ChatGPT shows wrong information about your business — how to fix it

The annoyance

Someone asks ChatGPT about your company and it answers with confidence. The problem is the answer is wrong.

It quotes pricing you scrapped a year ago. It calls you by your old name. It says you are based in a city you left, or it credits a feature to a competitor that is actually yours. Worse, a customer screenshots it and asks you why your AI says one thing and your website says another.

You did not put that information anywhere. So where is it coming from, and how do you make it stop?

Why it gets your facts wrong

There are three reasons an AI talks confidently about a version of your business that no longer exists.

It learned an old reality. A model has a training cutoff. It read the web at some point in the past and froze that snapshot. If you changed your pricing, renamed the company, or moved offices after that date, the model never saw the update. It is reciting facts that were true when it studied, and it has no idea they have expired.

It is pulling from stale third-party sources. Models corroborate facts from across the web, and a lot of that web is out of date. An old directory listing, an abandoned Crunchbase entry, a competitor's comparison page from 2023, a Wikipedia paragraph nobody has touched in years. If those say one thing and your site says another, the model often trusts the crowd over you.

There is no source it trusts. If the facts about your business are thin or contradictory online, the model has nothing solid to anchor to. So it guesses, stitching together whatever fragments it can find. This is where the truly strange answers come from: a confident sentence assembled from scraps. The same thin-corroboration gap is why some businesses don't get named at all, which is the subject of why ChatGPT isn't citing your website.

Most wrong answers are some mix of all three.

Training memory or live retrieval — which are you fighting?

Before you fix anything, work out where the bad fact lives. There is a quick test.

Ask ChatGPT your question twice: once with web browsing off, once with it on. (Toggle search, or use a plain chat versus one you have explicitly told to search the web.)

If it is wrong both times, you are fighting training memory. The wrong fact is baked into the model's frozen snapshot of the web. You cannot reach in and edit that. The only lever is to improve the public ground truth so that the next time the model is trained or fine-tuned, it learns the correct version.

If it is wrong without browsing but right with it, the model's memory is stale but the live web is correct. That is the good case. It means newer ChatGPT sessions that search the web will already find the truth. Your job is just to make sure that stays true everywhere.

If it is wrong even with browsing on, the live web itself is feeding it bad information. That points straight at the third-party sources. This kind of retrieval-augmented answer is only as good as what the retriever finds, so somewhere out there a page it trusts is telling it the wrong thing. Find that page.

This one diagnostic saves hours, because it tells you whether to wait and seed, or to go hunt down a specific bad source.

The fixes

You cannot log into ChatGPT and correct it. What you can do is fix the signal it reads, so the answer corrects itself on the next crawl or the next retrieval.

Publish the correct facts on your own site, as real text. This is the foundation. Put your current name, pricing, location, founding year, and what you actually do in plain, selectable HTML on pages an AI crawler can read. Not locked in an image, not buried in a PDF, not rendered only after a click. If the canonical facts are not clearly stated on your own domain, you have handed authorship of your story to whoever else mentions you. Make sure GPTBot and the other AI crawlers are allowed to reach those pages.

Add structured data with sameAs links. Mark up your homepage or about page with Organization or LocalBusiness structured data — name, URL, logo, address, the facts you want fixed. Then use the sameAs property to link out to your official profiles: your Google Business Profile, LinkedIn, Wikidata entry, X account. This does two jobs. It states your facts in a machine-readable form, and it explicitly ties together all the places that represent you, so a model can see they are the same entity. We go deeper on this in structured data for AI search, and you can generate the markup with our schema generator.

Get the major third-party sources to agree. Models corroborate. A fact that appears the same way across several independent, reputable sources reads as true; a fact that only your own site claims reads as a claim. So go and update the big ones. Fix your Google Business Profile. Correct your LinkedIn company page. Update or claim your Wikidata entry, and your Wikipedia article if you are eligible for one. Sort out the key industry directories. The goal is consistency: when the model checks five places and they all say the same thing, your version wins. That same credibility-by-corroboration is what decides citations too, which is the angle in why Perplexity cites your competitors but not you.

Keep it current. This is not a one-off. Every time something material changes — a new price, a new product, a new address — update your own site first, then sweep the third-party sources. Drift is how you end up back here in a year.

What to actually expect

Be honest with yourself about timing, because this is where people get frustrated.

If the wrong fact is live-retrieval based, fixing your site and your profiles can correct AI answers within days to weeks, as crawlers re-index and retrieval picks up the new pages.

If it is training-memory based, you are playing a longer game. You cannot force a retrain, and the current model may keep repeating the old fact until the next version learns from a cleaner web. What you control is making sure that when that retrain happens, the public record is unambiguous. Seed the truth now so the future model has no excuse.

Either way, the move is the same: own your facts, make them consistent, and keep them fresh. You are not editing the AI. You are fixing the world it reads from.

Keep an eye on it

The hard part is that you rarely notice the drift until a customer does. By then the wrong answer has been served for months.

Rankport watches what the AI engines actually say about you and flags it when their version stops matching reality, so you find the bad fact before your customers do. You can see where you stand with our AI visibility checker.