directories. Inconsistencies suppress both local pack and AI citations.
Build core directory presence — submit or claim listings on Yelp, Apple Business Connect, Bing Places, Foursquare, and any industry-specific directories relevant to your sector.
Implement LocalBusiness schema on your location page with complete properties including geo coordinates, opening hours, and aggregate rating.
Generate reviews consistently — ask every customer. Volume and recency both matter. Respond to every review, positive and negative.
Earn local editorial mentions — write for local publications, participate in community events that get covered online, and get into local business roundup articles. These mentions feed Google AI Overviews directly.
Track your AI visibility — traditional rank tracking won’t show you whether ChatGPT or Perplexity are recommending your business. Use a tool like Fokal to monitor whether AI engines cite you for your target local queries.

The role of your website in local AI visibility

Your website is the most frequently cited source for local business information in ChatGPT searches (58% of the time, per BrightLocal). That percentage is not a coincidence — a website you control gives you the clearest, most structured presentation of your business information.

Practical website requirements for local AI visibility: a location page with complete NAP data, LocalBusiness schema, a service description that uses the language customers search with, a FAQ section covering common questions about your business (hours, parking, payment methods, service areas), and testimonials or review snippets that demonstrate social proof.

The FAQ section is particularly valuable. AI engines use FAQ content to answer conversational queries directly. A plumber whose website answers “do you offer emergency call-outs?” or “what suburbs do you service?” is more likely to be cited when a user asks those questions through Perplexity or ChatGPT than a competitor with only a homepage.

For a comprehensive view of all the signals involved, the local SEO hub covers each component in detail — from Google Business Profile optimisation to local landing pages and ranking factors.