GEO audit: know exactly what AI says about you

An SEO audit and a GEO audit are both diagnostic tools, but they measure completely different search ecosystems. An SEO audit targets Google’s ranking algorithm: crawlability, indexability, Core Web Vitals, backlink profiles, and keyword density. A GEO audit targets AI language models: whether engines can parse your content, whether your facts are grounded and citable, whether your authority signals are machine-readable, and whether the tone of your pages makes you a trustworthy source inside AI-generated responses. The two disciplines are complementary. Strong SEO hygiene, fast pages, clean HTML, proper canonicals, improves your GEO baseline. But many sites with perfect SEO scores are invisible in AI answers because they lack structured data, factual depth, or the semantic authority signals that LLMs weigh. Running both audits in parallel gives you the full picture of your search presence.

Citeme covers ten AI surfaces: ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Perplexity AI, Grok 4.3 (xAI), Siri AI (Apple, on iOS 27), DeepSeek, Meta AI and Mistral through their official APIs, plus Google AI Overviews through SERP capture. That last one matters more than the others combined for most brands, because it is the AI surface the largest number of people actually see, and it appears above the classic results rather than in a separate product. Each engine retrieves information differently, and that difference matters for your strategy. ChatGPT and Claude are primarily language models that draw on training data, with some live web retrieval in recent versions. Perplexity functions as an AI search engine that actively fetches and cites live web pages in every answer. Gemini blends both approaches, while Grok operates within X’s data ecosystem and draws on real-time posts alongside indexed content. The same website can have strong visibility on Perplexity, which indexes the live web, while being nearly absent from ChatGPT, which leans on training patterns built months earlier. Citeme surfaces these gaps engine by engine, so your team knows exactly where to concentrate effort. Every engine is queried with prompts tailored to your actual market, not generic benchmarks.

The right cadence depends on how actively you publish and how competitive your market is. Every team should begin with a baseline audit before any optimization work, you need a starting point to measure progress against. After that, three triggers should prompt an immediate re-audit. First, after every significant content update: when you publish a pillar page, update a core product page, or restructure site navigation, re-audit within two weeks. AI engines with live retrieval like Perplexity can pick up changes quickly, and you want to confirm the impact. Second, on a regular cycle every 4–6 weeks: AI models update their training data, retrieval logic, and ranking preferences continuously. A site that was performing well six weeks ago may have slipped without any change on your end, the engine moved. Third, when a competitor makes a major move: a rival launching new content targeting your core queries is a direct trigger for an immediate comparative audit to quantify the shift. For teams managing multiple sites, Citeme’s automatic scheduled audits run weekly or daily in the background, so you’re always notified before a gap becomes a trend.

The GEO Score runs from 0 to 100 and reflects your AI citation visibility, built from visibility, authority and sentiment across the engines you’re targeting. A score above 70 indicates solid AI visibility; below 50, your site is likely invisible or inconsistently cited across the engines. Keep in mind that target scores depend on your competitive landscape. In highly contested categories, fintech, SaaS, legal, healthcare, market leaders often sit at 85–95. A score of 72 in one of those markets may still mean you’re losing ground to more aggressive competitors. The more actionable number is the breakdown beneath the overall score. A site at 65 overall might score 92 on metadata but only 28 on content depth and semantic coherence, meaning the problem is editorial, not technical. The audit surfaces this detail and identifies the specific pages dragging the number down. Fix those first, re-audit, and track the delta.

An audit checks the conditions a model needs before it can cite you at all, and reports them next to the citation results. Access comes first. If GPTBot (OpenAI), ClaudeBot (Anthropic), PerplexityBot or Google-Extended are blocked in your robots.txt, nothing else matters, because a crawler that cannot read the page cannot quote it, and many sites block them without knowing it through legacy rules. The same applies to our own crawler: behind Cloudflare or a strict WAF the CiteMeBot/1.0 user agent has to be allowed first, and pages behind a login, pages marked noindex and pages absent from your sitemap are never read. Then comes machine readability. JSON-LD and structured data give a model the context to understand who you are and what you sell. Metadata provides the first signals it reads. The H1 to H6 heading hierarchy decides how cleanly your pages break into the segments of roughly 300 words that get turned into embeddings, which is what the semantic analysis actually works on. The project record carries a structured data score and a metadata quality score, next to the number of pages analysed and the date of the last automated check. The rest is content and off-site: factual grounding and freshness, semantic consistency with the vocabulary of your market, and the off-site signals, backlinks, brand mentions, press coverage and social presence, which a dedicated node can recalculate on demand rather than only at audit time.

Your audit delivers a ranked action list, start with the highest-impact items, not the ones that feel most familiar. The fastest wins are almost always technical: AI crawler access, JSON-LD structured data, and metadata. If any AI crawlers are blocked in your robots.txt, GPTBot and ClaudeBot are the most common offenders, unblocking them is the first move. Nothing else matters until the engines can read your pages. Once crawlability is confirmed, adding or enriching JSON-LD schema and sharpening title tags typically delivers the most immediate score lift. Content fixes are slower to propagate but more durable. Pages flagged for low content depth need substantive rewrites, more facts, direct answers, data tables, and expert quotes, not just more words. FAQ sections on product pages are particularly effective because they match the question format AI engines query with. Citeme’s Actions feature automates many of these changes: you review and approve, the AI agent writes and publishes directly to your CMS. After each round of fixes, re-run the audit to confirm the delta before moving to the next priority batch.

Yes, every Citeme audit runs on shared prompts, meaning your competitors appear in the same AI responses you do. The audit captures their citations alongside yours and surfaces three competitive views. The GEO Podium shows which brand ranks first most consistently across your full query set. Share of Model shows each player’s percentage share of all citations across the engines and prompts audited. The dimension breakdown lets you compare your structured data or content depth score directly against a competitor’s, pinpointing exactly where they outperform you and by how much. This makes it immediately visible if a rival is winning on Perplexity but absent on Claude, a strong signal about the type of content driving their citations and where you can counter most efficiently. You can also run direct competitor audits: input a competitor’s URL and audit it exactly as you would your own site, surfacing the specific technical and content gaps that explain their AI visibility advantage.