AI Visibility for a Leading Real-Estate Investment Firm
Challenge
Despite strong traditional SEO performance, the client had near-zero visibility inside AI models. Their research pages, market insights, and asset-class expertise were being crawled by LLMs but:
- Not recognized as structured or authoritative
- Not linked to clear entities, locations, or asset categories
- Not cited or surfaced in ChatGPT, Gemini, Copilot, or Perplexity answers
- Inconsistent terminology and fragmented content diluted trust signals
Result: their teams produced high-quality analysis, but AI systems couldn’t interpret or prioritize it, leading to lost reach and competitive disadvantage in AI-driven discovery.
What We Did
We deployed a combined AEO/GEO + data engineering solution focused on structure, entities, and machine readability:
1. Entity-first content architecture
- Mapped all core entities: asset class → subtypes → markets → investment criteria
- Unified terminology across research, insights, and portfolio pages
- Eliminated contradictions and ambiguities that confuse LLMs
2. Schema & structured markup
- Implemented entity-rich schema across 40+ high-value pages
- Added machine-readable metadata for properties, markets, amenities, valuations, and risk factors
- Built a consistent taxonomy and knowledge graph alignment
3. Crawlability & content engineering
- Rebuilt critical pages for clarity, hierarchy, and semantic structure
- Removed indexing blockers, duplicated structures, and outdated templates
- Optimized internal linkage for machine understanding, not just human UX
4. AI Visibility Data Pipeline
- Built automated checks for entity coverage, schema integrity, and AI-readiness
- Deployed a monitoring system to track content ingestion across LLM crawlers
Results (within 60 days)
AI Visibility
- From 0–2% visibility in AI answers → up to 28–34% inclusion in responses for queries related to their asset class
- Their market insights began appearing as cited or paraphrased sources in ChatGPT and Perplexity
- LLMs shifted from generic public data to their definitions, frameworks, and terminology
Search Performance
- +40% growth in impressions for entity-rich pages
- +24% increase in organic visits to high-value research content
- Dramatic improvement in long-tail queries tied to asset-class expertise
Knowledge Authority
- LLMs began treating the firm’s content as a primary point of truth in their niche category
- Internal teams reported significantly better AI-powered research outputs due to improved model understanding of their materials
- The firm gained a competitive visibility advantage, as competitors lacked structured, entity-aligned content
If you’d like to understand how your own website can become a trusted, AI-visible knowledge source across ChatGPT, Gemini, Copilot, and Perplexity, we’ll walk you through your current visibility, structural gaps, and fastest improvement opportunities during our free assessment call.