How iRestore Built a High-Intent AI Growth Channel and Increased AI Traffic 6.5× in 90 Days

At a Glance

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

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 didn’t chase AI traffic.
They built a system to earn it.

By operationalizing AI visibility with Erlin.ai, they turned AI platforms into their most efficient growth channel proving that AI discovery is not a trend, but a controllable performance lever.