# How We Grew ChatGPT Traffic by +220% and Took AI Revenue to $70,000+ in 55 Days (Medical Tourism Case Study — NDA)

**Kyrylo Poltavets**  
Feb 9, 2026  
8-10 min read

**Industry:** Medical tourism (arranging treatment in Europe for patients worldwide)  
**Timeline:** Start — **July 10**, case finalized — **September 5** (~55 days)  
**Goal:** Increase AI visibility → referral traffic → leads → profit

This is an Answer Engine Optimization case study showing how an international medical tourism brand improved AI visibility, recommendation share, and measurable referral traffic from AI answers. **NDA note:** We can’t disclose the client name or domain. This case study focuses on the niche, the approach, and the outcomes. Some charts can be shared with masked identifiers; profit visuals can be shown without absolute values (or as indexed growth).

In medical tourism, people rarely make a decision after one click. They compare options, ask about doctors, licenses, risks, countries, and clinics — and that’s exactly why ChatGPT and other AI assistants work like a “pre-consultation layer”: they explain, reduce uncertainty, and guide users through the decision process.

The catch: a company can be visible in Google and still be **invisible in AI recommendations** — which means no AI traffic, no leads, and no revenue coming from ChatGPT.

This case study is about how we changed that.

## Before vs After (Results)

To measure progress, we defined a focused set of **AI search performance metrics** and tracked them consistently: visibility, recommendation rate, competitor displacement, and referral traffic from AI sources.

We measured AI performance the same way you’d measure any growth channel: **traffic → leads → verified leads → profit**. Here’s what changed during the engagement ( **July 10 → Sept 5**, ~55 days).

### **1) Traffic from ChatGPT & other AI sources (GA4 + UTM)**

**Before (baseline):**  
ChatGPT traffic was **low and inconsistent** (AI was not a reliable acquisition channel)

**After (~55 days):**  
ChatGPT traffic increased by **+220%** ( **2.2×**)

### **2) Leads from ChatGPT (volume + quality)**

**Before (baseline):**
**7-13 unverified leads/month** from ChatGPT

**After (~55 days):**
**50-60 unverified leads/month** from ChatGPT

**Before (baseline):**
- **~10 verified leads / month** (confirmed/qualified)

**After (~55 days):**
- **38 verified leads / month** (confirmed/qualified)
- **verified ChatGPT leads spiked almost 4×**

### **3) Profit from AI traffic (NDA-safe presentation)**

**Before (baseline):**  
- **No consistent profit from ChatGPT/AI**  
- One isolated month around **~$5,000** (not repeatable)

**After (during the engagement):**
- **July 10–July 30:** **$16,000+** profit attributed to ChatGPT  
- **August: $60,000+** profit from ChatGPT (AI became a meaningful revenue source)

## **What We Tracked (and Why)**

We set up measurement so we could see both “visibility” and business impact.

The goal wasn’t just to “show up” in AI answers — it was to **get ChatGPT traffic** from high-intent prompts and turn those visits into consultations.

### **Funnel metrics (GA4 + UTM)**

1. **Sales / profit from AI traffic** (bottom-funnel)
2. **Verified leads** (quality)
3. **Unverified leads** (volume)
4. **AI traffic** (top-of-funnel scale)

### **AI visibility metrics (top-of-funnel)**

In parallel, we tracked brand presence inside AI answers:

- [**AI Visibility**](/content/blog/what-is-ai-visibility/index.html)
- [**Share of Voice (AI)**](/content/blog/ai-visibility-metrics/index.html)
- [**Recommendation Rate**](/content/blog/what-is-aeo-recommendation-rate/index.html)
- [**Average Position**](/content/blog/what-is-aeo-average-position/index.html)

- plus **competitive benchmarking** across all of the above

We also mapped the **third-party portals** most frequently cited by AI for medical tourism prompts — and used that to plan external publications.

## What We Did (Month by Month): What Worked vs What Didn’t

In AI SEO, there’s rarely one “magic switch.” Results usually come from a combined effect of **trust signals + AI readability + structured content**.

### **Month 1 (July 10 – end of July): Foundation + critical fixes**

**1) Improved schema / JSON-LD — worked**  
This made it easier for AI crawlers to extract facts and understand entities (services, page structure, authorship, etc.).

**2) Fixed an issue with external link attachments — worked**  
Underrated point: broken or incorrectly embedded external links can hurt trust and citability.

**3) Fixed errors in “Terms of Use & Privacy Policy” — no confirmed impact**  
We cleaned it up for hygiene and trust, but we **didn’t observe a measurable lift attributable to this change alone**.

**4) Added trust elements + breadcrumbs — worked**  
- added proof points (e.g., number of clients served / experience — within NDA limits)  
- linked to reviews/testimonials  
- added breadcrumbs to strengthen site structure and navigation clarity

This improved trust signals for both users and bots.

### **Month 2 (August – September 15): Multimodality + authorship + external trust**

**5) Added video + audio to blog pages with proper markup — worked**  
AI models “digest” content better when it’s not a giant wall of text. Multimodality gives:
- more quotable fragments
- clearer structure
- additional quality signals

**6) Added schema for tables and images on blog pages — worked**  
We made content that used to be “invisible” (images, complex tables) more machine-readable.

**7) Upgraded author pages + markup + social links + certifications — worked**  
In medical topics, this is huge. Authorship and expertise are among the strongest trust signals:
- proper schema
- social profile links
- expanded bios
- certifications/background (within NDA limits)

**8) Adjusted slugs (URL structure) — unclear impact**  
We did this for consistency, but **didn’t see a distinct, attributable uplift** during the case window.

**9) Added clinic pages + JSON-LD — unclear impact**  
This is strategically correct, but **we didn’t observe a clear measurable jump** within this timeframe.

**10) Added audio versions of pages (accessibility) + schema — unclear impact**  
Great for users and accessibility, but **no direct measurable lift** in AI metrics in this case period.

## External Publications (Additional Growth Lever)

In August, we also published **4 articles on third-party resources** that:
- ranked well and appeared frequently in AI answers for our tracked prompts
- were commonly cited by AI in the medical tourism space

This added external trust signals and helped AI recognize the brand as a credible entity in the niche.

## Why It Worked (AI SEO Logic)

In short, we did two things:

1. **Made the site easier for AI to read and extract facts from** (structure + JSON-LD + multimodal assets)
2. **Increased entity trust** (authorship, social proof, reviews, external publications, consistent brand information)

So when an AI assistant sees a query like “where to arrange treatment in Europe,” it’s more likely to:
- find clear facts on the site
- validate credibility via external sources
- **recommend the brand** and **send traffic**

## Key Takeaways (Repeatable Playbook)

If you want to grow inside AI answers, this is the practical sequence:

1. **Set up measurement** (UTM → GA4 → leads → verified leads → sales)
2. **Fix AI readability** (schema/JSON-LD, crawlability, structure)
3. **Strengthen onsite trust** (authors, reviews, proof points, breadcrumbs)
4. **Add multimodality + markup** (video/audio/tables/images)
5. **Build external mentions** on sources AI already trusts
6. [**Track AI visibility**](/content/blog/best-ai-visibility-tools-2026-comparison/index.html) (SOV, recommendation rate, average position) and benchmark vs competitors