AI Visibility Scanner — GEO & LLM Optimization Checker

How the AI Visibility Scanner Works

1. 1Enter a full URL (e.g. https://example.com/blog/my-post). The scanner accepts any publicly accessible page — your homepage, a blog post, a product page, or a tool page.
2. 2Click Scan. Our server fetches the page HTML directly, then checks your robots.txt and sitemap.xml — all in parallel so results are fast.
3. 3The scanner analyses 25+ signals across four categories: Technical, Meta & SEO, Content Signals, and Structured Data. Each check earns points toward a total score out of 100.
4. 4Review your scored report with pass/warn/fail indicators for every check. Each finding includes a plain-English explanation and the specific fix needed to improve your score.

What Is Generative Engine Optimisation (GEO)?

Generative Engine Optimisation is the practice of structuring web content so that AI-powered search systems — Google AI Overviews, Perplexity, ChatGPT Search, and similar tools — can accurately extract, attribute, and cite your content in their generated answers. Unlike traditional SEO, which optimises for ranking position in a list of links, GEO optimises for inclusion in AI-generated summaries that may not link at all.

The core difference: traditional search engines rank pages and let humans decide what to click. AI engines extract information from pages and synthesise an answer directly, often citing one or two sources. Pages with clear structure, explicit question-and-answer content, and machine-readable schema markup are disproportionately likely to be cited. Pages without these signals are effectively invisible to AI engines even if they rank well in classic search.

The Complete Guide to AI Visibility and GEO

For twenty years, being found online meant one thing: ranking on the first page of Google's ten blue links. That world is changing fast. AI-powered search — Google's AI Overviews, Perplexity, ChatGPT Search, and a growing list of assistants — increasingly answers questions directly by synthesising information from web pages, often citing just one or two sources and frequently without the user ever clicking through. This shift has created a new discipline, Generative Engine Optimisation (GEO), focused on making your content the source an AI chooses to extract and cite. This guide explains how AI search differs from the search you know, what signals these systems rely on, and how to make your pages genuinely AI-visible.

How AI Search Differs from Traditional Search

The fundamental difference is extraction versus ranking. A traditional search engine ranks a list of pages and leaves the human to click and read; its job ends at ordering links. An AI engine goes further: it reads the pages itself, pulls out the specific facts that answer the question, and composes a single synthesised answer. The human may get their answer without visiting any site at all. This changes what “winning” means. You are no longer only competing for a rank position — you are competing to be the passage an AI lifts its answer from and attributes.

That reframing has real consequences. A page can rank well in classic search yet be effectively invisible to AI engines because its information is buried in prose the model cannot easily parse, or because it lacks the machine-readable structure that lets an AI confidently extract and attribute a fact. Conversely, a clearly structured page with explicit questions, answers, and schema can be cited by an AI even when it is not the top classic result. GEO is about making your content easy for a machine to understand and quote, not just easy for a human to find.

The Building Blocks of AI Visibility

AI engines reward content that is structured, explicit, and unambiguous. A handful of building blocks do most of the work:

• Structured data (JSON-LD): machine-readable markup that states plainly what a page is and what it contains — an article, an FAQ, a product, an organisation — removing the guesswork for a crawler.
• Clear heading hierarchy: a single descriptive H1 and logical H2/H3 sub-headings that map the page's structure, letting a model navigate it the way a table of contents would.
• Explicit question-and-answer content: real FAQ sections where a question is stated and directly answered, which mirrors exactly how people query AI assistants.
• Content depth: substantive, genuinely informative coverage of a topic, which signals authority and gives an AI enough material to draw a confident answer from.
• Entity signals: organisation and website schema that anchor your brand as a recognised entity in the knowledge graph AI systems consult.

None of these are tricks; they are simply clarity made explicit. The same structure that helps an AI extract your content also helps human readers skim and understand it, which is why GEO and good content design point in the same direction.

Why FAQ Schema Punches Above Its Weight

Among all the signals, FAQPage schema delivers the most impact for the least effort, and it is worth understanding why. When you mark up question-and-answer pairs in JSON-LD, you hand an AI engine a set of ready-made answers in exactly the format it wants — no natural-language interpretation required. The engine does not have to guess which sentence answers a question; you have told it explicitly, in machine-readable form. Because AI assistants are fundamentally question-answering systems, content that is already shaped as questions and answers aligns perfectly with how they work.

The practical payoff is that a page with well-written FAQ schema is far more likely to have its answers extracted and cited than an equivalent page that buries the same information in paragraphs. The key is that the questions must be ones real people actually ask, and the answers must genuinely and completely answer them — schema wrapped around thin or evasive content helps no one. Done well, four to eight solid questions per page is one of the highest-return changes you can make for AI visibility.

GEO and SEO: Overlap and Differences

GEO does not replace SEO — it extends it. The two share a great deal: both reward fast, accessible, well-structured pages with clear titles, sensible headings, and genuine authority. If your SEO fundamentals are sound, you are already part of the way to good AI visibility. But the priorities differ in emphasis. Classic SEO leans heavily on ranking signals like backlinks, page speed, and Core Web Vitals. GEO leans harder on machine-readable structure and answer-shaped content — schema markup, explicit Q&A, clear entity signals, and topical depth — because those are what let an AI extract and attribute your content with confidence.

The healthiest way to think about it is that GEO is a layer on top of solid SEO, not a competing strategy. Fix the technical and content fundamentals that both share, then add the structured-data and Q&A signals that AI engines specifically depend on. A page optimised this way tends to perform well in both worlds at once.

A Practical Roadmap to Improve Your Score

If you are starting from a low score, tackle the highest-impact items first. Begin by adding FAQPage schema to your key pages, since it offers the best return. Next, ensure each page has a single clear H1 and a logical heading structure, and that your meta title and description fall in their optimal length ranges so engines use your deliberate summary rather than inventing one. Add Organization and WebSite schema through your shared layout so every page inherits those entity signals with a single change. Confirm the technical basics — HTTPS, a canonical URL, an accessible robots.txt, and an XML sitemap at your root — so AI crawlers can find and trust your pages.

Finally, invest in content depth: thin pages rarely get cited, because they give an AI little to work with and little reason to treat them as authoritative. Re-scan after each round of changes to see your score climb and to catch anything you missed. Remember that a high score removes the barriers to being cited — it does not guarantee it, because relevance, authority, and genuine quality still matter and cannot be faked with markup alone. Treat the scanner as a checklist for making your best content as easy as possible for AI engines to understand, quote, and attribute.