Quick answer: When ChatGPT, Perplexity or an AI Overview states wrong facts about your brand – dead products, wrong prices, false history, confusion with another company – you fix it by correcting the sources the error came from: your own pages, structured profiles, and the third-party content engines retrieve. Direct feedback to AI providers helps occasionally; fixing the evidence trail works reliably.
Diagnose where the error lives
Ask the engine to elaborate and check its citations. Retrieval-based errors (Perplexity, AI Overviews, ChatGPT search) trace to a live page you can identify and often influence. Training-data errors (confident wrong answers with no citations) come from the historical corpus – outdated articles, old pricing pages, abandoned profiles – and take longer to wash out.
The correction playbook
1. Fix your own contradictions first. Old pricing pages, stale About copy and dead product pages on your own domain are the most common error source. Update, redirect or remove.
2. Update every structured profile. LinkedIn, Crunchbase (guide), GBP, directories – wrong facts in structured sources get repeated verbatim by engines.
3. Publish an authoritative fact page. A current, schema-marked About page stating name, ownership, products and prices gives retrieval systems a fresher, more authoritative source than whatever spawned the error.
4. Correct third-party sources. Politely request updates on wrong articles and outdated reviews; where the source will not change, outweigh it – fresher corroborating coverage buries stale facts (PR for GEO).
5. Use official feedback channels. Report factual errors via engine feedback tools – inconsistent but occasionally fast, and worthwhile for damaging errors.
Prevent the next error
Entity consistency is inoculation: engines confused about you fill gaps with guesses. A complete entity system – schema, consistent descriptions, active profiles, fresh content – leaves less room for hallucination. Monitor brand prompts monthly with IndexGraph.ai so errors are caught in weeks, not discovered by a prospect.
FAQ
How long do corrections take to appear?
Retrieval-based answers: days to weeks after sources update. Training-data answers: typically the next model update cycle – months. Both start from the moment sources are fixed.
Can I sue over AI misinformation?
Legal remedies are unsettled and slow; source correction is almost always faster and more effective. For defamatory content, consult a lawyer – we are not one.
Found AI spreading wrong information about your brand? Adexorb Technologies runs correction campaigns that fix the record at its sources.