Compare two sites where AI engines actually make the choice.
Enter two URLs below and run a free head-to-head GEO audit. See which site is more visible to AI answer engines like ChatGPT, Perplexity, and Claude — scored across the same 8 signal categories, side by side.
Site A
Baseline score and blockers.
Site B
Competing signal profile.
Gap
Where one domain wins trust.
Head to head
GEO scoreSee exactly which signals the higher-scoring site has that you don’t.
How comparison works
Each site is benchmarked against the same categories used in the standard GEO audit.
Score
GEO Score across 8 signal categories.
Citability
Citation-oriented content and source signals.
Readiness
Technical access, structure, and AI discovery.
Need to evaluate more than two domains? Use competitor analysis.
When to run a head-to-head GEO comparison
Run a two-site comparison when you have one clear benchmark in mind. The most common cases are your own domain against a single competitor, a before-and-after on a site you have just changed, or two candidate pages competing for the same query. The point is isolation: with exactly two sites, every difference in the score is attributable to one of them, not averaged across a crowd.
It is the wrong tool when you want a market picture. If you are trying to understand how a whole category treats AI visibility, or to rank several domains at once, a single pair will mislead you. For that, use multi-competitor analysis. And if you only need a baseline for one site, you do not need a comparison at all — run a single audit first, then compare once you have something to measure against.
What the 8 signal categories measure
Both sites are scored on the same eight categories used in the standard GEO audit, weighted to a total of 100 points. The weights reflect how much each category influences whether an AI answer engine can reach, understand, and quote a page. Crawlability and orientation files carry the most weight because they gate everything downstream: if a bot cannot fetch the page or find your key URLs, the quality of the content never gets a chance to matter.
| Category | Weight | What it checks |
|---|---|---|
| robots.txt | 18 | Whether AI crawlers can reach the site and whether the file invites citation-oriented bots rather than blocking them by default. |
| llms.txt | 18 | Presence and quality of a root-level llms.txt: title, summary, sectioned links, and link depth that orient AI systems to the right pages. |
| Schema JSON-LD | 16 | Valid structured data — Organization, WebSite, Article, FAQ — that lets engines disambiguate entities and pull facts confidently. |
| Meta tags | 14 | Title, description, canonical, and Open Graph tags that keep the page identifiable and free of duplication. |
| Content | 12 | Heading hierarchy, front-loaded answers, lists, and the numbers and links that make passages quotable. |
| Brand & entity | 10 | Naming coherence, knowledge-graph readiness, and about/contact clarity that tie pages to a recognizable entity. |
| Signals | 6 | Declared language, RSS, and freshness indicators that help engines judge currency. |
| AI discovery | 6 | Machine-readable endpoints such as /.well-known/ai.txt and JSON summaries that expose the site to AI tooling. |
The same weights apply to both sites, so the comparison is apples to apples. A site can score well on content yet lose the overall gap on a single blocked crawler — which is exactly the kind of imbalance a side-by-side view makes visible.
How to read the gap between two sites
Read the gap by category, not by the headline number. Two sites can sit ten points apart for very different reasons, and the reason determines the work. A gap concentrated in robots.txt or llms.txt is usually a technical fix you can ship in an afternoon. The same gap spread across content and brand signals reflects editorial and authority work that takes weeks.
Map each category difference to the band it falls into:
Most signals in place; the site is structurally ready to be cited.
Solid foundation with a few high-value gaps left to close.
Core pieces exist but several categories need work.
Crawlability or structure blocks visibility before content matters.
Then prioritize where the difference is largest and the effort is lowest. A losing site in the foundation band with a strong competitor in good territory should fix crawlability and structure before touching copy. If you want the full reasoning behind why these categories matter for AI engines specifically, the GEO vs SEO guide explains what changes when the interface is an answer rather than a list of links.
Comparison vs multi-competitor analysis
A two-site comparison and a multi-competitor analysis answer different questions. The comparison is built for depth on a single pair: it puts two domains side by side so the gap in each category is explicit and easy to act on. It is the right tool for a duel — you versus one rival, or one version of a page versus another.
Multi-competitor analysis is built for breadth. It runs a batch audit across several domains and surfaces the pattern — shared blockers, the signals the leaders have in common, and where a whole set of sites is weak. Use it when you are setting strategy for a category rather than closing a gap with one competitor. When a pattern points you back to a single contender, return here and run the head-to-head. See competitor AI visibility analysis for the multi-site view.
Comparison FAQ
What does a head-to-head GEO comparison actually measure?
It scores two sites across the same 8 signal categories used in the standard GEO audit — robots.txt, llms.txt, schema, meta tags, content, brand and entity signals, freshness signals, and AI discovery — and shows the gap category by category. The output is a relative readiness picture, not a prediction that a specific model will cite either site.
Is the comparison free, and do I need an account?
The two-site comparison is free and runs without an account. It returns a side-by-side GEO score for each URL across all 8 categories. Saving reports and tracking changes over time are account features, but the comparison itself is not gated.
When should I compare two sites instead of analyzing several competitors?
Use a two-site comparison when you have one clear benchmark — your domain against a single competitor, or a before-and-after on a redesign. When you need to see a market pattern across a set of domains, multi-competitor analysis is the better tool because it surfaces shared blockers and ranks several sites at once.
Does a higher GEO score guarantee more AI citations?
No. The score measures structural readiness — whether crawlers can reach the site, whether content is quotable, and whether entities are clear. Citation behavior in AI engines is probabilistic and changes as models are retrained. A stronger score removes friction; it does not force a citation.
Which AI engines does the comparison reflect?
The signals are engine-agnostic. They reflect the technical and content conditions that AI answer engines such as ChatGPT, Perplexity, and Claude rely on when they retrieve and cite sources — crawler access, structured data, quotable content, and entity clarity — rather than any single vendor’s ranking system.
How should I read a large gap between two sites?
Read it by category, not by the headline number. A 20-point gap concentrated in robots.txt or llms.txt is a fast, technical fix; the same gap spread across content and brand signals reflects slower editorial work. Start with the category where the difference is largest and the effort is lowest.