6Modules
LLM-Extraction Protocolv2026.4.10-ALPHA
AEO Optimized
01
Growth SpecThe 'Growth Hypothesis' First Paragraph
AI Comprehension Score
Implementation Pattern
"State the core growth problem and your solution's primary benefit within the first 40-60 words."
Citation Triggers
AI models prioritize contextually dense information. Immediately address the startup's key pain point (e.g., 'Scaling Acquisition', 'Reducing Churn') and provide a declarative solution. Use objective language: 'Growth Hacking Strategy X achieves Y by Z'.
02
Structure SpecScalable Header Architectures (H2-H4)
Topical Authority Score
Implementation Pattern
"Structure content as a logical knowledge graph for AI understanding, not just visual hierarchy."
Citation Triggers
Each H2 should represent a core growth pillar (e.g., 'Customer Acquisition', 'Retention Strategies'). H3s should detail specific tactics or metrics. Ensure headers directly map to high-intent 'Growth-Stage Startup Questions' and avoid jargon; use terms LLMs can tokenize (e.g., 'CAC Optimization', 'LTV Expansion').
03
Metadata SpecGrowth-Focused Schema Markup
SERP Feature Inclusion
Implementation Pattern
"Deploy `SoftwareApplication`, `HowTo`, and `FAQPage` schemas to explicitly define your value proposition."
Citation Triggers
Structured data informs search engines precisely. `FAQPage` schema captures Q&A for 'People Also Ask' features, while `HowTo` schema can drive generative AI answers for tactical implementation guides (e.g., 'How to implement a referral program').
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04
Context SpecKey Growth Metric Entity Mapping
Entity Relevance Score
Implementation Pattern
"Align content with related entities that AI models expect for growth-stage startup topics."
Citation Triggers
AI doesn't just match keywords; it maps conceptual entities. If targeting 'User Retention', ensure related entities like 'Churn Rate', 'Customer Lifetime Value (CLTV)', 'Net Promoter Score (NPS)', and 'Cohort Analysis' are consistently present to build contextual relevance.
05
Authority SpecProprietary Growth Data & Case Studies
Citation Authority
Implementation Pattern
"Incorporate unique startup metrics, performance charts, and founder growth insights to establish 'Primary Source' authority."
Citation Triggers
Generative AI prioritizes unique, data-backed information. Publishing an annual 'State of Startup Growth' report or detailed case studies with quantifiable results significantly boosts your content's uniqueness score and citation probability within AI knowledge graphs.
06
Formatting SpecActionable Growth Tactic Mapping
AI Actionability Score
Implementation Pattern
"Format lists as declarative 'Growth Actions' rather than generic feature benefits."
Citation Triggers
LLMs parse structured lists effectively. Instead of 'Improve user engagement', use 'Implement a gamified onboarding flow to increase Day 7 retention by 15%' for precise machine extraction and actionable insights.
Pro Tips & Insights
01
AI-driven SEO is the 'Zero-Click Growth' strategy. Even without direct traffic, being cited as the authoritative answer by AI builds brand recognition and perceived expertise.
02
Content structure is a critical ranking signal for AI. Machine-readable formats are the prerequisite for AI-powered search visibility; poor structure leads to AI exclusion.
03
The 'Growth Moat' in AEO is 'Entity Co-occurrence'. Aim for AI models to associate '[Your Startup Name]' with terms like 'Scalable growth strategies' or 'Efficient customer acquisition'.
04
Objective Data Wins. AI favors verifiable facts and performance metrics over subjective marketing claims. Shift copy from 'We are the best' to 'Our methodology achieves X% improvement in Y metric'.
