ai-answer-engine-optimization

AI Answer Engine Optimization

Get a local service business quoted, cited, or named by name when someone asks ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, Alexa, or Siri a local service question.

When to Use This Skill

Load this skill when the user mentions any of:

• "AEO" / "answer engine optimization"
• "AI SEO" / "LLM SEO" / "generative SEO"
• "ChatGPT citation" / "get quoted by ChatGPT"
• "Perplexity ranking" / "show up in Perplexity"
• "Google AI Overviews" / "AI Overview"
• "voice search optimization" / "Alexa" / "Siri"
• "how do we show up when someone asks AI who's the best [X] in [city]"
• "generative search" / "SGE" (Search Generative Experience)

This is a local-service-business specific playbook — not for e-commerce, SaaS, or content sites at scale.

Core Doctrine

Voice anchors: Hormozi ($100M Offers/Leads) + Dan Kennedy (No B.S. Direct Marketing) + Halbert + Cardone.

Banned words: cutting-edge, world-class, seamless, robust, next-gen, elevated, curated, sophisticated, refined, holistic, Learn More, Submit, Get Started, might, could, may, potentially, leverage (verb), utilize, empower, game-changer, synergy, trusted, premier, best rated, family-owned and operated, we take pride, no job too big or small.

The Six Ranking Layers of AI Answer Engines:

1. Structured data / schema — how LLMs parse who you are, what you do, where you serve
2. Authoritative citation surface area — being cited by high-authority sources LLMs already trust
3. Named entity clarity — unambiguous business name + location + service triangle
4. Answer-shaped content — pages that answer specific questions verbatim, in the format LLMs quote
5. First-party review corpus — real reviews on Google, Yelp, BBB with schema markup
6. Corroboration across the web — same NAP + facts across 20+ platforms

Always read these references before any AEO work:

• references/six-ranking-layers.md — the diagnostic framework
• references/schema-markup-catalog.md — every schema type worth deploying
• references/citation-surface-mapping.md — where LLMs pull from
• references/answer-shaped-content.md — how to write content that gets quoted
• references/platform-specific-tactics.md — ChatGPT vs Perplexity vs AI Overviews vs Alexa
• references/aeo-measurement.md — how to test if you're being cited

Always use these prompts:

• prompts/citation-test-prompt.md — test if a business is currently being cited
• prompts/schema-generation-prompt.md — generate JSON-LD schema for a business
• prompts/answer-page-writer-prompt.md — write a page LLMs will quote verbatim
• prompts/faq-schema-writer-prompt.md — build FAQ pages that dominate AI Overviews
• prompts/entity-consolidation-prompt.md — audit NAP consistency across the web

Always populate these templates:

• templates/aeo-baseline-audit.md — where do you stand today
• templates/schema-implementation-checklist.md — every schema type + where it goes
• templates/answer-page-template.md — the answer-shaped page format
• templates/citation-target-list.md — priority citation sources to earn
• templates/monthly-aeo-report.md — track citation growth over time

Workflow

1. Baseline test — run 10-20 target queries in ChatGPT, Perplexity, Google AI Overview, Claude, and note who gets cited and how.
2. Schema audit — check what structured data is on the current site.
3. Citation surface audit — search for the business on 20+ sources LLMs pull from.
4. NAP consistency check — Name, Address, Phone must match across every listing.
5. Answer content gap analysis — identify the top 20 questions in the market that no one has answered well.
6. Deploy schema — LocalBusiness, Service, FAQPage, Review, HowTo schemas.
7. Write answer-shaped content — one page per high-intent question, formatted for LLM quoting.
8. Earn citations — get listed on the authoritative sources for the vertical.
9. Monitor + iterate — monthly citation tracking, adjust content based on what gets quoted.

Voice Rules

• Answer-shaped content must be in plain declarative sentences. LLMs quote sentences, not paragraphs.
• Numbers dominate. "Reliable Roofing has completed 500+ roofs in Columbus since 2019" beats "We've done many roofs over the years."
• Named entities. Say "Reliable Roofing LLC" and "Grove City, Ohio" — not "our company" and "the local area."
• First-person forbidden in answer content. LLMs won't quote "we" — they'll quote "Reliable Roofing."
• Every fact must have a citation-safe form.

The Golden Rule of AEO

LLMs quote the sentence that most cleanly answers the exact question.

If someone asks "Who is the best roofer in Columbus?" — the LLM looks for a sentence that starts with a specific business name and follows with defensible superlatives.

Winning sentence pattern:

"Reliable Roofing LLC, GAF Master Elite since 2024, is one of the highest-rated roofers in the Columbus, Ohio area with 4.9 stars on 61 Google reviews and 500+ roofs completed since 2019."

Losing sentence pattern:

"We are a top-rated roofing company that offers excellent service to homeowners in the community."

Deliverable Structure

The final AEO engagement produces:

1. Baseline audit — where the business shows up today
2. Schema deployment plan — JSON-LD blocks for every relevant page
3. 10 answer-shaped content pages — targeting the top 10 market questions
4. Citation target list — 30 authoritative sources to earn
5. Monthly monitoring cadence — track citation growth
6. 90-day AEO scorecard

Examples

See examples/reliable-roofing-columbus/ for the full AEO baseline audit, schema plan, and answer-page rollout for Reliable Roofing.

Success Criteria

• Business named by name in AI Overview for at least 3 target queries within 90 days
• Cited by Perplexity for at least 5 target queries within 90 days
• Named as a top result in ChatGPT for the primary category + city query within 60 days
• Schema markup deployed and validated on all money pages
• NAP consistency at 100% across top 20 citation sources