AI Citations Intelligence System

Self-Learning Citation Intelligence

Optiview's citation system doesn't use static templates. Instead, we've built a context-aware, self-learning engine that analyzes your actual site content to generate queries indistinguishable from real user searches.

How the System Works

1. Industry Classification (200+ Taxonomies)

When you run an audit, the system automatically classifies your site using a hierarchical dot-slug taxonomy:

• AI-Powered Detection: Analyzes your domain, content, and schema
• Hierarchical Structure: From broad categories to specific niches (e.g., health.pharma.brand, travel.air.commercial, retail.grocery)
• Cascading Templates: Industry-specific query patterns that match real user intent

2. Context-Aware Query Generation (v4-llm)

Our proprietary query engine combines multiple intelligence layers:

• Contextual Grounding: Analyzes your homepage title, H1, meta description, and site structure
• Entity Intelligence: Extracts brand name, primary topics, and semantic relationships with intelligent camelCase and compound-word splitting
• Intent Modeling: Maps your content to real user search behaviors across discovery, informational, evaluative, commercial, and navigational intents
• Quality Filtering: Multi-stage validation ensures queries read like authentic user questions—proper grammar, natural phrasing, no awkward repetition
• Competitive Awareness: Understands category positioning without explicit input

3. Prompt Intelligence Index

The system continuously learns and improves through:

• Post-Audit Updates: Brand, entities, and site type immediately indexed
• Citation Feedback Loop: Analyzes which queries produce citations, feeding back into query generation
• Cross-Domain Pattern Mining: Learns from successful query patterns across thousands of audits
• Semantic Discovery: Powers entity-based search for competitive intelligence and category benchmarking

Query Types Generated

️ Branded Queries (~10 per run)

Questions that test brand recognition and direct discovery:

• Identity queries ("What is [Brand]?")
• Service/product inquiries ("[Brand] features and capabilities")
• Trust and safety questions ("[Brand] customer reviews")
• Contact and support searches ("[Brand] customer service number")
• Comparative positioning ("[Brand] vs [Competitor]")
• Navigational anchors ("[Brand] login", "[Brand] store locator")

Non-Branded Queries (~18 per run)

Category-level questions that test topical authority:

• Discovery: "Best [category] options", "Top [services] to consider"
• Informational: "How does [technology] work?", "What are [services]?"
• ️ Evaluative: "Pros and cons of [category]", "Is [service] worth it?"
• Commercial: "How much does [service] cost?", "[Category] pricing guide"
• Alternatives: "Alternatives to [category]", "[Service] competitors"
• Problem-solving: "How to [accomplish goal] with [category]"

Linguistic Quality Assurance

Every query passes through intelligent filters:

• Natural grammar and syntax
• No brand leakage into non-branded queries
• No repetitive phrases or awkward constructions (e.g., "cruises cruises")
• Appropriate verb conjugation and pluralization
• Intent-appropriate phrasing

AI Platforms Tracked

Each query is tested across all major AI assistants:

Industry-Specific Examples

Here's how query generation adapts to different industries:

Healthcare (Pharma)

• "prescribing information for {brand}"
• "{brand} medications contraindications and warnings"
• "{brand} dosage and administration guidelines"
• "How to report side effects to {brand}"

Travel (Airlines)

• "{brand} baggage policy"
• "{brand} customer service phone number"
• "Check-in for {brand} flights"
• "{brand} flight status and delays"

B2B SaaS

• "{brand} pricing plans and features"
• "{brand} integrations with {technology}"
• "{brand} vs {competitor} comparison"
• "How to set up {brand} for {use-case}"

E-commerce (Fashion)

• "{brand} sizing guide"
• "Best {category} from {brand}"
• "{brand} return policy and shipping"
• "{brand} customer reviews for {product}"

Education (Higher Ed)

• "{brand} admissions requirements"
• "{brand} tuition costs and financial aid"
• "{brand} vs {competitor} rankings"
• "{brand} academic programs in {field}"

Advanced Intelligence Features

Three-Tier Intelligent Caching

• Tier 1: Hot Cache (KV Store) - 5-10ms response, 7-day TTL, serves 90% of requests instantly
• Tier 2: Canonical Store (D1 SQL) - 50-100ms response, full query history, version tracking
• Tier 3: Fresh Build (On-Demand) - 300-500ms response, applies latest intelligence models

Semantic Discovery & Competitive Intelligence

• Find competitors by entity overlap
• Benchmark citation performance against category peers
• Discover emerging topic trends in your industry
• Identify content gaps where competitors are cited but you're not

Automatic Learning Cycle

• Post-audit updates to brand, entities, and site classification
• Hourly refresh jobs for 100 least-recently-refreshed domains
• Citation feedback loop analyzes successful query patterns
• Cross-domain pattern mining improves all future audits

Understanding Your Results

Citation Percentage by Source

• 0-10%: Low visibility—focus on content clarity, FAQ structure, and crawler access
• 10-25%: Moderate visibility—optimize content chunkability and add citations
• 25-50%: Strong visibility—expand content depth and maintain quality
• 50%+: Excellent visibility—you're a trusted source for this AI platform

Query Type Performance

️ Branded Queries: Tests brand awareness

• High citation rate (>80%) = Strong brand recognition
• Low citation rate (<50%) = AI systems lack good brand information

Non-Branded Queries: Tests category authority

• High citation rate (>50%) = You're a trusted authority in your category
• Low citation rate (<30%) = Opportunity for educational/topic-focused content

Optimizing for AI Citations

Content Strategy

• Answer-Focused Content: Create content that directly answers common questions
• FAQ Optimization: Structure content with clear questions and detailed answers
• Comprehensive Coverage: Provide thorough, authoritative information on topics
• Technical Accuracy: Ensure information is current and factually correct
• Unique Value: Offer original insights, data, or research

Technical Implementation

• Structured Data: Implement FAQPage, QAPage, and Organization JSON-LD markup
• Clear Headings: Use descriptive H1, H2, H3 tags that AI can easily parse
• Meta Descriptions: Write compelling descriptions that summarize key points
• Internal Linking: Connect related content to help AI understand relationships
• Mobile Optimization: Ensure content is accessible and well-formatted on all devices

AI Crawler Access

• Allow GPTBot, Claude-Web, PerplexityBot in robots.txt
• Ensure content is accessible without JavaScript (SPA parity)
• Use semantic HTML structure
• Provide clear, stable URLs for key content

Getting Started

Ready to measure your AI citation performance?

1. Visit the Optiview Dashboard
2. Run an audit on your domain
3. Check the Citations tab to see AI references to your content
4. Review your citation rates by AI source (ChatGPT, Claude, Perplexity, Brave)
5. Analyze branded vs non-branded query performance
6. Identify top cited pages and missed opportunities
7. Implement recommended optimizations
8. Re-run citations to track improvement over time

API Access

Programmatic access to citation intelligence:

Query & Prompt Endpoints

• GET /api/llm/prompts?domain=example.com - Get cached queries with metadata
• GET /api/prompts/related?entity=cruise&limit=20 - Find related domains by entity

Citation Endpoints

• POST /api/citations/run - Trigger manual citation runs
• GET /api/citations/summary - Get aggregated metrics
• GET /api/citations/list - Retrieve detailed citation records
• GET /api/insights/:domain - Combined scoring + citations analysis

Performance: ~98% cache hit rate, <20ms avg response time for cached queries