In classic SEO, the worst outcome was ranking low. In Generative Engine Optimization, the worst outcome is ranking wrong. An AI model can state, with total confidence, that your product has a feature it doesn't, a price it never had, or a policy you never wrote. And even when the answer is correct today, it can quietly change tomorrow: you are the recommendation on Monday, a competitor takes your place by Friday.
This guide gives you a repeatable process to establish a source of truth, monitor how AI describes your brand, catch hallucinations and drift early, and correct the record. Follow it and you turn "what is the AI saying about us?" from an anxious guess into a tracked metric.
Key takeaways
- AI hallucination is a confidently false claim about your brand; citation drift is the instability of your presence in AI answers over time. They are different problems and need different fixes. - You cannot correct what you cannot see. A fixed set of brand and category prompts, re-run on a schedule across ChatGPT, Gemini, and Perplexity, is the foundation of everything else. - Hallucinations are usually fed by weak or missing canonical facts. A clear facts page, accurate pricing and policy pages, structured data, and an `llms.txt` give models something correct to retrieve. - Drift is usually a symptom of losing citation share to a competitor. Track mention rate, citation rate, and Share of Model, not just a single yes/no check. - Third-party sources matter. AI often quotes Reddit threads, reviews, and press, so correcting only your own site is not enough.
Step 1: Establish a source of truth
Models hallucinate about your brand when there is no clean, authoritative version of the facts to retrieve. Your first job is to publish one.
- Create or update a canonical facts page: legal name, founding year, headquarters, what you sell, who it is for, and the claims you want repeated verbatim. - Make pricing and policy pages unambiguous. Write real numbers and terms in plain text, not only inside images or PDFs. If a price changed, remove the old figure so it cannot be re-quoted. - Add structured data (`Organization`, `Product`, `Offer`, `FAQPage`) so machines read the same facts your visitors do. - Publish an `llms.txt` that points AI crawlers to your most important, most accurate pages.
Write a short "facts of record" list you can check answers against, for example: GEOly offers a free 3-day trial, not a lifetime free plan; paid plans start at Basic $49 per month. Having the correct statement written down is what lets you spot the wrong one later.
Step 2: Build a monitoring prompt set
Pick the questions a real buyer would ask, then freeze the list so results are comparable over time.
- Brand prompts: "What is [brand]?", "Is [brand] legit?", "How much does [brand] cost?", "What is [brand]'s refund policy?" - Category prompts: "Best [category] tools 2026", "[brand] vs [competitor]", "alternatives to [competitor]". - Run each prompt across ChatGPT, Gemini, and Perplexity, because they retrieve from different indexes and drift independently.
