Google Business Profile and AI answers: what we check
The Business Profile checks we run for every local client, the consistency pass against the website, and how we then verify what AI engines actually say about each location.
Clients often ask us how much their Google Business Profile matters for ChatGPT or Google's AI answers. We don't have a sourced answer to how each engine uses profile data, and we're wary of anyone who claims to. What we can do is check two ends of the chain: whether the facts the business publishes about itself are correct and consistent, and whether the AI answers people actually see repeat those facts or contradict them.
This is the checklist we work through for each location.
Part one: the profile itself
None of this is new. It's the same profile hygiene local SEO has always needed, and our local SEO playbook covers the wider program. For AI work we go through it with one extra question in mind: if an engine repeated this field word for word, would it be right?
The business name should match the signage and the website. Not a keyword-stuffed version, and not a legal entity name nobody uses.
Categories come next. The primary category should be the most specific one that fits, and secondary categories should only cover services the location really offers. A category for a service the location dropped two years ago is exactly the kind of thing that ends up recommended back to a customer.
Hours, including holiday and seasonal hours, get checked against what the front desk says, not against what the profile said last year. We check the address or service area, the phone number, and the website link. That link should go to the page for that location, not the homepage, when the client has location pages.
Last, the services list and attributes. These tend to be filled in once and forgotten, so they're where stale facts hide.
Part two: does the website agree?
Then we put the profile next to the client's own site and look for disagreements. The location page, the footer, the contact page and any LocalBusiness markup should all carry the same name, address, phone number and hours. We cover the markup side in local business schema for AI search.
The most common problem is a site that was right when it launched. A location moved, a phone number changed, Sunday hours were added, and the profile got updated while the website didn't (or the other way around). Every mismatch is a fact that could be picked up from either source. We'd rather there be one version.
We also look for old pages: a closed location's page still live, a "new clinic opening soon" post from three years back, a PDF price list. If a crawler can reach it, we treat it as something an engine might read.
Part three: what do AI answers actually say?
Now the part that isn't covered by a profile audit. We run the location through the platform we run client programs on, Promptwatch, with a monitor set to that location. For a walk-in location that's usually a coordinate monitor on the storefront, which makes ChatGPT, Google AI Overviews and Google AI Mode answer as if asked from that spot. For a service area it's a city monitor. Setup details are in how we set up local GEO tracking for a new client.
The prompts for this check are mostly factual, the kind a customer asks before visiting:
- is this location open on Sunday
- what services does it offer
- where is it and is there parking
- does it take walk-ins or bookings only
Then a few unbranded ones, like the best option for a service nearby, to see whether the location gets named at all and how it's described when it does.
We read the responses, not just the scores. Promptwatch stores each response, so we can line up what the engine said against the profile and the site. Anything wrong goes on a list: hours that don't match, a service the location doesn't offer, an old address, a competitor's details mixed in.
Brand settings matter here. Location names are messy. One branch might be called "Brand Northside" in one place and just "Brand" in another. We set brand aliases so all versions count as the client, and use the Brand Book's analysis instructions to spell out what counts as a mention of this location versus the chain.
Part four: trace each wrong fact to a source
A wrong answer is only fixable if we know where it came from. For each error on the list, we look at the citations behind that response. Promptwatch's citation analytics show the pages and domains each answer cited. Often the wrong hours trace back to an old directory listing or an outdated page on the client's own site. Sometimes no citation explains it, and we note that honestly rather than guessing.
Then we fix the source. Profile or website fields get updated by whoever owns them. Third-party listings get corrected or claimed. Stale pages on the client's site get updated, redirected or removed.
Part five: check again later
The monitor keeps running daily after the fixes. We don't expect AI answers to change the next morning, and we don't promise a date. What we do is watch the same factual prompts and the same citations. When the answer starts quoting the corrected hours, or the old listing stops being cited, we can show the client that the fix landed. When it doesn't, the next step is usually another source we haven't found yet.
We also keep an eye on crawler logs for the location pages. If GPTBot, OAI-SearchBot or PerplexityBot hit errors on a location page, that goes to the developer, because a page that fails to load can't be the one an engine quotes.
Why we frame it as checks
It would be easy to write that a complete Business Profile "boosts" AI visibility. We can't source that, so we don't say it. What we can say is that inconsistent facts give every engine a chance to pick the wrong one, and that measuring the answers is the only way to know which one they picked. Profile hygiene is the cheap part. Checking what the engines repeat is where the platform earns its place.
If you want this check run on your locations, email hello@1001seomedia.com with the list.