How to Rank in ChatGPT Local Search: Get Cited for Local Queries in 2026
ChatGPT cites a specific local business in just 3% of relevant queries. Here is the five-step technical checklist that separates those businesses from the 97% that get skipped.
If you have searched for how to rank in ChatGPT for local queries, you have probably found advice that is either too vague ("have a good website") or borrowed from Google SEO playbooks that do not apply. This post is built from actual measurement data and covers the five technical moves that change whether AI systems name your business or skip it.
Across 140 measured local service prompts, ChatGPT cited a specific business in just 3% of relevant queries. Gemini came in at 5%, Perplexity at 6%, Claude at 7%. The baseline is low across every engine. That is not a reason to give up. It is a reason to understand what separates the 3% from the 97%.
The data came from our audit of 58,882 local businesses across service verticals and metro areas. The businesses that did get cited shared a common infrastructure. The ones that did not were almost universally missing one or more of the same five elements. Here is that infrastructure, step by step.
How to Rank in ChatGPT Local Search: Why Most Businesses Are Invisible
AI models do not browse the web the way a human would. They retrieve content from indexed sources, synthesize it, and generate an answer. For local business queries, the sources they draw from are:
- Bing's search index (for ChatGPT specifically)
- Review platforms that Bing indexes prominently: Yelp, Angi, BBB, Houzz
- Your website, if it is indexed and has clear, specific content
- Structured data (schema markup) on your pages
The core problem for most local businesses is not that they have a bad website. It is that the data across those sources is inconsistent, incomplete, or missing entirely. When a model tries to match a user's query to a specific business and the data is thin or contradictory, it hedges. It gives a general answer or names a competitor with cleaner data.
Our audit found that owner reachability, meaning whether a business had a working phone number and contact method in rendered HTML, was missing in 41% of businesses we measured. That alone is enough to suppress a citation. An AI model that cannot confidently say "call this number" will not name your business.
Moves 1 and 2: Schema That Resolves Your Entity
Move 1: LocalBusiness Schema with the Correct Subtype
Generic LocalBusiness schema is a start. Specific subtype schema is what actually resolves your entity for AI models.
Schema.org has more than 120 subtypes under LocalBusiness. A plumber should use PlumbingService. An HVAC contractor should use HVACBusiness. A dentist should use Dentist. These subtypes are how AI models understand what category of business you are without having to infer it from your page text.
What to include in the JSON-LD block:
{
"@context": "https://schema.org",
"@type": "PlumbingService",
"name": "Your Business Name",
"url": "https://yourdomain.com",
"telephone": "+15551234567",
"address": {
"@type": "PostalAddress",
"streetAddress": "123 Main St",
"addressLocality": "Your City",
"addressRegion": "CA",
"postalCode": "90210",
"addressCountry": "US"
},
"geo": {
"@type": "GeoCoordinates",
"latitude": 34.0522,
"longitude": -118.2437
},
"openingHoursSpecification": [...],
"priceRange": "$$",
"areaServed": ["Your City", "Neighboring City"]
}
Two fields that most implementations omit: geo coordinates and areaServed. Coordinates anchor your location precisely. areaServed explicitly tells AI systems which cities you serve, so you appear for queries from those areas even if your address is in a different ZIP code.
Place this JSON-LD in the <head> of your homepage and on every service page. If your service pages each have their own schema block with the specific service subtype, you give AI models multiple clean entry points into your entity.
Move 2: Person Schema with sameAs to Establish the Owner
This one is underused and measurably effective. When an identifiable person is linked to a business, AI models treat the business as a real, verifiable entity rather than an anonymous listing.
Add a Person schema block for the business owner on your About page:
{
"@context": "https://schema.org",
"@type": "Person",
"name": "Jane Smith",
"jobTitle": "Owner",
"worksFor": {
"@type": "PlumbingService",
"name": "Your Business Name"
},
"sameAs": [
"https://www.linkedin.com/in/janesmith",
"https://www.facebook.com/janesmith"
]
}
The sameAs property is the key. It links the Person entity to external profiles that AI models can cross-reference. LinkedIn and Facebook are the two highest-value links here because they are heavily indexed by Bing and trusted by AI models as non-spam entity references.
This move also directly affects what AI models say when a user asks "who runs [business name]" or "is [business name] a local company." Those queries are about trust and legitimacy, not just service matching. Businesses that can be traced to a real, named owner with verifiable profiles get cited in those contexts.
Move 3: FAQ Schema Targeting the Questions AI Systems Actually Answer
AI models are retrieval systems. When a user asks "what does [service] cost in [city]," the model retrieves documents that contain an answer to that question, then synthesizes a response. Your FAQ schema is what makes your page retrievable for those queries.
The most cited FAQ topics in our data, across service verticals:
| Query type | Example FAQ question |
|---|---|
| Price transparency | "How much does [service] cost in [city]?" |
| Emergency availability | "Do you offer same-day [service]?" |
| Credentials | "Are you licensed and insured in [state]?" |
| Service scope | "What areas do you serve?" |
| Process | "How long does [service] take?" |
Write the answers to these questions in plain, specific language. "Our service calls start at $89 for the first hour" is retrievable. "We offer competitive pricing" is not. The answer has to contain an actual answer.
FAQPage schema wraps these Q&A pairs in machine-readable format. Put FAQ schema on your service pages and on any blog post that contains Q&A content. Each FAQ block is a discrete retrieval target for AI systems responding to conversational queries.
Move 4: NAP Consistency Across Every Indexed Source
NAP stands for name, address, and phone number. Inconsistency across sources is one of the most common reasons a business gets skipped in AI citations.
Here is why it matters technically. When ChatGPT retrieves information about a local business, it is drawing from multiple indexed sources simultaneously: your website, Bing Places, Yelp, Angi, BBB, industry directories. If your phone number on Yelp is different from your website, or your business name on Angi has a comma where your Google profile does not, the model detects a conflict. The confidence score for naming your business drops.
The audit process:
- Pull your current NAP from your website (the exact format you use there is your canonical version)
- Check Bing Places, Yelp, Angi, BBB, and two or three industry-specific directories
- Correct any that differ, including subtle differences like "St" vs "Street" or extra punctuation in the business name
- For directories you cannot edit directly, contact the platform or use a service like Yext to submit corrections
This is not glamorous work. It is also the kind of work your competitors have not done, which is exactly why it moves the needle.
Move 5: Bing Index Health Drives ChatGPT Citation Rate
This is the most direct lever for ChatGPT specifically, and it is the one most local businesses ignore entirely because they have never thought about Bing.
ChatGPT's web search runs on Bing. Not a version of Bing. Bing. If your pages are not indexed by Bing, or if they are indexed but crawled infrequently, ChatGPT is working with stale or missing information about your business.
Three things to do:
Claim and complete your Bing Places listing. Go to bingplaces.com, verify ownership, and fill out every field with the same information as your canonical NAP. This takes 30 to 60 minutes. Most of your direct competitors have not done it.
Submit your sitemap to Bing Webmaster Tools. Go to bing.com/webmasters, verify your site, and submit your sitemap URL. This tells Bing what pages exist and asks it to crawl them. Many local business sites have never been explicitly submitted to Bing Webmaster Tools.
Set up IndexNow pings on content publish. IndexNow is a protocol supported by Bing (and Yandex) that lets you notify the search engine the moment you publish or update a page, rather than waiting for its crawl schedule. When you add a new service page or update your pricing, an IndexNow ping gets that change into Bing's index within hours instead of weeks. The key steps: generate a UUID, drop a verification text file at yourdomain.com/<uuid>.txt, register the key in Bing Webmaster Tools, then ping the IndexNow endpoint whenever a page changes.
Once your Bing presence is current and verified, the pages ChatGPT retrieves when answering local queries will reflect your actual business, not whatever Bing last crawled six months ago.
What to Do in the Next 30 Days
These five moves compound. Do them in the order they are listed, because each one builds on the last.
| Week | Action | Time required |
|---|---|---|
| 1 | Add LocalBusiness subtype schema to homepage and all service pages | 2 to 4 hours |
| 1 | Add Person schema with sameAs to About page | 30 minutes |
| 2 | Write and add FAQ schema to 3 to 5 service pages | 3 to 5 hours |
| 2 | Audit NAP across Bing Places, Yelp, Angi, BBB; correct any differences | 2 to 3 hours |
| 3 | Claim Bing Places, submit to Bing Webmaster Tools, set up IndexNow | 1 to 2 hours |
| 4 | Run your target prompts in ChatGPT and log which businesses appear | 30 minutes |
The 30-day check is important. Run the same 5 to 10 prompts you care about ("best [service] in [your city]," "who to call for [service] near [neighborhood]") and record the results. Do this before you start any of the above work and again after. The difference in citation rate is how you measure whether the infrastructure changes worked.
The 3% citation rate is not a ceiling. It is the baseline for businesses that have done none of this work. The businesses that appear in that 3% are not running a different SEO strategy. They have cleaner data, more specific schema, and a verified Bing presence.
If you want to know where your business stands across ChatGPT, Gemini, Perplexity, and Google AI Overviews right now, start with a free AI search audit. We check all four engines against your target queries and return a gap report with the specific fixes that would move you from invisible to cited.
If you are weighing whether to use a template builder or commission a custom build for this, see AI website builders vs. custom AEO sites for a direct comparison of what each approach delivers on citation infrastructure.
For a full technical build covering schema, Bing verification, NAP cleanup, and FAQ infrastructure as a single engagement, see AI-optimized websites for small business. That is the fastest path from zero to citable for businesses that want it done rather than done by them.
Charles Lau
Founder, Formula Won Labs
Charles Lau is the founder of Formula Won Labs, an AI visibility infrastructure company that helps local businesses rank on Google Maps and get recommended by AI platforms. He works with home service companies, med spas, dental practices, and other local businesses across the US.