Direct answers to the questions B2B teams ask about AI visibility, GEO, AEO, ChatGPT citations, and getting their brand into AI search results.
AI Overviews pull from the same Google index as regular Search, so the path in is standard SEO: crawlable pages, strong E-E-A-T signals, and content with original insight. Google confirmed in May 2026 that no special files, markup, or AI-specific rewrites are required.
ChatGPT confuses your company with another because it links your name to the wrong entity in its internal knowledge graph. This is brand disambiguation failure, not hallucination: the facts it returns may be accurate, just about a different company that shares your name. The fix is stronger entity signals, not more content.
AI visibility audits range from free to a few hundred dollars per month. Radar starts at $0 for technical readiness tools, $5 for a single full audit, and $199/month for a Pro Retainer with weekly re-scans. Subscription competitors like AthenaHQ ($295/mo) and Gauge ($99/mo) sit at the higher, monitoring-only end.
ChatGPT cites sites it treats as authoritative for a query. Most B2B SaaS sites lack three specific signals: structured data declaring entity identity, an llms.txt file, and citations from domains ChatGPT already trusts.
Perplexity cites sources it crawls + ranks for the live query. To get cited: allow PerplexityBot in robots.txt, ship answer-first content (FAQPage schema, BLUF paragraphs), and acquire citations from high-authority domains Perplexity already ranks.
Generative Engine Optimization (GEO) is the practice of structuring web content so AI search engines like ChatGPT, Claude, Perplexity, and Gemini cite it in their responses. Unlike SEO which optimizes for keyword rankings, GEO optimizes for entity recognition, structured data, and citation probability.
All four AI engines surface brand information but cite sources differently. Perplexity shows explicit URL citations. ChatGPT blends training data with browsing. Claude prioritizes recency and reasoning. Gemini integrates live Google search results.
ChatGPT hallucinations about your company come from three sources: outdated or thin training data, confusion with similarly-named companies, and absence of authoritative web sources for ChatGPT to ground its answers in. Each source has a different fix.
AI engines surface companies they trust as authoritative for a query. Invisibility usually means one of three things: AI crawlers cannot access your site, your structured data does not identify your entity, or no high-authority source on the web mentions you.
Perplexity ranks sources per-query by domain authority, content relevance, and recency. If your competitor is cited and you are not, they typically beat you on one of three signals: answer-first content structure, citation accumulation from high-trust domains, or recency of updates on the relevant page.
Add a JSON-LD script tag with Organization schema to your root layout (head). Include name, legalName, url, logo, foundingDate, founders, sameAs links to LinkedIn/GitHub/Crunchbase, and disambiguatingDescription if a similarly-named company exists. AI engines re-crawl and update within 7-14 days.
ChatGPT cites content that answers a specific question in 1-3 sentences and comes from a domain it trusts. Five tactics: open every section with the answer (BLUF), use question-shaped H2s, ship FAQPage schema, structure data as HTML tables, and republish with fresh dateModified when claims change.
Answer Engine Optimization (AEO) is the practice of structuring web content so AI engines can extract and cite it as a complete answer. AEO focuses on extraction-friendly formatting: BLUF paragraphs, FAQPage schema, HTML comparison tables, and speakable schema.
llms.txt is an emerging markdown spec that tells AI engines what your site is about, what content they should prioritize, and how to use it. It sits at /llms.txt. If your buyers research vendors via ChatGPT, Claude, Perplexity, or Gemini, yes — you need it.
All three matter, but for different buyer behaviors. SEO captures Google search traffic. GEO builds entity authority that AI engines cite. AEO formats content for extraction by AI answer engines. B2B SaaS teams need all three; consumer brands prioritize SEO; emerging AI-native teams prioritize GEO + AEO.
Both matter and they do different jobs. Schema.org JSON-LD identifies your entities (Organization, Product, Person) per-page for machine parsing. llms.txt is a site-level declaration of what your site is about, what content to prioritize, and how AI engines should use it. Ship both.
AI Readiness scores under 60 usually indicate a critical gap in one of five categories: bot discoverability, structured data, LLM communication (llms.txt), content accessibility, or cross-signal readiness. The category breakdown in your Radar audit identifies which one is dragging the unified score down.
Run a head-to-head audit to identify exactly which signals your competitor has that you do not. The gap is typically one of: bot access, Organization schema, llms.txt, authoritative citations, or freshness. Close the gap on the highest-impact signal first, expect 30-60 days to register in ChatGPT.
Our most-cited deep dives on AI search visibility, plus what we shipped this month.
Learn the difference between SEO, AEO, and GEO, and how brands can move from ranking in search to being cited in answers and recommended by AI engines.
Grok answers brand questions for 117M monthly users per the SpaceX S-1. We measured what it says, and it got our own brand wrong. Check yours today.
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