AEO/GEO Optimizer

Optimize content and websites for AI-powered search experiences — ChatGPT, Perplexity, Claude, Google AI Overviews, and Bing Copilot.

Install

git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/aeo-geo-optimizer ~/.claude/skills/

Why This Matters

Traditional SEO optimizes for 10 blue links. AEO/GEO optimizes for AI-generated answers. When someone asks ChatGPT or Perplexity a question, the answer synthesizes from sources — and those sources get cited, linked, and trusted. If your content is not structured for AI consumption, you are invisible in the fastest-growing search channel.

Core Concepts

AEO vs GEO vs Traditional SEO

Dimension	Traditional SEO	AEO (Answer Engine)	GEO (Generative Engine)
Target	Google/Bing SERPs	Featured snippets, AI Overviews, voice assistants	ChatGPT, Perplexity, Claude citations
Goal	Rank on page 1	Be THE answer	Be cited in AI-generated responses
Content format	Long-form, keyword-rich	Concise, structured Q&A	Authoritative, quotable, fact-dense
Signals	Backlinks, keywords, UX	Schema markup, direct answers, authority	E-E-A-T, data density, citation-worthiness
Measurement	Rankings, traffic	Answer box appearance, voice search hits	AI citation tracking, brand mentions in AI

The Citation Hierarchy

AI models prioritize sources based on:

1. Authority signals — Domain authority, author expertise, institutional backing
2. Content structure — Clear headings, direct answers, structured data
3. Freshness — Recent publication dates, updated statistics
4. Specificity — Exact numbers, named sources, verifiable claims
5. Uniqueness — Original research, proprietary data, novel frameworks

AEO/GEO Audit Workflow

Step 1: Assess Current AI Visibility

1. Test AI citation presence: Query ChatGPT, Perplexity, and Google AI Overviews with questions your content should answer. Document which queries cite your content vs competitors.

2. Check structured data: Validate schema markup coverage using Google Rich Results Test or Schema.org validator.

3. Evaluate content structure: Score each page on AEO readiness using the Content Scorecard below.

Step 2: Content Scorecard

Rate each piece of content (1-5) on these dimensions:

Dimension	Score 1 (Poor)	Score 5 (Excellent)
Direct answers	Buried in paragraphs	Clear Q&A format, first-sentence answers
Data density	Opinions without evidence	Specific numbers, percentages, dates
Source attribution	No citations	Named sources, linked studies
Structure	Wall of text	H2/H3 hierarchy, lists, tables
Schema markup	None	Article, FAQ, HowTo, or relevant type
Freshness signals	No dates	Published date, "Updated" date, recent data
Author authority	No byline	Named author with expertise credentials
Quotability	Meandering prose	Crisp, self-contained statements AI can extract

Scoring: 32-40 = AI-ready. 24-31 = Needs optimization. Below 24 = Major rework needed.

Step 3: Optimize for AI Citation

Content Structure Patterns

The Direct Answer Pattern:

## [Question as H2]

[One-sentence direct answer.] [Supporting context in 2-3 sentences.]

**Key details:**
- [Specific data point]
- [Specific data point]
- [Source attribution]

The Definition Pattern:

## What Is [Term]?

[Term] is [clear, concise definition in one sentence]. [Elaboration with context.] [How it differs from related concepts.]

The Comparison Pattern:

## [X] vs [Y]: Key Differences

| Dimension | [X] | [Y] |
|-----------|-----|-----|
| [Aspect 1] | [Specific detail] | [Specific detail] |
| [Aspect 2] | [Specific detail] | [Specific detail] |

**Bottom line:** [One-sentence recommendation with reasoning.]

The Statistics Pattern:

## [Topic] Statistics ([Year])

- **[Stat 1]**: [Number] ([Source, Year])
- **[Stat 2]**: [Number] ([Source, Year])
- **[Stat 3]**: [Number] ([Source, Year])

*Sources: [List with links]*

Writing for AI Extraction

1. Lead with the answer. AI models extract the first sentence after a heading. Make it count.
2. Use specific numbers. "Revenue increased 47% year-over-year" beats "revenue increased significantly."
3. Name your sources. "According to a 2026 McKinsey report" is citable; unsourced claims are not.
4. Create self-contained paragraphs. Each paragraph should make sense extracted in isolation.
5. Use comparison tables. AI models love structured comparisons — they are easy to synthesize.
6. Include "What is" and "How to" headings. These directly match common AI queries.
7. Add freshness signals. Include publication date, last-updated date, and date-stamp your statistics.
8. Write quotable sentences. Crisp, declarative statements that AI can extract verbatim.

Technical Optimization

1. Schema markup — See the schema-markup-generator skill for implementation
2. Canonical URLs — Ensure AI models find the authoritative version
3. XML sitemap — Keep it current so AI crawlers find new content
4. Page speed — AI crawlers respect crawl budgets; fast sites get crawled more
5. robots.txt — Ensure AI crawlers (GPTBot, anthropic-ai, PerplexityBot) are not blocked

Step 4: Monitor AI Visibility

AI Crawler User Agents

Crawler	User Agent	Purpose
OpenAI	GPTBot	ChatGPT training and browsing
Anthropic	anthropic-ai, ClaudeBot	Claude training and citations
Perplexity	PerplexityBot	Perplexity search citations
Google	Google-Extended	Gemini/AI Overview training
Microsoft	Bingbot (+ AI signals)	Bing Copilot citations
Meta	Meta-ExternalAgent	Meta AI features
Apple	Applebot-Extended	Apple Intelligence

robots.txt Recommendations

# Allow AI crawlers for maximum AI search visibility
User-agent: GPTBot
Allow: /

User-agent: anthropic-ai
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: Google-Extended
Allow: /

Decision framework: If your goal is AI visibility (AEO/GEO), allow all AI crawlers. If you have licensing concerns about training data, selectively block training-only crawlers while allowing search/citation crawlers.

Measurement Approaches

Method	What It Tracks	Tools
Manual citation checks	Query AI platforms, document citations	ChatGPT, Perplexity, Google
Server log analysis	AI crawler frequency and pages crawled	Log analyzers, custom scripts
Brand mention monitoring	Your brand/content mentioned in AI answers	Manual checks, brand monitoring tools
Referral traffic	Traffic from AI platforms	GA4 (check referral sources for chat.openai.com, perplexity.ai)
Schema validation	Structured data coverage and errors	Google Search Console, Rich Results Test

Content Types and AI Optimization

Blog Posts / Articles

• Add FAQ schema for common questions
• Structure with clear H2 question headings
• Include "Key Takeaways" or "TL;DR" section
• Date-stamp all statistics

Product / Service Pages

• Add Product or Service schema
• Include comparison tables vs alternatives
• Answer "What is [product]?" in first paragraph
• List specific features with quantified benefits

Documentation / How-To Content

• Add HowTo schema with explicit steps
• Number every step
• Include time estimates and difficulty level
• Add "Prerequisites" and "Common Mistakes" sections

Research / Data Content

• Add Dataset schema where applicable
• Lead with key findings before methodology
• Create a "Key Statistics" summary section
• Cite sample sizes, date ranges, and confidence levels

Anti-Patterns (Never Do)

1. Do not block AI crawlers if your goal is AI visibility
2. Do not write "click here" or "read more below" — AI extracts content out of context
3. Do not bury answers in long introductions — lead with the answer
4. Do not use vague qualifiers — "many," "significant," "some" — use specific numbers
5. Do not neglect author bylines — E-E-A-T signals matter to AI models
6. Do not duplicate content across pages — AI models deduplicate and may ignore both
7. Do not over-optimize for one AI platform — optimize for all of them
8. Do not forget internal linking — AI crawlers follow links to build topical authority maps

Integration with Other Skills

• technical-seo-audit — Run technical audit first, then layer AEO/GEO optimization
• schema-markup-generator — Generate the structured data this skill recommends
• seo-content-writer — Apply AEO writing patterns during content creation
• content-creator — Use brand voice analysis to maintain voice while optimizing for AI