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How klarava measures GEO/AEO
klarava examines representative public pages and reports three separate views of a website: technical readiness, deterministic brand clarity and evidence-bound AI interpretation. Facts and interpretation remain separate, and conclusions are limited to the evidence that supports them.
At a glance
klarava measures observable properties of retrievable pages. Technical and brand signals follow versioned rules; the AI layer interprets only checked content and must cite its evidence. Each layer has its own score and may be marked not assessed. No score predicts rankings, traffic or AI mentions.
The three layers we measure
Each layer answers a different question an AI implicitly asks about a site.
- Technical GEO/AEO. Can machines retrieve and extract the pages? Checks include crawler access, rendering, indexability, canonical signals, structured data, answer structure and sitemaps.
- Brand clarity. Are identity, people, evidence, sources and freshness structurally verifiable? General requirements apply until they are demonstrably not applicable. Optional signals such as customer reviews count only when their applicability is evidenced.
- AI interpretation. Are identity, offering, audience, differentiation, proof and structure clear? Every claim in the AI analysis must cite checked pages and respect their evidence scope.
Evidence, sampling and applicability
klarava does not treat a sample as the complete website. It selects diverse, relevant pages from the sitemap and discovered links, then shows the known inventory and checked sample. One article provides page-level evidence; a section overview may support a section-level statement. Excluded or unusable pages do not become AI evidence.
Requirements can depend on the kind of website. When applicability is unclear, the report qualifies the finding or leaves the dimension unassessed.
How to read the scores
Read the three scores separately. Technical measures machine-readable signals, brand measures applicable structural facts, and AI measures the clarity of checked content across assessed dimensions.
Scores guide decisions; they do not forecast visibility. Do not present results from different score versions as a before-and-after improvement. Live content, crawl access and freshness signals can also change between runs.
What the report delivers
The browser report contains checked pages, evidence, applicability decisions, separate scores and prioritized next steps. It also includes an implementation briefing and drafts for an AI profile, FAQ content and optional llms.txt. Generated content requires professional approval; not every score deduction needs a universal fix.
Transparent about what and why
klarava shows which layers were checked, which pages and evidence support a result, and where the limits lie. The internal detection, selection and validation logic, along with the creation of site-specific drafts, remains part of the product. The method is accountable; the exact implementation stays protected.
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Run the free checkFrequently asked questions
Does klarava check the entire website?
Not necessarily. klarava selects representative, assessment-relevant pages and documents both the known inventory and the checked sample. Findings are limited to the evidence scope of those pages.
What makes the deterministic results reproducible?
The technical and brand layers apply versioned rules to captured signals. With the same inputs, score version and check date, they produce the same result. The AI layer is reported separately because it is model-based.
Does a good score guarantee AI visibility?
No. The scores describe the readiness and clarity of the checked website content. Search rankings, traffic, citations and mentions are controlled by external systems and are not guaranteed.
Are the generated blocks ready to publish?
They are site-specific drafts. Names, claims, contact details, structured data and legal implications must be checked and approved before publication.