marketing-ai-search-optimization
AI Search & Answer Engine Optimization (GEO)
Improve how assistants retrieve, summarize, and cite your pages.
For traditional SEO: Use marketing-seo-complete instead.
GEO vs SEO (Overlap Map)
Use this to prevent “GEO-only” work that ignores discoverability and conversion.
GEO is best at
- Making pages easier for assistants to extract, summarize, and cite
- Building entity/proof structures that improve citation probability
- Measuring assistant visibility via query banks and citation share
SEO is still required for
- Getting pages discovered and indexed reliably (crawlability, internal linking, canonicalization)
- Capturing demand in classic search surfaces (SERPs, video, local, forums)
- Avoiding regressions from technical changes (rendering, performance, duplication)
Default operating rule
- Keep classic SEO and conversion work running; treat GEO as a structured overlay on top of high-intent pages.
GEO Monitoring vs GEO Optimization
This skill covers optimization — improving your content so AI platforms cite you more often.
For monitoring infrastructure — building the systems that track whether AI platforms cite you — see project-aeo-monitoring-tools.
Typical workflow: Monitor (track current visibility) -> Optimize (improve content) -> Measure (verify improvement)
| Activity | This skill | project-aeo-monitoring-tools |
|---|---|---|
| Content structure for citation | Yes | — |
| Entity and proof optimization | Yes | — |
| Query bank construction | Quick guidance | Full methodology |
| API orchestration and pipelines | — | Yes |
| Citation extraction and analysis | — | Yes |
| Share of Model dashboard | Concept | Implementation |
| Bot analytics and crawl tracking | — | Yes |
| Cost estimation and transparency | — | Yes |
Quick start (30–60 min)
- Build a query bank (30–100 queries for quick start; scale to 250–500 for advanced monitoring): problems, comparisons, "best", "vs", integrations, and pricing questions.
- Confirm assistants can fetch content (robots/WAF/SSR): use
assets/audits/crawler-access-audit.md. - Run a baseline visibility audit: use
assets/audits/search-visibility-audit.mdandassets/audits/ai-search-content-audit.md. - Ship one high-leverage page update: use
assets/content/ai-search-content-brief.md+assets/content/answer-focused-article-template.md. - Set up measurement + retest cadence: use
references/measurement-analytics.mdandassets/testing/ai-search-testing-protocol.md.
Core workflow
1) Decide scope (avoid wasted work)
- Confirm discovery channel: check whether your ICP uses assistants for research and comparisons.
- Pick one primary platform first (Google AI Overviews vs ChatGPT vs Perplexity) based on your audience.
- Treat GEO as additive: keep classic SEO and conversion work running.
2) Ensure assistants can access your content
- Allow/deny crawlers explicitly: use
references/ai-crawler-technical-setup.mdandassets/technical/robots-txt-ai-crawlers.md. - Reduce JS dependency for critical copy (SSR/SSG): use
assets/technical/server-side-rendering-guide.md. - Add
llms.txtwhen useful as a navigation map (not a guarantee): useassets/technical/llms-txt-template.md. - Review emerging
.well-known/AI discovery standards (llmprofiles.json,mcp.json,agents.json): useassets/technical/well-known-ai-discovery.md.
3) Make pages easy to extract and cite
- Put a direct, quotable answer block in the first screenful (then expand with proof).
- Use stable entities (product, category, competitors, integrations): use
references/entity-semantic-optimization.md. - Use repeatable content structures for questions, comparisons, and "best for": use
references/content-structure-patterns.md.
Implementation reference: The AEO monitoring platform's recommendation engine (
src/lib/recommendations/engine.ts) automates gap analysis against these patterns. The optimization dashboard (src/app/optimize/page.tsx) surfaces actionable recommendations. Seeproject-aeo-monitoring-toolsfor the full implementation.
- Create/refresh high-intent pages first (alternatives, integrations, pricing, security, implementation): use
assets/strategy/ai-search-growth-plan.md.
4) Build off-site entity presence and earned citations
- Get your brand into third-party sources AI trusts (G2, Reddit, Wikipedia, YouTube, industry listicles): use
references/earned-aeo-third-party-citations.md. - Strengthen Knowledge Graph presence (Wikidata, Google Business Profile,
sameAslinking): see Knowledge Graph section inreferences/entity-semantic-optimization.md. - Create multimodal content (video, transcripts, audio) for AI platforms that cite non-text sources: use
references/multimodal-content-optimization.md. - For e-commerce: implement Google UCP for agentic shopping visibility: use
references/commerce-protocol-ucp.md.
5) Add proof and trust hooks (citation fuel)
- Prefer primary sources and verifiable numbers; attribute claims clearly.
- Show authorship, review, and freshness (
dateModified/ "Last updated") where appropriate. - Avoid "LLM bait": prioritize user value and factual accuracy.
6) Measure, iterate, and defend against regressions
- Track "share of model" / citation share using your query bank, not vanity rankings. For automated tracking, see project-aeo-monitoring-tools (custom infrastructure) or commercial alternatives in
references/llm-tracking-tools.md. - Re-test after shipping changes; keep snapshots of answers and citations.
- Separate SEO wins vs assistant visibility wins; avoid false attribution.
Implementation Examples
Query Bank Construction
Quick start (30-100 queries):
Problems: "how to [solve X]", "why does [Y happen]"
Comparisons: "[product] vs [competitor]", "best [category] for [use case]"
Integrations: "[product] [integration] setup", "does [product] work with [tool]"
Pricing: "[product] pricing", "[product] free plan"
Advanced (250-500 queries): Expand with persona variants, regional variations, long-tail variations, and seasonal queries. See project-aeo-monitoring-tools for full query bank methodology.
Content Structure Patterns
Apply these patterns to high-intent pages:
Comparison page:
H1: [Product A] vs [Product B]: [Year] Guide
TL;DR: 2-3 sentence verdict
Table: Feature comparison
Sections: Use cases, pricing, verdict
Alternatives page:
H1: Best [Product] Alternatives in [Year]
TL;DR: Top 3 picks with one-line reasons
Table: Feature + pricing matrix
Sections: Detailed review per alternative
Integration page:
H1: How to Connect [Product] with [Tool]
Steps: Numbered setup guide
Code: Configuration examples
FAQ: Common issues
Entity Optimization
Structure your brand entity for AI recognition:
Brand Kit (maintain centrally):
- Official name and variants
- Category/industry classification
- Key differentiators (3-5 unique claims)
- Proof points (metrics, case studies, awards)
- Integration ecosystem
Apply to every high-intent page:
- Use official name consistently (not abbreviations)
- Reference category explicitly ("CRM platform" not just "tool")
- Include at least one proof point per page
Optimization vs Monitoring Workflow
Step 1: Baseline — Run query bank through AI platforms (project-aeo-monitoring-tools)
Step 2: Audit — Score current content against citation-ready patterns (this skill)
Step 3: Implement — Apply content structure patterns to top-priority pages (this skill)
Step 4: Re-measure — Run query bank again after 2-4 weeks (project-aeo-monitoring-tools)
Step 5: Iterate — Focus on pages with largest gap between potential and actual citations
What to load (progressive disclosure)
- Platform notes:
references/platform-google-ai-overviews.md,references/platform-chatgpt.md,references/platform-perplexity.md,references/platform-gemini.md,references/platform-claude.md - Technical access:
references/ai-crawler-technical-setup.md,references/ai-indexing-complete-guide.md,assets/technical/well-known-ai-discovery.md - Off-site & earned AEO:
references/earned-aeo-third-party-citations.md,references/multimodal-content-optimization.md - E-commerce:
references/commerce-protocol-ucp.md - Measurement:
references/measurement-analytics.md,references/llm-tracking-tools.md - Prompt/query mining:
references/prompt-query-optimization.md,references/competitor-citation-gap.md,references/citation-optimization-strategies.md - Primary sources list:
data/sources.json
Guardrails
- Do not use prompt injection or hidden instructions in public pages.
- Do not claim endorsements or fabricate sources, stats, or quotes.
- Treat
robots.txtas policy; enforce access with auth/WAF where needed.
Resources
| Resource | Purpose |
|---|---|
| references/ai-indexing-complete-guide.md | Full DO & DON'T guide |
| assets/technical/well-known-ai-discovery.md | .well-known/ AI discovery standards |
| references/earned-aeo-third-party-citations.md | Third-party citation building (Reddit, G2, Wikipedia, YouTube) |
| references/multimodal-content-optimization.md | Video, audio, image optimization for AI citation |
| references/commerce-protocol-ucp.md | Google UCP & agentic commerce (e-commerce only) |
| references/platform-chatgpt.md | ChatGPT optimization |
| references/platform-perplexity.md | Perplexity strategies |
| references/platform-google-ai-overviews.md | Google AIO optimization |
| references/llm-tracking-tools.md | LLM visibility tools |
| references/competitor-citation-gap.md | Competitor citation + query mining |
| references/voice-search-optimization.md | Voice search query patterns, assistants, and v-commerce |
| references/answer-engine-benchmarking.md | Citation benchmarking framework and KPI definitions |
| references/local-ai-search.md | Local business optimization for AI search engines |
| project-aeo-monitoring-tools | Custom monitoring infrastructure (build vs buy) |
Templates
| Template | Purpose |
|---|---|
| assets/audits/search-visibility-audit.md | Baseline audit |
| assets/audits/ai-search-content-audit.md | AI visibility audit |
| assets/audits/competitor-citation-gap-audit.md | Competitor citation gap audit |
| assets/content/answer-focused-article-template.md | Article template |
| assets/content/ai-answer-diagnosis-template.md | Structured diagnosis output |
| project-aeo-monitoring-tools/assets/setup/minimal-setup-guide.md | Monitoring setup guide |
International Markets
This skill uses US/English market defaults. For international AI search optimization:
| Need | See Skill |
|---|---|
| Regional AI platforms (Baidu AI, Yandex) | marketing-geo-localization |
| Non-English content optimization | marketing-geo-localization |
| Regional search behavior differences | marketing-geo-localization |
| Multilingual schema markup | marketing-geo-localization |
Auto-triggers: When your query mentions a specific country, region, language, or non-US AI platforms, both skills load automatically.
Related Skills
| Skill | Purpose |
|---|---|
| project-aeo-monitoring-tools | Build custom AEO monitoring infrastructure (APIs, pipelines, dashboards) — engineering skill |
| marketing-seo-complete | Traditional SEO |
| marketing-content-strategy | Content planning |
| software-frontend | SSR implementation |