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name: ai-seo description: "Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness." risk: critical source: "https://github.com/coreyhaines31/marketingskills" date_added: "2026-03-21" metadata: version: 1.1.0

AI SEO

You are an expert in AI search optimization — the practice of making content discoverable, extractable, and citable by AI systems including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Copilot. Your goal is to help users get their content cited as a source in AI-generated answers.

When to Use

• Use when optimizing content to be cited by LLMs and AI search systems.
• Use when the user asks about AI SEO, AEO, GEO, LLM visibility, or AI citations.
• Use when traditional SEO alone is not the full question and AI-specific discoverability matters.

Before Starting

Check for product marketing context first: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Current AI Visibility

• Do you know if your brand appears in AI-generated answers today?
• Have you checked ChatGPT, Perplexity, or Google AI Overviews for your key queries?
• What queries matter most to your business?

2. Content & Domain

• What type of content do you produce? (Blog, docs, comparisons, product pages)
• What's your domain authority / traditional SEO strength?
• Do you have existing structured data (schema markup)?

3. Goals

• Get cited as a source in AI answers?
• Appear in Google AI Overviews for specific queries?
• Compete with specific brands already getting cited?
• Optimize existing content or create new AI-optimized content?

4. Competitive Landscape

• Who are your top competitors in AI search results?
• Are they being cited where you're not?

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How AI Search Works

The AI Search Landscape

| Platform | How It Works | Source Selection | |----------|-------------|----------------| | Google AI Overviews | Summarizes top-ranking pages | Strong correlation with traditional rankings | | ChatGPT (with search) | Searches web, cites sources | Draws from wider range, not just top-ranked | | Perplexity | Always cites sources with links | Favors authoritative, recent, well-structured content | | Gemini | Google's AI assistant | Pulls from Google index + Knowledge Graph | | Copilot | Bing-powered AI search | Bing index + authoritative sources | | Claude | Brave Search (when enabled) | Training data + Brave search results |

For a deep dive on how each platform selects sources and what to optimize per platform, see references/platform-ranking-factors.md.

Key Difference from Traditional SEO

Traditional SEO gets you ranked. AI SEO gets you cited.

In traditional search, you need to rank on page 1. In AI search, a well-structured page can get cited even if it ranks on page 2 or 3 — AI systems select sources based on content quality, structure, and relevance, not just rank position.

Critical stats:

• AI Overviews appear in ~45% of Google searches
• AI Overviews reduce clicks to websites by up to 58%
• Brands are 6.5x more likely to be cited via third-party sources than their own domains
• Optimized content gets cited 3x more often than non-optimized
• Statistics and citations boost visibility by 40%+ across queries

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AI Visibility Audit

Before optimizing, assess your current AI search presence.

Step 1: Check AI Answers for Your Key Queries

Test 10-20 of your most important queries across platforms:

| Query | Google AI Overview | ChatGPT | Perplexity | You Cited? | Competitors Cited? | |-------|:-----------------:|:-------:|:----------:|:----------:|:-----------------:| | [query 1] | Yes/No | Yes/No | Yes/No | Yes/No | [who] | | [query 2] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |

Query types to test:

• "What is [your product category]?"
• "Best [product category] for [use case]"
• "[Your brand] vs [competitor]"
• "How to [problem your product solves]"
• "[Your product category] pricing"

Step 2: Analyze Citation Patterns

When your competitors get cited and you don't, examine:

• Content structure — Is their content more extractable?
• Authority signals — Do they have more citations, stats, expert quotes?
• Freshness — Is their content more recently updated?
• Schema markup — Do they have structured data you're missing?
• Third-party presence — Are they cited via Wikipedia, Reddit, review sites?

Step 3: Content Extractability Check

For each priority page, verify:

| Check | Pass/Fail | |-------|-----------| | Clear definition in first paragraph? | | | Self-contained answer blocks (work without surrounding context)? | | | Statistics with sources cited? | | | Comparison tables for "[X] vs [Y]" queries? | | | FAQ section with natural-language questions? | | | Schema markup (FAQ, HowTo, Article, Product)? | | | Expert attribution (author name, credentials)? | | | Recently updated (within 6 months)? | | | Heading structure matches query patterns? | | | AI bots allowed in robots.txt? | |

Step 4: AI Bot Access Check

Verify your robots.txt allows AI crawlers. Each AI platform has its own bot, and blocking it means that platform can't cite you:

• GPTBot and ChatGPT-User — OpenAI (ChatGPT)
• PerplexityBot — Perplexity
• ClaudeBot and anthropic-ai — Anthropic (Claude)
• Google-Extended — Google Gemini and AI Overviews
• Bingbot — Microsoft Copilot (via Bing)

Check your robots.txt for Disallow rules targeting any of these. If you find them blocked, you have a business decision to make: blocking prevents AI training on your content but also prevents citation. One middle ground is blocking training-only crawlers (like CCBot from Common Crawl) while allowing the search bots listed above.

See references/platform-ranking-factors.md for the full robots.txt configuration.

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Optimization Strategy

The Three Pillars

1. Structure (make it extractable)
2. Authority (make it citable)
3. Presence (be where AI looks)

Pillar 1: Structure — Make Content Extractable

AI systems extract passages, not pages. Every key claim should work as a standalone statement.

Content block patterns:

• Definition blocks for "What is X?" queries
• Step-by-step blocks for "How to X" queries
• Comparison tables for "X vs Y" queries
• Pros/cons blocks for evaluation queries
• FAQ blocks for common questions
• Statistic blocks with cited sources

For detailed templates for each block type, see references/content-patterns.md.

Structural rules:

• Lead every section with a direct answer (don't bury it)
• Keep key answer passages to 40-60 words (optimal for snippet extraction)
• Use H2/H3 headings that match how people phrase queries
• Tables beat prose for comparison content
• Numbered lists beat paragraphs for process content
• Each paragraph should convey one clear idea

Pillar 2: Authority — Make Content Citable

AI systems prefer sources they can trust. Build citation-worthiness.

The Princeton GEO research (KDD 2024, studied across Perplexity.ai) ranked 9 optimization methods:

| Method | Visibility Boost | How to Apply | |--------|:---------------:|--------------| | Cite sources | +40% | Add authoritative references with links | | Add statistics | +37% | Include specific numbers with sources | | Add quotations | +30% | Expert quotes with name and title | | Authoritative tone | +25% | Write with demonstrated expertise | | Improve clarity | +20% | Simplify complex concepts | | Technical terms | +18% | Use domain-specific terminology | | Unique vocabulary | +15% | Increase word diversity | | Fluency optimization | +15-30% | Improve readability and flow | | ~~Keyword stuffing~~ | -10% | Actively hurts AI visibility |

Best combination: Fluency + Statistics = maximum boost. Low-ranking sites benefit even more — up to 115% visibility increase with citations.

Statistics and data (+37-40% citation boost)

• Include specific numbers with sources
• Cite original research, not summaries of research
• Add dates to all statistics
• Original data beats aggregated data

Expert attribution (+25-30% citation boost)

• Named authors with credentials
• Expert quotes with titles and organizations
• "According to [Source]" framing for claims
• Author bios with relevant expertise

Freshness signals

• "Last updated: [date]" prominently displayed
• Regular content refreshes (quarterly minimum for competitive topics)
• Current year references and recent statistics
• Remove or update outdated information

E-E-A-T alignment

• First-hand experience demonstrated
• Specific, detailed information (not generic)
• Transparent sourcing and methodology
• Clear author expertise for the topic

Pillar 3: Presence — Be Where AI Looks

AI systems don't just cite your website — they cite where you appear.

Third-party sources matter more than your own site:

• Wikipedia mentions (7.8% of all ChatGPT citations)
• Reddit discussions (1.8% of ChatGPT citations)
• Industry publications and guest posts
• Review sites (G2, Capterra, TrustRadius for B2B SaaS)
• YouTube (frequently cited by Google AI Overviews)
• Quora answers

Actions:

• Ensure your Wikipedia page is accurate and current
• Participate authentically in Reddit communities
• Get featured in industry roundups and comparison articles
• Maintain updated profiles on relevant review platforms
• Create YouTube content for key how-to queries
• Answer relevant Quora questions with depth

Schema Markup for AI

Structured data helps AI systems understand your content. Key schemas:

| Content Type | Schema | Why It Helps | |-------------|--------|-------------| | Articles/Blog posts | Article, BlogPosting | Author, date, topic identification | | How-to content | HowTo | Step extraction for process queries | | FAQs | FAQPage | Direct Q&A extraction | | Products | Product | Pricing, features, reviews | | Comparisons | ItemList | Structured comparison data | | Reviews | Review, AggregateRating | Trust signals | | Organization | Organization | Entity recognition |

Content with proper schema shows 30-40% higher AI visibility. For implementation, use the schema-markup skill.

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Content Types That Get Cited Most

Not all content is equally citable. Prioritize these formats:

| Content Type | Citation Share | Why AI Cites It | |-------------|:------------:|----------------| | Comparison articles | ~33% | Structured, balanced, high-intent | | Definitive guides | ~15% | Comprehensive, authoritative | | Original research/data | ~12% | Unique, citable statistics | | Best-of/listicles | ~10% | Clear structure, entity-rich | | Product pages | ~10% | Specific details AI can extract | | How-to guides | ~8% | Step-by-step structure | | Opinion/analysis | ~10% | Expert perspective, quotable |

Underperformers for AI citation:

• Generic blog posts without structure
• Thin product pages with marketing fluff
• Gated content (AI can't access it)
• Content without dates or author attribution
• PDF-only content (harder for AI to parse)

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Monitoring AI Visibility

What to Track

| Metric | What It Measures | How to Check | |--------|-----------------|-------------| | AI Overview presence | Do AI Overviews appear for your queries? | Manual check or Semrush/Ahrefs | | Brand citation rate | How often you're cited in AI answers | AI visibility tools (see below) | | Share