GEO Content Review Framework: 6 Scoring Categories to Get Cited by AI

Most GEO content fails for reasons authors never check

Your content can have perfect structure, authoritative sources, and fresh data — and still get ignored by AI engines. The missing piece is usually semantic authenticity: content that reads like a brand ad or AI-generated filler triggers trust penalties that no amount of schema markup can fix.

This framework gives you six scoring categories to evaluate any page before publishing. Run every piece through it, and you'll catch the gaps that keep content out of AI-generated answers.

The 6 scoring categories

Category | What it measures | Why AI engines care
Structure & Quotability | BLUF, headings, tables, FAQ | Engines extract discrete answers from structured content
Trust & Authority | Citations, expert quotes, source quality | Engines verify claims before citing them
Freshness | Publish dates, data recency, citation decay | Stale content gets deprioritized in synthesis
Brand Integration | Mention density, competitive context | Over-promotion flags content as advertising
Semantic Authenticity | Author voice, testing evidence, bias signals | AI detects "brand ad feel" and downgrades trust
Engine Fit | Format alignment with target engine preferences | Each engine weights different signals

1. Structure & Quotability

AI engines don't read your page top-to-bottom. They scan for independently quotable fragments — a heading that answers a question, a table row that compares options, a FAQ entry that matches a user's prompt.

Checklist:

BLUF (Bottom Line Up Front) — Does the first paragraph answer the core question? ChatGPT and Perplexity both favor content that leads with the answer, not a preamble.

Question-based H1 — Does the H1 match how users phrase queries to AI engines?

H2/H3 independence — Can each subheading stand alone as a cited snippet?

Comparison tables — Are key comparisons in table format, not buried in paragraphs?

FAQ section — Do you have 3–5 FAQs that match long-tail AI queries?

Schema hints — Is there structured data (FAQ schema, HowTo, Article) that engines can parse?

Pages that score high here give AI engines easy extraction points. Pages that bury answers in narrative paragraphs get skipped for competitors who don't.

2. Trust & Authority

Generative engines verify claims before including them in synthesized answers. Content without inline citations is content without credibility.

Checklist:

Inline citations — Are sources linked directly in the text, not just listed at the bottom? Format: [Source Name](URL).

Expert quotes — Do quotes include the person's full name and title? Anonymous quotes carry near-zero weight.

Source quality — Are you citing .edu, .gov, or recognized industry sources? A Georgia Tech study on GEO found that content with authoritative citations saw 40% higher visibility in AI-generated responses.

Link diversity — Do you have both internal links (establishing topical authority) and external links (establishing objectivity)?

3. Freshness

AI engines apply citation decay — the older your data, the less likely it gets cited. A 2024 statistic in a 2026 article is already suspect.

Checklist:

datePublished and dateModified — Are both present in your page metadata? Engines check these programmatically.

Data recency — Is every statistic from within the last 12 months? Replace or remove anything older.

Update cadence — For evergreen topics, are you updating quarterly at minimum?

According to Semrush's 2026 State of Content report, pages updated within 90 days receive 2.1x more AI citations than pages left unchanged for 6+ months.

4. Brand Integration

This is where most branded content fails the GEO test. AI engines are trained to detect promotional content and exclude it from objective answers.

The 15–25% rule: Your brand should appear in 15–25% of the content — enough to be included in AI responses, not enough to trigger the promotion filter.

Checklist:

Mention density — Is the brand name in 15–25% of content sections, not every paragraph?

Competitive context — Are competitors mentioned by name? Content that only mentions one brand signals advertising.

List placement — Does the brand appear within a list of options, not as the solo recommendation?

Fact-based claims only — Are all brand mentions tied to specific, verifiable capabilities? "Best in class" gets filtered. "Tracks citation rates across 4 AI engines" does not.

Platforms like Aeolo can automate brand density analysis, but the editorial judgment — where to place brand mentions for natural flow — still requires human review.

5. Semantic Authenticity

This is the category that overrides everything else. Even perfect scores in categories 1–4 fail if the content reads as inauthentic.

AI engines in 2026 evaluate content along multiple trust dimensions that go beyond traditional SEO signals. Think of it as an "AI smell test" — if the content feels like it was written to manipulate AI citations rather than inform readers, it gets flagged.

Checklist:

Positioning honesty — Is the content clearly labeled as branded, or is it disguised as an independent review? Engines detect the mismatch.

Product bias check — Does the content acknowledge limitations or tradeoffs? One-sided content signals advertising.

Independent expert voices — Are there quotes or references from people not affiliated with the brand?

Experience specificity — Does the content include specific implementation details, timelines, or results? Vague claims like "improves performance" carry no weight.

Testing methodology — If claims are made, is the testing approach described?

First-party data — Does the content include original research, surveys, or proprietary analysis?

Author E-E-A-T — Does the author have demonstrable expertise in the topic? Is there an author bio with credentials?

A Princeton/Georgia Tech research paper on generative engine optimization found that content perceived as authentic and experience-based was cited 2.4x more frequently than content with equivalent structure but generic, brand-heavy language.

6. Engine Fit

Each AI engine has different preferences. Content optimized for one may underperform on another.

Engine | Primary preference | Format tip
ChatGPT | Practical, step-by-step guidance | How-to structure, numbered lists
Gemini | Structured data, schema markup | Rich schema, clear hierarchies
Perplexity | Fresh sources, niche expertise | Recent citations, specialized depth
Grok | Real-time data, trending context | Current events tie-ins, social proof

Recommendation: Score your content against your primary target engine first, then adjust for secondary engines. Trying to optimize for all four equally produces generic content that none of them prefer.

Aeolo's visibility checks run queries across all four engines simultaneously, showing exactly where your content appears and where gaps exist — so you can prioritize engine-specific adjustments based on actual citation data rather than guesswork.

How to use this framework

Score before publishing — Run every draft through all six categories. A weak score in any single category can suppress citations across all engines.

Prioritize authenticity — If you only have time to fix one category, fix semantic authenticity. It's the multiplier that makes everything else work.

Re-score quarterly — Freshness decay is real. Content that scored well three months ago may be losing citations today.

Track results — Measure AI citation rates before and after applying the framework to quantify impact.

FAQ

What is a good overall score across all six categories?

There's no universal number — the framework is qualitative. The goal is zero failing categories. A single weak category (especially semantic authenticity or trust) can negate strengths everywhere else.

How often should I re-audit existing content?

Every 90 days at minimum. Freshness decay accelerates after 6 months, and competitor content improves continuously. Automated monitoring tools like Aeolo can flag citation drops between manual audits.

Does this framework replace SEO best practices?

No. GEO and SEO are complementary. Strong SEO (page speed, mobile-friendliness, keyword relevance) still matters for traditional search. This framework adds the layer needed for AI engine visibility.

Which category matters most for AI citations?

Semantic authenticity is the strongest single predictor. Structure and trust are prerequisites — without them, engines can't extract or verify your content. But authenticity is the signal that determines whether extracted content actually gets cited.

Aeolo scores your content across all four major AI engines and identifies exactly where citations are being won or lost. Request beta access to run your first visibility audit.