Local GEO: how AI assistants choose the "best" local business
AI assistants build local recommendations differently from map rankings. We set out what Google, ChatGPT, Apple and Bing document about local data and which signals a business can manage.
Consider a hypothetical request from a parent: "Which pediatric dentist near Kadıköy is good with anxious children and open on Saturdays?" A generative assistant tends to answer such a request by naming a few practices, each with a sentence explaining why it fits, rather than by returning a long list of map pins. That sentence is where local competition is increasingly decided, and it is the subject of local GEO: the practice of making a business's location, services, attributes and reputation legible to generative assistants, so that an assistant can select the business and justify the choice in a conversational recommendation rather than merely list it in a map pack.
Local GEO does not replace the work described in our guide to local SEO and "near me" searches; it changes the question that work must answer. A map pack asks which nearby profiles are most relevant and prominent, whereas an assistant asks which businesses it can describe confidently enough to recommend for a specific need. Below we separate what each platform documents about its local data from what remains undisclosed, then turn the manageable signals into a decision table.
What is local GEO, and how does it differ from local SEO?
Classic local search is a ranking problem: Google states that local results are mainly based on relevance, distance and prominence (its help page now also uses the word "popularity"), the last reflecting how well known a business is, including how many websites link to it and how many reviews it has. A generative answer adds a step after retrieval, compressing the candidates into a short list and writing a reason for each. The set of winners shrinks, and the criterion for entry shifts from being findable to being explainable.
Two measurements illustrate the gap, though neither is a universal constant. SOCi, a local marketing vendor, reported in its 2026 Local Visibility Index, which covered more than 350,000 locations of 2,751 multi-location brands, that ChatGPT recommended 1.2 percent of brand locations and Gemini 11 percent, against an average 35.9 percent appearance rate in Google's local 3-pack; it used one standardized prompt per location, asked for ten businesses and counted only the first five. Because the sample consists of chain locations, and SOCi itself reports that local small businesses are recommended more often, the figures describe multi-location brands rather than independent firms. A 2025 arXiv preprint by Chen, Wang, Chen and Koudas found low overlap between the domains Google returned and those a web-enabled AI engine cited for local queries: 20.6 percent for home cleaning, 2.5 percent for auto repair and only 0.1 percent for IT support. Paid formats such as Local Services Ads are a separate channel, and Google states there is no way to pay for a better local ranking.
Where do AI assistants get local business data?
The documentation differs by platform and is often silent; the summary below is limited to what each company publishes, and where a mechanism is not described it is marked as not publicly documented.
Google says AI Mode can draw on the Knowledge Graph and "info about the real world," and that AI Mode and AI Overviews may use query fan-out, running several related searches across data sources. Its guide to generative AI features in Search, last updated in July 2026, states that Business Profiles and Merchant Center feeds can help products and services appear in AI responses. Gemini features in Maps, launched first in the United States in 2024, are grounded in data about 250 million places and community insights, including review summaries and answers such as whether a place has outdoor seating. How places are ordered is not documented.
ChatGPT
OpenAI explains that ChatGPT may infer approximate location from the IP address, that device location sharing is optional and off by default, and that mobile results may include a map. It sometimes partners with other search providers and may share location with trusted third parties for nearby business listings; restaurant availability may come from OpenTable, Resy or Yelp. The help page does not name the provider behind business listings, map pins or ratings. OpenAI does state that placement is not guaranteed and that sites must allow OAI-SearchBot to be eligible.
Apple
Apple Business Connect, launched in January 2023, lets a business claim its place card, whose information reaches Apple Maps, Messages, Wallet, Siri and other apps; a card carries exactly one primary category and up to four optional ones. How Siri chooses among nearby businesses is not publicly documented, so the principles in our article on voice search and AI assistants remain the safest guide.
Microsoft
Bing Places for Business, relaunched in October 2025, manages listings shown in Bing search and Bing Maps; "deeper integrations with Bing Maps and Copilot" are announced as a future plan. How Copilot selects local businesses is not publicly documented.
Why does the conversational query change the rules?
People ask assistants longer questions loaded with constraints. In May 2026 Google reported that the average AI Mode search in the United States was about three times as long as a traditional query, and that searches beginning with "where should I" were growing. "Dentist Kadıköy" becomes a sentence carrying an audience, a need and a time window, and an assistant can satisfy only the constraints it finds stated in sources it trusts.
Attribute-rich descriptions therefore matter more than keyword repetition. Google Business Profile supports attributes such as outdoor seating, Wi-Fi or a wheelchair-accessible entrance, some populated from customer input. Chen et al., writing about product recommendations generally, argue that content must supply "justification attributes", reasons a model can extract easily, and that the brand offering the most easily synthesized justification wins the recommendation; the argument transfers naturally to local businesses, although the paper does not test it on them. Collecting customers' real wording, with the methods in our article on prompt research, shows which attributes your profile and site must state.
An assistant recommends a local business only when it can find, in sources it trusts, a stated reason that matches the user's need; local GEO is the discipline of making that reason explicit, consistent and verifiable.
Is your business described the same way everywhere?
Because Google merges crawled pages, licensed data and user edits, every inconsistent directory entry is a competing claim about the same entity, and an assistant that must name one business confidently has little reason to resolve the conflict in your favor. Google requires the business name to match the real-world name used on the storefront, prohibits adding unnecessary information to it, and allows one profile per business. Setup is covered in our guide to creating a Google Business Profile, and the entity logic behind consistency in our article on the knowledge graph and your brand entity.
Categories and hours need the same discipline. Google advises as few categories as possible to describe the core business, and Apple asks for exactly one primary category. Hours should include holiday hours, because an assistant answering "open on Saturday" repeats your data to someone about to act on it.
What role do reviews play, and where are the policy limits?
Google says more reviews and positive ratings can help local ranking; it does not say how recency is weighed, so freshness is a practical consideration rather than a documented factor. In generative answers, review text gains a second role, because summaries and attribute answers draw on what customers wrote: a practice repeatedly called "patient with nervous children" holds a reason a star rating cannot supply. SOCi found that locations recommended by ChatGPT averaged 4.3 stars, a correlation rather than proof of cause.
The limits are explicit. Google's Maps policy prohibits reviews paid for directly or in kind, content posted because of a business's incentive, and reviews written under a conflict of interest; it also forbids discouraging negative reviews or soliciting positive ones selectively, which rules out review gating, and it says merchants should not ask for specific content to be included in a review. The descriptive reasons an assistant can reuse must therefore come from customers' own words: ask every customer at a natural moment, without suggesting what to write, and reply in substance.
Why do directories and local press matter more in AI answers?
Generative engines cite pages, and for local questions many are listings. Yext, a listings-management company, analysed 6.8 million citations that ChatGPT, Gemini and Perplexity produced for location-specific queries in July and August 2025 in four industries, and reported that first-party websites supplied 44 percent and listings 42 percent, with reviews and social content at 8 percent and forums near 2 percent. In the Chen et al. Toronto experiment, only a handful of domains, notably large review aggregators, appeared in all four engines' answers. Neither study isolates causes, and Yext sells the listings management it measures, so the figures indicate a direction rather than a rule. That direction still argues for keeping sector directories and chamber listings accurate and for earning genuine local press coverage, because these are among the third-party pages an assistant can draw on when it explains what a business is known for.
How should a service-area business state where it works?
A plumber or mobile physiotherapist has no storefront to anchor proximity, so a service-area statement does that work. Google asks such businesses to hide their address and says the service area should generally not exceed about two hours of driving time. On the website, the equivalent is one crawlable list of districts or cities served, worded like the profile. Google's spam policies cite multiple pages targeted at specific cities that funnel users to one page as doorway abuse, so a page per district is defensible only with genuinely distinct content, such as local projects or staff based there.
Does LocalBusiness structured data help AI assistants?
Google's LocalBusiness documentation requires name and address, recommends properties such as geo, openingHoursSpecification, telephone and url, and advises the most specific subtype. Schema.org defines areaServed as the geographic area where a service is provided, the natural home for a service-area statement; implementation is covered in our article on schema markup. Expectations should stay realistic: Google says no special markup is needed for AI Overviews or AI Mode and that structured data should match the visible text, and reviews a business controls about itself do not earn star snippets. Markup is a consistency layer, not a ranking lever.
The local GEO decision table
| Signal | Where it lives | What the business can do | How to check it |
|---|---|---|---|
| Name, address, phone | Google, Apple and Bing profiles, website, directories | Fix one canonical spelling; merge duplicates | Search name and phone on each platform; log mismatches |
| Primary category | Google profile, Apple place card | Choose the most specific category for the core business | Compare with profiles recommended instead of you |
| Hours | All profiles, contact page | Update holiday hours everywhere before the date | Ask an assistant "open on [day]" the week before |
| Attributes and services | Profile attributes, service pages | Complete applicable attributes; describe audience and constraints | Run constraint prompts; check the stated reason |
| Reviews | Google Maps, review platforms | Ask every customer, no incentives or gating; reply | Monthly count and recurring themes |
| Directories and press | Sector directories, chambers, local news | Correct listings; earn coverage with real news | Note third-party domains assistants cite |
| Service area | Website, profile service area | Publish one clear list; avoid near-duplicate city pages | Confirm site and profile match |
| LocalBusiness markup | Website code | Mark up name, address, geo, hours, areaServed | Validate after each site change |
How can you check local AI visibility, and what are the limits?
Start manually: write ten to twenty requests in customers' own form, run each several times, and record whether you are named and with which reason. Location context matters, since OpenAI notes that a VPN or network location can change ChatGPT's inferred location. Read the results against the shift described in our analysis of AI Overviews and zero-click search and our pillar guide to generative engine optimization; the category-level version of the problem is examined in getting into AI's "top 5".
Rocketly GEO Suite tracks prompts by country market (Türkiye, the United States, Russia, the United Kingdom, Germany) and language (Turkish, English, Russian); it does not measure city-level, local-pack or Maps results. Its local contribution is preparatory: approved brand facts can record location and service region with an evidence URL (a reference record, not a check of whether answers are true), and the AI Readiness audit includes a Google Business Profile consistency criterion. To see how often answers name and cite your brand at country level, create a Rocketly account and add GEO Suite: Google AI Overview is measured weekly as standard, ChatGPT and Perplexity are in controlled rollout, and a run that was not measured is never counted as zero.
Frequently asked questions
Does local GEO replace local SEO?
No. Profile completeness, reviews and proximity remain the foundation of map results, and the same signals feed generative answers. Local GEO adds one requirement: the reasons for choosing you must be stated clearly and consistently enough for an assistant to repeat them.
Can a business pay to be recommended for local queries?
Google states there is no way to pay for a better local ranking, and OpenAI states that placement in ChatGPT search is not guaranteed. Paid formats exist as separate, labeled channels, and neither company describes a way to pay for a place inside the generated recommendation itself.
Should I create a page for every district I serve?
Only where each page carries genuinely distinct content, because Google's spam policies list pages targeted at specific cities that funnel visitors to one page as doorway abuse. One clear service-area statement, consistent with your profile and marked up with areaServed, is usually the stronger foundation.