How One SEO Consultant Turns Semrush’s AI Sentiment Insights into Traffic and Visibility
Zbyněk Fridrich is a freelance SEO expert and last year’s winner of the Best SEO Project award in the Czech Republic.
With 17 years in the field, he has one strict rule for all new clients: “If you want to work with me, you need Semrush.”
To set his clients up for success, he analyzes How AI programs recommend brands—and when their customers aren’t among those recommendations.
In this guide, I’ll share his exact workflow and what he produced for WorkLounge, a collaborative brand that doubled its organic visibility and AI traffic in five months.
A Two-Phase Approach to Visual Search
Zbyněk’s workflow includes two main steps that leverage AI sentiment and AI insights from Semrush’s AI Visibility Toolkit:
- Section 1: Control your emotions—understand what AI is saying about your product right now, and adjust it.
- Section 2: Discover new possibilities—check the commands where you have to appear but not appear and close the gap.
“The goal is to have maximum control over what AI says about us today. Only in the second step do we look for new content opportunities.”
Skipping step 1 is a mistake many brands make. If the AI has the wrong image of you, mindlessly creating more content doesn’t fix the problem.
Step 1: Analyze Emotions in Product Performance
Zbyněk begins by opening the Product Performance tool, adding the client’s key competitors and target area, and testing How engines like ChatGPT, Google AI, and Gemini define the genre.
This is important because AI search visibility is not driven by “rankings” alone. It is decided that the AI models consider your product as authoritative and valuable enough to recommend.
“It is not important to enter all of them the answer. The most important thing is the feeling and general appearance. “
First, Zbyněk examines the overall feel of the brand in AI responses and examines how it compares to other players in the niche.
Then, you scroll down Business Drivers report and evaluate specific factors, organizations, and topics that keep appearing in AI results.
Next, you open Seeing report to analyze some of the ideas—good and bad—that influence the state of AI.
Finally, Zbyněk reviews AI-generated strategy recommendations in the toolkit—actionable suggestions based on his client’s AI visibility data.
“For WorkLounge, the first image was clear—and damaging. The AI always described the space as noisy. Phone booths were never mentioned anywhere. Member access was described as 9–5, even though members came and left 24/7. None of this was completely accurate, but that’s what the AI had to work with based on the website’s existing content.”
Step 2: Rewrite Existing Website Content
From here, Zbyněk identifies key areas of focus—points of change—and revises the client’s website to fix anything the AI is doing wrong.
If negative or negative reviews or third-party sources are shaping AI’s perception of your product, your website content needs to directly address and counter that narrative.
“I never work on new content if I haven’t edited the content already on the website.”
For WorkLounge, that meant going through 90 pages of product and service content and rewriting them to provide AI with accurate information. For example, Zbyněk included:
- Opening hours: Curated content now clearly separates 24/7 member access from 9-5 community hours
- Quiet places: Call booths and quiet areas—already there—are finally listed on the site
- Membership benefits: Product pages have been rewritten to make the member vs. non-member experience clearer
Step 3: Fix Technical Problems and Use the Structured Data
Next, Zbyněk uses the Site Inspection tool to identify and fix problems that prevent search engines and LLMs from properly reading the client’s site.
These amendments include:
- Adding structured data
- Improving page layout
- Improves content formatting
- Solving problems with internal links
He also checks with LLM.txt—a file that gives AI crawlers clear instructions on how to interpret your site’s content.
It’s still an emerging trend with no definitive proof of impact, but Zbyněk has seen positive results with her clients.
Step 3: Use AI Prompt Data to edit content
When the feeling is in good shape, Zbyněk issues orders to Narrative Drivers tool and use them to organize new content.
These are real questions people ask AI tools about topics in the client space.
He then downloads the data to create a complete audit report and reporting file for his clients.
In the end, Zbyněk selects the 20-30 most relevant commands for each project. Each information becomes an FAQ block on the relevant product or service page or a new piece of content.
For WorkLounge, this meant creating FAQ sections around questions like what the member access policy is, what quiet work options are available, and how the space compares to regular offices.
To sum it all up, alerts also tell him where the gaps are. If the content doesn’t present its client in a solid place, that piece of content needs to be there or needs to be modified.
Step 4: Distribute to All Channels at the Right Time
From here, Zbyněk works on pushing this new content across all channels—blog, social media, newsletter, link building—until the moment when search demand peaks.
“AI tools read your entire digital environment, not just your website. The more consistently and accurately a product appears across all trusted sources, the stronger the signal becomes.”
For WorkLounge, content about quiet spaces and call centers went out all at once, including an updated Google My Business profile. Social posts reinforced the same message. The content of the newspaper binds it together.
Time is also important.
Zbyněk aligns content pushes with peak seasonal demand for each topic—so content lands when people are actively looking for it, not whenever the editorial calendar frees up.
Step 5: Track performance in parallel
To track the effectiveness of his efforts and iterations, Zbyněk monitors commands and keywords in Position Tracking a tool.
This allows him to see the organic impact of key search areas—from Google AI to ChatGPT.
For WorkLounge, the visibility of the AI Overview took off 17% to 35% over five months—directly integrated with the content changes made in phases 1 and 2.
And guess what? Organic traffic and rankings are tracked, too.
The traffic attributed to ChatGPT has also increased almost 20x compared to the previous period and continues to increase.
“All of this cocktail is aimed at improving the visibility of LLM programs, increasing organic traffic, getting mentioned in AI reviews, and improving the overall business performance of the website.”
Step 6. Generate Client- and Exec-Ready Reports
Finally, Zbyněk uses Semrush’s My Reports feature to extract AI visibility and SEO data into clean, shareable PDF reports.
This goes directly to client presentations—showing emotional points, quick visualizations, strategic tips, and timelines without requiring clients to log into the tool themselves.
It’s also how he gets to buy. When clients see AI misrepresenting their brand in a polished report, the case to fix it is made.
Results: What Five Months of AI Performance Look Like
WorkLounge started this program in September. By January, all of Zbyněk’s metric tracks were gone:
- Emotional rating: 67 → 82. A fundamental change. AI tools go from describing WorkLounge as a noisy, 9-to-5 office space to accurately represent what the product actually offers—quiet spaces, 24/7 member access, and a range of workspace options.
- AI Overview: 17% → 34%. The share of important keywords where WorkLounge appears in Google AI Overviews has doubled. This is a direct result of the content changes—AI now has accurate, well-structured information to draw from.
- Organic traffic: up. Better AI sentiment leads to more accurate AI recommendations, which leads to more keyword searches, which leads to organic traffic. This thread is consistent across all Zbyněk clients that use this workflow.
“I never do something just because of AI. I treat AI visibility as part of SEO.”
The New Biology Playbook
Zbyněk’s method is not difficult. He uses AI data to find what’s broken, fix the content, and build on a clean foundation. The results follow.
What makes it work is treating AI visibility and SEO as one strategy—not two separate workflows.
Prepare an AI narrative about your product, and everything else evolves with it: organic rates, AI overview, and referral traffic.
That’s exactly what Semrush One is built for. It combines traditional SEO tools with AI visibility data in one connected workflow—so you can quickly track visibility and keyword rankings, run site audits on both search engines and AI crawlers, and report on it all without switching tools.
If you want to use the same workflow that Zbyněk uses, this is where you can start.
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