Case Study · AI Visibility (AEO)
From 31 to 72.
AI visibility, rebuilt.
Comfort Control Heating, Air & Refrigeration was visible online, and invisible to AI. Here is exactly what we changed, and what it moved.
- AI Visibility Score
- 31 → 72
- Score Increase
- +132%
- Engagement
- 5 months
- Platforms Audited
- 6
01 · The Situation
Visible online. Invisible to AI.
Comfort Control is an established HVAC and commercial refrigeration company serving Walker, Denham Springs, Livingston Parish and the Greater Baton Rouge area. They had a website, a Google Business Profile, and real customers.
In December 2025 we ran a full AI visibility audit. The result was 31 out of 100, the low-visibility tier. When someone asked an AI assistant who to call for HVAC work in their service area, Comfort Control was not part of the answer.
02 · The Diagnosis
Six structural gaps.
Inconsistent Entity Signals
The business identity was not expressed the same way across the sources AI systems cross-reference.
Weak Schema Implementation
Structured data was incomplete, so machines had to guess at basic facts about the business.
Underdeveloped Google Business Profile
The single highest-weight local signal was not fully built out.
Limited AI-Readable Structure
Content was written for people to skim, not for language models to extract and cite.
Weak Citation Consistency
Name, address and phone varied across directories. Every variance dilutes confidence.
No AI Platform Presence
Zero surface area in the assistants that a growing share of customers now ask first.
03 · The Approach
Six pillars, five months.
Structured Schema Implementation
Deployed complete LocalBusiness structured data covering address, geo-coordinates, contact, and service area, so AI systems read facts instead of inferring them.
Entity Consistency Standardization
Locked one canonical version of the business identity and pushed it across every citation source.
Google Business Profile Optimization
Built out categories, services, attributes and posting cadence on the highest-weight local signal.
Content & Freshness Signals
Established ongoing activity so the business reads as current, not archived.
Service Architecture Improvements
Restructured how services are described and separated so each is independently retrievable.
Local Authority Reinforcement
Strengthened the geographic and topical signals that connect the business to its actual service area.
04 · The Results
31 to 72 in five months.
December 2025 · Baseline
31/100
Low visibility tier
May 2026 · Re-audit
72/100
+132% increase
Scores are from Cornerstone’s AI visibility audit framework, measured on the same criteria at both points in time.
05 · The Takeaway
What this case proves.
AEO is the new competitive advantage
Answer Engine Optimization is where local discovery is moving, and most competitors have not started.
Structure and trust signals drive the score
The gains came from machine-readable structure and consistency, not from publishing more content.
Entity consistency is non-negotiable
Every inconsistent listing is a reason for an AI system to lower its confidence in you.
The first-mover window is still open
In most Louisiana service markets, no one is optimizing for this yet. That will not last.
Where does your business score?
Same audit framework. Same six platforms. Free.
Get Your Free AI Visibility Score