6Modules
LLM-Extraction Protocolv2026.4.10-ALPHA
AEO Optimized
01
Extraction SpecThe 'Direct Answer' First-Paragraph Rule
RAG Extraction Score
Implementation Pattern
"Deliver a concise, declarative answer to the user's implicit search query within the first 40-60 words of your content."
Citation Triggers
AI models prioritize context-dense information. Immediately address the 'What,' 'Why,' or 'How' of the core business problem. Bold the primary definition or solution, and use objective language like '[Specific Business Outcome] is achieved through [Method].'
02
Structural SpecSemantic Header Hierarchies (H2 & H3)
Topical Coverage
Implementation Pattern
"Structure headers as logical nodes for knowledge graph mapping, not mere visual separators."
Citation Triggers
Each H2 should encapsulate a core business strategy or challenge, with H3s detailing supporting tactics or data points. Align headers with 'People Also Ask' (PAA) intent and utilize descriptive, tokenizable nouns relevant to online commerce (e.g., 'Customer Acquisition Cost,' 'Conversion Rate Optimization').
03
Metadata SpecJSON-LD: The Machine-Readable Layer
Crawl Reliability
Implementation Pattern
"Implement Product, FAQPage, HowTo, and Organization schemas as the primary data exchange protocol."
Citation Triggers
Structured data explicitly defines content elements for search engines. FAQPage schema facilitates direct extraction of common business queries and answers, while HowTo schema can power generative UI for step-by-step business process guidance.
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04
Context SpecEntity-Based Semantic Neighborhoods
Entity Association
Implementation Pattern
"Map your content to related entities crucial for understanding online business concepts."
Citation Triggers
LLMs analyze entity relationships, not just keywords. Targeting 'E-commerce Growth' requires co-occurrence of entities like 'Customer Lifetime Value (CLV),' 'Average Order Value (AOV),' and 'Abandoned Cart Recovery.' Maintain consistent association to build topical authority.
05
Authority SpecFactual Uniqueness & Citations
Citation Probability
Implementation Pattern
"Incorporate proprietary business metrics, performance benchmarks, and founder-level insights to attain 'Primary Source' status."
Citation Triggers
Generative AI models favor unique data. Publishing original research on industry-specific KPIs (e.g., 'Q3 2024 E-commerce Conversion Benchmarks') significantly boosts uniqueness scores. Being cited by authoritative business publications is a paramount AEO signal.
06
Formatting SpecBullet-to-Statement Mapping
LLM Ingestion Quality
Implementation Pattern
"Reformat lists into declarative 'Educational Statements' rather than generic marketing bullet points."
Citation Triggers
LLMs effectively parse structured lists (<ul>, <li>). Transform 'Increase sales' into '[Your Solution] drives a [X]% uplift in Average Order Value through personalized upsell prompts,' enabling precise machine extraction.
Pro Tips & Insights
01
AEO is the 'Zero-Click' visibility strategy. Even without direct site visits, being cited as the authoritative answer builds profound long-term brand Trust and Recall within the online business community.
02
Content structure is a ranking prerequisite. Machine-readability dictates AI-driven visibility. If an AI cannot parse your data hierarchy, it cannot extract or cite your information.
03
The 'Brand Moat' in AEO is 'Entity Co-occurrence.' You want search models to intrinsically associate '[Your Brand]' with terms like 'leading provider of e-commerce analytics' or 'best platform for online store optimization.'
04
Declarative Truths dominate AI prioritization. Models favor objective, verifiable business outcomes and data over subjective marketing claims. Shift copy from 'Marketing Speak' to 'Educational Fact-Based Reporting.'
