How iRESTORE built a high-intent AI growth channel and increased AI traffic 6.5× in 90 Days
iRESTORE
Health & Wellness · DTC E-commerce
At a Glance
Metric | Result |
|---|---|
AI Traffic Growth | 6.5× increase (90 days) |
AI Conversion Rate | 4× higher than site average |
Primary AI Source | ChatGPT (94% of AI traffic) |
The Challenge: Invisible in Decision-Stage AI Queries
iRESTORE performed well across traditional SEO and paid acquisition.
However, customer discovery was shifting toward AI systems.
Buyers were asking questions like:
“Best laser hair growth device”
“Does X actually work for hair loss?”
Despite strong products and reviews, iRestore was missing from these AI answers.
Demand existed.
Visibility inside AI systems did not.
The Constraint: No Operational View of AI Visibility
From a systems perspective, iRestore lacked visibility and control over AI-driven discovery:
No way to measure how often the brand appeared in AI answers
No breakdown of which AI platforms were driving traffic
No execution loop to convert visibility gaps into fixes
AI traffic existed, but performance and impact were opaque
AI had become a high-intent channel , but it was unmanaged.
The Solution: Treat AI Visibility as an Execution System
iRestore used Erlin.ai to operationalize Answer Engine Optimization (AEO) as a repeatable workflow.
1. Clarifying How AI Systems Identify the Product
Erlin helped ensure AI systems could consistently recognize:
What the product is
What problems it solves
How it differs from alternatives
System effect: AI stopped inferring details and began citing iRESTORE accurately.
2. Structuring Content for AI Retrieval
Action: Build content explicitly formatted for AI extraction and citation.
Content was designed around how AI systems retrieve answers , not how humans skim blogs.
System effect: iRESTORE began appearing as a referenced source in product-level AI answers.
3. Translating the Site into Machine-Readable Signals
Erlin prioritized schema and structured data that reduced ambiguity for AI systems.
System effect: Citation probability increased across AI platforms.
Results: High-Intent Traffic at Scale
1. 6.5× Growth in AI Traffic
AI referrals grew from negligible to a meaningful acquisition channel within one quarter.
2. AI Became the Best-Converting Channel
Channel | Conversion Rate |
|---|---|
Site Average | 0.84% |
AI Referrals | 3× higher |
Users arriving from AI were already educated and decision-ready.
3. Focused Channel Optimization
Analysis showed:
94% of AI traffic came from ChatGPT
This allowed iRESTORE to concentrate execution on the platform driving real revenue.
Conclusion
iRESTORE had AI traffic but couldn't see where it came from or which prompts drove it. No dashboard showed ChatGPT vs. Claude. No way to track if coverage was improving or declining.
Erlin tracked 15 high-intent prompts daily across four platforms. iRESTORE saw that ChatGPT drove 94% of AI referrals and optimized there. They detected coverage gaps in 14 days instead of 67.
AI traffic grew 6.5× in 90 days. Conversion rate: 3× site average.
