Generative Engine Optimization (GEO) Scoring
GEO measures how well your content can be understood, summarized, and cited by AI answer systems. Primenza GEO Intelligence scores pages across readability, citation readiness, structure, and trust — based on crawled content, not guaranteed AI outputs.
What is GEO?
Generative Engine Optimization (GEO) evaluates content readiness for AI-mediated answers — including clarity, structure, entities, citations, and trust signals that affect how machines extract and reference your pages.
GEO vs SEO in Primenza
SEO audits focus on classic search engine technical and on-page signals. GEO audits add AI-readability metrics, citation readiness, entity clarity, and structure pillars designed for answer-engine contexts. Both run from the same domain workspace.
GEO scoring pillars
Primenza groups GEO metrics into four pillars aggregated from page-level measurements:
- Readability — AI readability, semantic clarity, topic coverage
- Citation — citation readiness, answer quality, source credibility
- Structure — entity recognition, structured information, hierarchy, chunking
- Trust — hallucination resistance, fact consistency, expert signals
GEO methodology
For how scores are calculated, data sources, and limitations, see the public Primenza methodology page. GEO scores are normalized 0–100 indicators for prioritization inside the product.
Limitations
GEO scores indicate measured readiness on audited pages. They do not guarantee citations, mentions, or inclusion in any AI engine response.
Primenza GEO capabilities
- GEO Intelligence audits with pillar breakdowns
- Per-page metric storage and recommendations
- Combined visibility scorecards with SEO and AI modules
- Documented methodology at /methodology
References
Frequently asked questions
Is GEO the same as AI search visibility?
Related but distinct. GEO scores on-page readiness from crawls. AI search visibility modules measure discovery and mention patterns where your plan and providers allow.
Where can I read the scoring methodology?
Visit /methodology for observed vs estimated metrics, limitations, and score semantics.