What is brand accuracy in AI answers?
Brand accuracy is whether AI answers describe your brand correctly: what you sell, who it is for, what it costs and how you compare. Visibility asks whether AI names you. Accuracy asks whether what it says is true. A wrong price, a retired plan or the wrong audience can cost more than being left out, because the buyer believes it.
What does brand accuracy cover?
Brand accuracy covers every fact a buyer might act on:
- What you are: category, products and what you do not do.
- Price and plans: amounts, limits, free trials and what each plan includes.
- Who you are for: team size, industry, region.
- Company facts: founding, headquarters, ownership.
- Comparisons: how you differ from the competitors named beside you.
Where do wrong facts in AI answers come from?
Mostly from sources, and some from memory. An engine that searches repeats what the pages it read say, so an out-of-date roundup or an old pricing page puts the stale fact straight into the answer (the post).
An engine answering from memory repeats what the web said before its training cutoff. And a name shared with something else can pull in the wrong entity's facts; see entity confusion.
What does brand accuracy look like in a real example?
In the public Tesla example (Oct 4, 2026), Claude answered two brand questions from memory with no sources. Asked "What is Tesla?", it said the company was founded in 2003 by Martin Eberhard and Marc Tarpenning. Asked "Is Tesla legit?", it said Tesla was founded by Elon Musk in 2003.
The two answers disagree about the founding, on the same engine, in the same run, and neither cites anything to check. Google AI Overviews, asked "What is Tesla?", opened with the magnetic unit before reaching the company.
How do you check and fix brand accuracy?
Check against your own facts, then fix the source the answer used:
- Write a fact sheet: price, plans, audience, founding, what you are not.
- Ask brand questions on each engine and compare every claim with the sheet.
- For each wrong claim, open the pages the answer cited and find the one that says it.
- Fix it if it is yours; ask the publisher for a correction, with proof, if it is not.
- Re-ask the same question on the same engine over several runs to confirm the fix landed.
How does Proofsource check brand accuracy?
Proofsource builds a fact sheet from your site that you confirm, then checks each answer that mentions your brand claim by claim, marking each correct, wrong or out of date, and raises an alert with the wrong sentence and the right fact side by side. See Accuracy and sentiment.
Common questions about Brand accuracy
Why does ChatGPT show an old price for my product?
Either it answered from memory, or it read a page that still carries the old price, often a third-party roundup or review. Check the answer's sources first; if there are none, the fix is slower.
How long does it take to correct AI answers about my brand?
For engines that search, the corrected page has to be recrawled and retrieved again, usually days to weeks. Answers from memory change only when a newer model ships.
Is brand accuracy part of AI visibility?
It is measured on a different set of questions. Visibility uses buyer questions that do not name you; accuracy uses brand questions that do.
Can I contact OpenAI or Google to fix a wrong answer?
The engines offer feedback buttons, but there is no guaranteed correction path. Fixing the sources an answer reads is the route you control.
Related terms
- AI hallucination
A hallucination is a confident statement in an AI answer that is false or unsupported, such as a wrong price, a feature that does not exist or a source that was never written.
- Brand question
A brand question is a question that names your brand, such as "What is Tesla?" or "Is Tesla worth it?", used to check how AI describes you rather than whether it names you.
- Entity confusion
Entity confusion is when an AI answer about your brand describes, or opens with, a different company or thing that shares or resembles your name.
- AI sentiment
AI sentiment is the tone an AI answer takes when it names your brand: positive, neutral or negative.
Worked example: Tesla, public AI answers, Oct 4, 2026: Proofsource's first scan of Tesla, 25 buyer questions and 5 brand questions, one answer per question on each of four engines. A small sample from one brand, shown as an example, not a benchmark.
See where AI leaves you out, and what to fix.
See which buyer questions name your brand, who gets named instead, and what to fix. 200 answers. 25 Prompts/Question. Top AI engines. 2 days. Free. No card.
Google AI OverviewsGoogle AI Mode
