How Katia increased AI search mentions by 40%

Summary

Katia, an AI-powered voice assistant built for healthcare practitioners, was heavily reliant on traditional SEO for lead generation. But as more of their ideal buyers started searching through ChatGPT, Perplexity, and Claude, Katia was nowhere to be found. Using Refine, they identified the prompts that mattered most, optimized their content to get cited by LLMs, and turned AI search into a reliable acquisition channel — signing more clients and growing their MRR in the process.

The Problem

Katia had built a strong SEO foundation. Google was one of their primary source of inbound leads, and it was working — until it wasn't enough. Their prospects, mostly doctors, therapists, and clinic managers, were shifting their research habits. Instead of scrolling through Google results, they were asking AI engines directly: "What's the best voice AI for medical practices?" or "AI assistant for patient notes."

The problem was clear: Katia had zero visibility on AI search engines. They weren't being cited, recommended, or even mentioned. Every prompt that mattered to their business was returning competitors — or generic answers that left Katia out entirely.

"We knew AI search was becoming a thing, but we had no idea how much pipeline we were leaving on the table," says the Head of Growth at Katia. "Our SEO was solid, but it didn't translate to LLM results at all."

The Solution

Katia partnered with Refine to build a GEO strategy from the ground up. The approach was methodical:

• Mapped the highest-value prompts prospects were using across ChatGPT, Claude, and Perplexity — focusing on healthcare-specific AI queries.
• Analyzed which sources LLMs were pulling from and identified the content gaps keeping Katia out of the answers.
• Created and optimized targeted content designed to be cited by AI engines — not just ranked by Google.
• Tracked AI visibility week over week to measure progress and iterate fast.

How Katia Used Refine

The first step was understanding the landscape. Refine's prompt intelligence showed Katia exactly which queries their ideal customers were running on AI search engines — and where Katia stood (or didn't) in the results.

What they found was eye-opening. Competitors with weaker products were consistently being recommended simply because they had content in the right places. Katia's existing blog posts and landing pages, while great for Google, weren't structured in a way that LLMs could easily parse and cite.

Using Refine's source classification, Katia identified the exact publications, directories, and content formats that LLMs favored for healthcare AI queries. They then built a focused content plan: comparison articles, practitioner-focused guides, and third-party placements — all engineered to get picked up by AI engines.

"Refine gave us a playbook we didn't know existed," says the Head of Growth. "We stopped guessing and started executing with precision."

Results

Within weeks of deploying their GEO strategy, Katia saw measurable impact:

• AI search visibility went from near-zero to consistent presence across their top-priority prompts.
• Inbound leads from AI search engines became a meaningful and growing channel alongside organic SEO.
• Multiple new clients signed directly attributed to AI search discovery — prospects who said they found Katia through ChatGPT or Perplexity.
• Monthly recurring revenue grew as the new acquisition channel compounded on top of their existing SEO pipeline.

For Katia, GEO didn't replace SEO — it supercharged it. By showing up where their buyers were actually searching, they unlocked a channel their competitors hadn't figured out yet.