Google Gemini: What SGE-SCORE Audits and How the Master-Fix Drives Visibility

How Gemini processes content

Gemini is Google's natively multimodal model — images, text, tables and code are processed in a shared embedding space. In Gemini App, Deep Research and AI Overviews, the model draws from two sources: the classic Google index and the Knowledge Graph. The latter rates entities (people, organisations, topics) on verifiable structural signals.

For you as a website operator this is concrete: a page without clear schema markup, without alt text on images and without entity-rich text faces a massive disadvantage in Gemini. Google's Search Central documentation on structured data explicitly calls schema "the gateway to the Knowledge Graph".

"Gemini scores not only what is written — but also what is structured."

Unlike ChatGPT, which mainly rewards main-content clarity, Gemini weights schema depth and image semantics noticeably higher. A pure text page without schema and without described images stays "flat" for Gemini.

→ Next step: Run our free demo analysis to score your schema depth and image semantics.

The 7 most important signals for Gemini visibility

1. Schema depth ≥ 4 types: Article, FAQPage, BreadcrumbList, Person, Organization — the more linked, the better.
2. Entity density: Clearly named people, places, studies, products — preferably with a sameAs link to Wikipedia/Wikidata.
3. Image alt text with context: Not "image1.jpg", but "Pascal Schildknecht presenting on GEO at ZHAW".
4. Tables with th scope: Gemini parses tables natively when they are semantically correct.
5. Complete Person schema: Mandatory for Knowledge Graph attachment of the author.
6. Multilingual hreflang: Gemini scores canonical language versions — see SGE-GEO knowledge hub.
7. Consistent Organization identity: Logo, name, URL, sameAs must be identical across all pages.

→ Next step: Test a page of your domain with Google's Rich Results Test — if nothing is recognised, schema is missing.

What our audit specifically checks for Gemini

Of the 57 SGE-SCORE checkpoints (max. 114 points), these 12 are particularly relevant for Gemini visibility:

Related read: Structured data for SGE — why Schema.org is decisive. Patent background lives in our knowledge hub; technical details in the docs.

→ Next step: Also read Google Knowledge Graph: the foundation for SGE visibility.

Before / after: what the Master-Fix actually produces

A typical before / after for Gemini looks like this:

Before

<script type="application/ld+json">
{ "@context":"https://schema.org", "@type":"Article",
  "headline":"Our solution" }
</script>

After (Master-Fix output)

<script type="application/ld+json">
[
  { "@context":"https://schema.org", "@type":"Organization",
    "@id":"https://example.com/#org",
    "name":"Example Inc.",
    "url":"https://example.com",
    "logo":"https://example.com/logo.png",
    "sameAs":["https://www.linkedin.com/company/example"] },
  { "@context":"https://schema.org", "@type":"Article",
    "headline":"Our solution for AI visibility",
    "datePublished":"2026-04-30",
    "dateModified":"2026-04-30",
    "author":{ "@type":"Person",
      "name":"Pascal Schildknecht",
      "sameAs":["https://www.linkedin.com/in/pascal-schildknecht-53676566"],
      "knowsAbout":["GEO","SGE","Google Ads"] },
    "publisher":{ "@id":"https://example.com/#org" },
    "image":{ "@type":"ImageObject",
      "url":"https://example.com/hero.jpg",
      "width":1216, "height":640 } }
]
</script>

This connects Article, Person and Organization via @id — Gemini reads it as one coherent entity cluster and can attach it to the Knowledge Graph.

→ Next step: If you have not unlocked the Master-Fix yet: our €9 promo is currently live.

Schema depth: more types, more linkage

"Schema depth" measures not the number of JSON lines but the number of linked types. A reference architecture for a mature page:

• Organization with @id
• WebSite with SearchAction
• BreadcrumbList
• Article with full Person
• FAQPage with all Q&A
• Service or Product for business context

The SGE-SCORE schema reference browser documents required and recommended properties per type — to schema.org spec.

The 5 most common mistakes in Gemini optimisation

• Only one schema block: Article without Organization, Person, Breadcrumb — no entity cluster.
• Images without alt text: Gemini can "read" images but needs a semantic anchor.
• Tables as layout: tables used for column layouts instead of data — no parse points.
• Hreflang missing: a multilingual domain without hreflang loses KG value.
• Logo without ImageObject: logo only as img, not in the Organization schema.

Frequently asked questions (FAQ)