Why Do AI Search Tools Recommend Local Businesses in the Wrong State?
AI search tools recommend local businesses in the wrong state for a handful of reasons. The city name may exist in several states, as with Springfield, Portland or Columbus. The question may not mention a state, and the assistant may not know or use the user's location. The business's own listings may be vague about where it operates. Metro areas that cross state lines, such as Kansas City or the Washington, DC area, add more confusion. Location errors are common in general. One vendor's test of London businesses found a wrong postcode in about one in ten answers, even when the question named the town. Businesses can reduce the risk by stating city, state and service areas explicitly and consistently everywhere they are listed.
Why does it happen?
| Cause | Example |
|---|---|
| Shared city names | "Best roofer in Springfield" gets answers from Illinois when the user is in Missouri |
| No state in the question | The assistant picks the larger or better-documented city |
| Location not used | VPNs, disabled location sharing, or a question asked without "near me" leave the assistant relying on a rough IP-based guess or on the city name alone |
| Cross-border metros | A Kansas City, Kansas business named for a question about Kansas City, Missouri |
| Ambiguous listings | "Serving the Greater Portland area" without saying which Portland |
| Directory errors | A listing with the wrong state, or an aggregator merging similar businesses |
| Multi-location brands | Answers mix details from branches in different states |
An assistant may not say that a city name is ambiguous; it can pick one interpretation and answer confidently.
Why does the wrong state matter more for some businesses?
For many trades and professions, the state is not just a detail. Contractors, electricians and plumbers are often licensed by state. So are lawyers, insurance agents, real estate agents and many healthcare providers. A recommendation for a business in the wrong state can point a customer to someone who cannot legally take the job. Customers may only find out after calling, which wastes time for both sides and can lead to poor reviews.
How do you test for it?
Run the questions your customers ask in several forms:
- With city and state: "Best HVAC company in Columbus, Ohio"
- With city only: "Best HVAC company in Columbus"
- Near me, with location set: "HVAC repair near me"
- Cross-border: "HVAC company serving Kansas City on the Missouri side"
Run each two or three times in ChatGPT, Gemini, Google's AI Mode, Perplexity and Copilot. Record the state of every business named, whether yours is included, and which sources are cited. Also ask directly: "Where is [business] located?" and "Which areas does [business] serve?"
What should businesses publish?
- City and state together, everywhere: page titles, headings, the footer, the contact page and every profile. "Columbus, Ohio" rather than "Columbus".
- A full address with ZIP code in text, and matching LocalBusiness structured data with the state in the address region field.
- Service areas by name: list the towns and counties you serve, with their state, especially near state borders.
- Licence details by state: licence numbers for each state you are licensed in, and a clear note of states you do not serve.
- Separate location pages for each state or metro area if you operate in more than one, each with its own address, phone number and team.
- Consistent listings: Google Business Profile, Apple Business, Bing Places, Yelp and industry directories should all show the same city, state and service areas.
Cross-border businesses should say it plainly: "Based in Overland Park, Kansas; serving Kansas City, Missouri and Kansas City, Kansas." That one sentence answers the question assistants most often get wrong.
How do you fix wrong listings?
- Find where the wrong state comes from. Check the sources the answers cite, plus major directories and data aggregators.
- Correct the listings on each platform, starting with those cited.
- Remove or update duplicate listings, which often carry old or mistaken addresses.
- Check for similarly named businesses in other states that assistants may be merging with yours, and make your location details more prominent.
- Retest after two to four weeks.
Why AI answers differ from map rankings is covered in why AI local recommendations differ from map rankings. Checking local businesses' visibility more generally is covered in how to check local businesses' AI visibility for prospecting.
What might an illustrative case look like?
Consider an illustrative roofing company in Springfield, Missouri. Customers tell it that ChatGPT recommended roofers in Springfield, Illinois when they asked for "the best roofer in Springfield". Testing confirms it. Without a state, most answers choose Illinois, and the company appears only when "Missouri" is in the question. Its website says "Springfield's trusted roofer" without the state. Its Yelp listing has no service area, and an old directory entry lists the wrong ZIP code. The company adds "Springfield, Missouri" to its titles and headings, and lists the Missouri towns it serves. It states that it is not licensed in Illinois, and corrects the directory. Answers to "best roofer in Springfield, MO" name it more often. Answers without a state still vary, so the company also asks every customer for an honest review.
What do people ask about wrong-state recommendations?
Can a business stop assistants guessing the wrong state?
Not entirely, when users leave the state out. Clear, consistent location details make the right match more likely when the state is given or inferred.
Does structured data help with location?
It helps assistants reading your site confirm the address and state. Profiles and consistent listings matter at least as much.
Should we create pages for cities in neighbouring states?
Only if you genuinely serve them and are licensed to. Pages for areas you cannot serve cause the wrong-fit problem you are trying to avoid.
How often should location details be checked?
Quarterly, and after any move, new branch or change in service area.
Published by The Kovmere Team · updated Sep 29, 2026 · More resources