The short answer
AI assistants don't look up your business by address — they look it up by name, and names aren't unique. If a customer asks ChatGPT about "Riverside Dental" and there are three Riverside Dentals in three different states, the model has to guess which one the question is about. Sometimes it guesses wrong, and it answers with another business's hours, phone number, or reviews stitched onto your listing.
This is entity confusion, and it's a different problem from having wrong information. Your data can be perfectly accurate everywhere it's published and you'll still get blamed for another business's bad Yelp review, because the AI merged the two of you into one answer.
Why this happens more than you'd think
Large language models build their picture of local businesses from a mix of training data, web search results, and structured data pulled at answer time. None of those sources come with a guaranteed-unique ID the way a database record would. The model is pattern-matching on name plus rough location, and "rough" is the operative word — it often doesn't distinguish between two cities in the same state, let alone two neighborhoods in the same city.
A few things make it worse:
- Generic or common names. "Riverside," "Main Street," "Elite," and "Family" show up in business names constantly. A search for "Elite Auto Repair" turns up dozens of unrelated shops nationwide.
- Franchises and copycats. If you run an independent shop and a regional chain opened a location with a nearly identical name, you're now competing for the same slot in the model's understanding — even though you have no relationship to them.
- Thin or missing disambiguating details. If your website, directory listings, and Google Business Profile don't consistently pin down your city, neighborhood, or a distinct part of your name, there's less for the model to anchor on.
- Old citations that never got cleaned up. A defunct business with a similar name, sitting in an old directory that still ranks, can pull weight even years after closing.
How to tell if it's happening to you
Ask ChatGPT, Claude, or Perplexity a direct question about your business — "What are the hours for [Business Name] in [City]?" or "Does [Business Name] take walk-ins?" — and read the answer closely, not just for accuracy but for details that don't belong to you at all: a phone number with the wrong area code, a service you don't offer, a price point that's off by a lot. Those are signs the model pulled from a different entity, not just outdated data about your own.
This is a narrower failure mode than the general accuracy problems covered in why AI gets your business info wrong, and it needs a different fix — you're not correcting stale facts, you're helping the model tell two entities apart. A free scan will flag this specifically when it shows up, since a scan that returns details clearly belonging to another business is a strong signal of a naming collision rather than a data-freshness issue.
How to fix it
You can't rename your competitor, but you can make your own entity sharper and easier to isolate.
Be specific everywhere, every time. Don't just say "Riverside Dental" on your homepage — say "Riverside Dental, serving [Neighborhood] in [City, State]" in your title tag, your About page, and your Google Business Profile description. Repeat the disambiguating detail rather than assuming one mention is enough.
Use LocalBusiness schema with full address fields filled in. Structured data gives AI systems and search engines a machine-readable anchor for who you are and where you are, instead of forcing them to infer it from prose. See LocalBusiness schema for local businesses for the fields that matter most.
Audit your own citations for the collision. Search your business name in quotes plus your city. If a same-named competitor or a defunct business ranks near you, that's likely contributing to the confusion — you can't remove their listing, but you can make sure every listing that is yours is airtight and consistent.
Lean on details only you have. A specific owner name, a specific founding year, a specific cross-street — anything that's true of your business and unlikely to match the other one gives the model something concrete to lock onto, the same way it helps humans tell two similarly named places apart.
For the fuller picture on getting an AI assistant to describe your business correctly and recommend it over a mixed-up alternative, see how to get recommended by ChatGPT.
Next step
Run your business name through a free scan and read the answer for details that don't match anything you actually offer — that mismatch is often the first sign you're sharing a name with someone else online. If the fix requires ongoing cleanup across listings and schema, the $29/mo plan tracks it so you're not re-checking manually every month.