iblai-marketing-ai-seo

name	iblai-marketing-ai-seo
description	When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see iblai-marketing-seo-audit. For structured data implementation, see iblai-marketing-schema-markup.
globs	null
alwaysApply	false
metadata	{"version":"1.2.0"}

/iblai-marketing-ai-seo

Make content discoverable, extractable, and citable by AI search systems — Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, Copilot. The goal is to get cited as a source in AI-generated answers.

Step 0: Context Check

Read .agents/product-marketing-context.md (or .claude/product-marketing-context.md on older setups) first. Only ask for what isn't there.

Pull this context:

1. Current AI Visibility

• Does your brand appear in AI-generated answers today?
• Have you checked ChatGPT, Perplexity, or Google AI Overviews for key queries?
• Which queries matter most to the business?

2. Content & Domain

• Content types you produce (blog, docs, comparisons, product pages)
• Domain authority / traditional SEO strength
• Existing structured data (schema markup)?

3. Goals

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

4. Competitive Landscape

• Top competitors in AI search results
• Are they cited where you're not?

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How AI Search Works

The 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

Per-platform deep dive on ranking factors: references/platform-ranking-factors.md.

The Key Difference From Traditional SEO

Traditional SEO ranks you. AI SEO gets you cited.

In traditional search you need page 1. In AI search a well-structured page on page 2 or 3 can still get cited — AI systems pick sources by 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

Audit current presence before optimizing.

Step 1: Check AI Answers for 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: Citation Pattern Analysis

When competitors get cited and you don't, look at:

• Content structure — more extractable than yours?
• Authority signals — more citations, stats, expert quotes?
• Freshness — more recently updated?
• Schema markup — structured data you're missing?
• Third-party presence — cited via Wikipedia, Reddit, review sites?

Step 3: Extractability Check

Per priority page:

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

Each AI platform has its own crawler. Block it and 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)

Audit your robots.txt for Disallow rules targeting these. If they're blocked, you have a business choice: blocking prevents training but also prevents citation. A middle ground is blocking training-only crawlers (like CCBot from Common Crawl) while allowing the search bots above.

Full robots.txt configuration: references/platform-ranking-factors.md.

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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 It Extractable

AI systems extract passages, not pages. Every key claim must work standalone.

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

Block templates: references/content-patterns.md.

Structural rules:

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

Pillar 2: Authority — Make It Citable

AI systems prefer sources they trust.

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 gain even more — up to 115% visibility lift with citations.

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

• Specific numbers with sources
• Cite original research, not summaries of research
• Date every statistic
• 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]" displayed prominently
• Regular refreshes (quarterly minimum for competitive topics)
• Current year references and recent statistics
• Remove or update stale info

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 doesn't only cite your website — it cites 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:

• Keep your Wikipedia page 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

Machine-Readable Files for AI Agents

AI agents aren't just answering — they're becoming buyers. When an agent evaluates tools on behalf of a user, it needs structured, parseable info. If pricing is locked in a JS-rendered page or behind a "contact sales" wall, agents skip you and recommend competitors they can actually parse.

Add these files at site root:

/pricing.md or /pricing.txt — Structured pricing for AI agents

# Pricing — [Your Product Name]

## Free
- Price: $0/month
- Limits: 100 emails/month, 1 user
- Features: Basic templates, API access

## Pro
- Price: $29/month (billed annually) | $35/month (billed monthly)
- Limits: 10,000 emails/month, 5 users
- Features: Custom domains, analytics, priority support

## Enterprise
- Price: Custom — contact [e-mail]
- Limits: Unlimited emails, unlimited users
- Features: SSO, SLA, dedicated account manager

Why this matters:

• AI agents increasingly compare products programmatically before a human visits
• Opaque pricing gets filtered out of AI-mediated buying journeys
• A markdown file is trivially parseable by any LLM — no rendering, no JS, no login walls
• Same principle as robots.txt (for crawlers), llms.txt (for AI context), AGENTS.md (for agent capabilities)

Rules:

• Consistent units (monthly vs. annual, per-seat vs. flat)
• Specific limits and thresholds, not just feature names
• List what's included at each tier, not just deltas
• Keep it updated — stale pricing is worse than no file
• Link from your sitemap and main pricing page

/llms.txt — Context file for AI systems (see llmstxt.org)

If you don't have one, add an llms.txt that gives AI systems a quick overview of what your product does, who it's for, and links to key pages (including pricing).

Schema Markup for AI

Structured data helps AI 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 gets 30-40% higher AI visibility. Implementation: use the iblai-marketing-schema-markup skill.

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Content Types That Get Cited Most

Not all content is equally citable. Prioritize:

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 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 of AI voice	Your citations vs. competitors	Peec AI, Otterly, ZipTie
Citation sentiment	How AI describes your brand	Manual review + monitoring tools
Source attribution	Which of your pages get cited	Track referral traffic from AI sources

Visibility Monitoring Tools

Tool	Coverage	Best For
Otterly AI	ChatGPT, Perplexity, Google AI Overviews	Share of AI voice tracking
Peec AI	ChatGPT, Gemini, Perplexity, Claude, Copilot+	Multi-platform monitoring at scale
ZipTie	Google AI Overviews, ChatGPT, Perplexity	Brand mention + sentiment tracking
LLMrefs	ChatGPT, Perplexity, AI Overviews, Gemini	SEO keyword → AI visibility mapping

DIY Monitoring

Monthly manual check:

1. Pick your top 20 queries
2. Run each through ChatGPT, Perplexity, and Google
3. Record: Are you cited? Who is? What page?
4. Log to a spreadsheet, track month over month

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AI SEO by Content Type

SaaS Product Pages

Goal: Get cited for "What is [category]?" and "Best [category]" queries.

Optimize:

• Clear product description in first paragraph (what it does, who it's for)
• Feature comparison tables (you vs. category, not just competitors)
• Specific metrics ("processes 10,000 transactions/sec," not "blazing fast")
• Customer count or social proof with numbers
• Visible pricing (AI cites pages with visible pricing). Add a /pricing.md so AI agents can parse plans without rendering your page (see "Machine-Readable Files" above)
• FAQ section covering common buyer questions

Blog Content

Goal: Get cited as an authoritative source on topics in your space.

Optimize:

• One clear target query per post (match heading to query)
• Definition in first paragraph for "What is" queries
• Original data, research, or expert quotes
• "Last updated" date visible
• Author bio with relevant credentials
• Internal links to related product/feature pages

Comparison / Alternative Pages

Goal: Get cited for "[X] vs [Y]" and "Best [X] alternatives" queries.

Optimize:

• Structured comparison tables (not just prose)
• Fair and balanced — AI penalizes obvious bias
• Specific criteria with ratings or scores
• Up-to-date pricing and feature data
• Build these with /iblai-marketing-competitor-alternatives

Documentation / Help Content

Goal: Get cited for "How to [X] with [your product]" queries.

Optimize:

• Step-by-step format with numbered lists
• Code examples where relevant
• HowTo schema markup
• Screenshots with descriptive alt text
• Clear prerequisites and expected outcomes

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Common Mistakes

• Ignoring AI search entirely — ~45% of Google searches now show AI Overviews; ChatGPT/Perplexity are growing fast
• Treating AI SEO as separate from SEO — Good traditional SEO is the foundation; AI SEO layers structure and authority on top
• Writing for AI, not humans — If content reads like algorithm-gaming, it won't get cited or convert
• No freshness signals — Undated content loses to dated content; AI weights recency heavily
• Gating everything — AI can't access gated content. Keep your most authoritative pages open
• Ignoring third-party presence — You may get more citations from a Wikipedia mention than from your own blog
• No structured data — Schema markup gives AI explicit context about your content
• Keyword stuffing — Unlike traditional SEO where it's just ineffective, stuffing actively reduces AI visibility by 10% (Princeton GEO study)
• Hiding pricing behind "contact sales" or JS-rendered pages — AI agents evaluating you on behalf of buyers can't parse what they can't read. Add /pricing.md
• Blocking AI bots — If GPTBot, PerplexityBot, or ClaudeBot are blocked in robots.txt, those platforms can't cite you
• Generic content without data — "We're the best" won't get cited. "Our customers see 3x improvement in [metric]" will
• Forgetting to monitor — Check AI visibility at least monthly

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Tool Integrations

See the tools registry.

Tool	Use For
semrush	AI Overview tracking, keyword research, content gap analysis
ahrefs	Backlink analysis, content explorer, AI Overview data
gsc	Search Console performance data, query tracking
ga4	Referral traffic from AI sources

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Task-Specific Questions

1. What are your top 10-20 most important queries?
2. Have you checked if AI answers exist for those queries today?
3. Do you have structured data (schema markup) on your site?
4. What content types do you publish? (Blog, docs, comparisons, etc.)
5. Are competitors being cited where you're not?
6. Do you have a Wikipedia page or presence on review sites?

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Related Skills

• iblai-marketing-seo-audit: For traditional technical and on-page SEO audits
• iblai-marketing-schema-markup: For implementing structured data
• iblai-marketing-content-strategy: For planning what content to create
• iblai-marketing-competitor-alternatives: For building comparison pages that get cited
• iblai-marketing-programmatic-seo: For SEO pages at scale
• iblai-marketing-copywriting: For writing content that's both human-readable and AI-extractable