How to Read GeoAnalyzer's 0-100 Score Before You Act on It

The five categories describe your pages, and the citation record has to be sampled separately on a fixed query set

*Image: Search Engine Results Page (SERP) Graphic Illustration by Muhammad Rafizeldi, licensed under CC BY 4.0.*

GeoAnalyzer is a GEO/AEO audit tool that scores a site from 0 to 100 on its readiness to be cited by AI assistants, according to its about page. The score is built from the site's own pages, but the citation itself is decided by engines on queries you do not control, so the score and the citation record come from different measurements.

The five categories the score inspects

GeoAnalyzer's about page lists five categories behind that score: Entity Clarity, Direct Answers, Trust Signals, Competitive Positioning and Technical Accessibility. Its FAQ describes Entity Clarity as how well AI understands the brand, Direct Answers as how easily AI can extract an answer from the content, and Trust Signals as the credibility indicators in place. The FAQ defines Competitive Positioning as how the site compares with competitors currently being cited, and Technical Accessibility as whether AI can reach the content.

A tier is the band label attached to the overall score. GeoAnalyzer's FAQ sets Bronze at 0 to 59, Silver at 60 to 79 and Gold at 80 to 100, and describes Bronze as basic AI discoverability with weak citation signals and Gold as strong signals for being cited. The pricing page lists what the free scan returns: the overall score, the tier, the top hesitation identified, and results shown instantly. The same FAQ puts the free preliminary score at 30 to 60 seconds.

Those categories describe properties of a page. Entity Clarity is scored from what the page says about the brand and how consistently it says it; the FAQ points to schema markup, knowledge graph entries and consistent mentions as the inputs AI systems use to build an entity. None of the five categories counts citations. A page can carry all five signals and still be absent from an answer, because retrieval, query wording and competitor trust sit between the page and the reply.

What the published evidence supports

A direct published test of these page-level changes is the GEO paper presented at KDD 2024. Aggarwal and coauthors built GEO-bench, a set of queries paired with relevant web sources, and measured whether rewriting source content changed how visible it was in generated answers. Aggarwal and coauthors' reported results show their three best methods producing a 30 to 40 percent relative improvement on the Position-Adjusted Word Count metric and 15 to 30 percent on a Subjective Impression rating. The three methods were adding citations to reliable sources, adding quotations and adding statistics.

The reported improvement is relative to a baseline on a benchmark, so it does not say what a specific site will gain. Aggarwal and coauthors also state in their limitations section that they tested two generative engines, that the methods may need to adapt as engines change, and that they did not evaluate how the changes affect search rankings.

Data on how often brands appear in AI answers comes from a 2026 preprint by Pratyush Kumar of Ranqo, which analyzed more than 100,000 prompt responses across more than 100 brands tracked between March and May 2026. Kumar's preprint reports first-run visibility of 73 percent for global household names, 44 percent for established mid-market and regional brands, and 11 percent for niche and small brands. Kumar's sample puts 78 percent of cited sources at corporate websites. The Ranqo analysis also reports that whether a brand is framed positively or negatively flips about 6.7 times more often than whether it is mentioned at all. Kumar is affiliated with Ranqo, a visibility-tracking vendor, so read those figures as one vendor's measurement of its own sample. The Ranqo figures describe a ladder by brand stature, which no page-level score captures.

Where the page-level score stops

According to Google's documentation on AI features, a page needs no extra work to be eligible beyond the SEO fundamentals Google already documents, and no special schema.org markup is required. Google's same documentation warns that meeting every requirement does not mean Google will crawl, index or serve a page. That documentation also says Google counts traffic from those features in Search Console under the "Web" search type, so a site owner sees only a combined traffic total.

Google's same documentation names nosnippet, data-nosnippet, max-snippet and noindex as the controls that limit what Search shows from a page. Google's same documentation separates those preview controls from AI training and grounding in other Google systems, which the Google-Extended token governs. A page can pass every readiness check and still be blocked from contributing a snippet, so the access check and the content check remain separate steps.

Crawler access is one input a site owner controls directly. OpenAI's crawler documentation states that sites opted out of OAI-SearchBot will not be shown in ChatGPT search answers. OpenAI's same documentation says opted-out sites can still appear as navigational links, and that a robots.txt change can take about 24 hours to take effect. A technical accessibility check establishes whether robots.txt and the documented bot tokens allow access. It cannot establish that the engine surfaces the page for the queries your buyers type.

None of the GeoAnalyzer pages inspected for this article publishes a validation study that ties score bands to measured citation rates. The about page describes the methodology as based on research into how AI engines select and verify sources and lists the five categories, without reporting a correlation between the score and how often a site is cited. The missing validation belongs to the tool's own documentation.

Free score or the $19 report

According to the pricing page, the free scan reports whether the pages carry the signals and which category is weakest. The homepage describes the input as a website URL and an email address, with results delivered to that inbox. The pricing page describes the $19 one-time report as a 15 to 25 page PDF containing:

• the five-dimension score breakdown, with evidence from the site's actual pages
• AI query simulations
• ready-to-paste content blocks
• a competitor landscape
• a per-page site health audit
• a 30-day roadmap
• an AEO best practices guide

The pricing page lists the content blocks as AI-optimized meta descriptions, FAQ sections, about paragraphs and page titles, written for pasting into the site. Those are the page-level changes the score rewards, handed over as text a writer can use.

The pricing page describes the site health audit as reporting per-page signals: word count, reading level and schema completeness. The same pricing page lists Open Graph tags, alt text coverage, freshness dates and author information among the per-page checks. That per-page evidence is the part a developer or a client can act on.

The pricing page describes the query simulations as showing whether AI would cite the site, an estimated position, the response snippet and the competitors that appear alongside. A simulation is a constructed test, so treat its output as a list of queries to run against the engines manually.

The pricing page states that payments are processed by Stripe, and GeoAnalyzer's about page states that it crawls only publicly accessible pages and uses the email address only for report delivery.

Measuring citations alongside the score

Citation measurement needs a fixed query set, because the set defines the number. Write down 20 to 50 questions a buyer would ask, the ones where your category should appear, and keep that list unchanged between runs. For each query, record whether the site is mentioned, where in the answer it appears, which competitors appear and how the site is described.

The query type changes the population. A branded question about what a company does returns pages about that company, while a category question about the best tool for a job returns listicles and comparison pages. Kumar's preprint reports that visibility differs across platforms and varies with brand maturity. Keep separate lists for branded, category and comparison questions, and compare each list with its own history.

Run the sample on a schedule and keep the raw answers. The FAQ recommends quarterly audits for most sites and lists the events that justify an earlier run: significant content changes, new schema markup, updated about pages, or a competitor being cited more often. Because sentiment moves more often than mention, per the Ranqo preprint, score mention and tone separately or a bad quarter for tone will look like a loss of visibility.

A drop in citations with a stable score points at retrieval, competition or query mix. A score drop with stable citations points at something you changed on the page. Keep both columns in one dated file, so the comparison survives a change of analyst.

The decision

Run the free scan first when the question is whether the page needs structural work, and read the tier together with the top hesitation. Buy the $19 report when you need per-page evidence for a developer or a client, and confirm the price at checkout, since the homepage displayed a 50 percent discount with the code GET50OFF on October 15, 2026. Start the query sample in the same week, so the readiness score and the citation record begin from the same baseline.