Zagreb SEO Day

Registration

SEARCH EVERYWHERE OPTIMIZATION: How to use every online channel to make sure the right people find you at the right moment

People are no longer searching only on Google, BUT they’re still buying. People discover brands on social media, search for reviews and recommendations on YouTube and Reddit, while increasingly using ChatGPT, Gemini and other AI tools to decide what to buy, where to go or which company to choose. You have to be findable EVERYWHERE.

In this session, I’ll show you how to optimize your entire online presence for discovery (Instagram, YouTube, Twitter (X), Facebook, LinkedIn, LLMs). You’ll learn how to adapt your content to different search behaviors and how SEO, social search and AI visibility work together.

No BS, you'll get real EXAMPLES to follow.

The money is still online. You just need to show up where your customers are searching.

Building and automating an AEO framework to take AI visibility to pipeline

A leading cybersecurity company came to Flow Agency in 2025 to grow their AI visibility. There was no proven playbook for AEO. Flow built a foundation: LLM visibility tracking, the Digital Footprint Audit, a content audit, and reporting that made a volatile landscape actually legible. As part of that, I built the Compare & Optimize framework for recovering lost citations fast, not just winning new ones.

We got our client recommended #1 in Google AI Overviews, with organic search driving real impact on a seven-figure pipeline across 2026. It's also the work that got shortlisted at the 2026 US Search Awards and European Search Awards for Best Use of AI in Search.

Backstory: early on, the wins came fast. We broke our client into a new product category, grew their visibility across LLMs, and got them recommended as the top brand in Google's AI Overviews.

But volatility was there from the start. Some citations we won one month would be gone the next. That is why the framework had to be built to recover, not just to win. Another big test came in May 2026, when Google started demoting the self-promotional listicles most of the industry relied on.

I'll show what broke, how we recovered each time, and how I automated the framework to run at scale. I'll walk you through exactly how we did it, so you can go build your own. Then the part most AEO work doesn't usually show: visibility reaching pipeline. The added ACV grew quarter over quarter, opportunities came in pre-qualified with higher value per opportunity year over year, and the client was ahead of their yearly goals by mid-2026.
Backstory: early on, the wins came fast. We broke them into a new product category, grew their visibility across LLMs, and got them recommended as the top brand in Google's AI Overviews.

But the volatility was there from the start. Some citations we won one month would be gone the next. That is why the framework had to be built to recover, not just to win. Another big test came in May 2026, when Google started demoting the self-promotional listicles most of the industry relied on.

I'll show what broke, how we recovered each time, and how I automated it to run at scale. I'll walk you through exactly how I did it, so you can go build your own. Then the part most AEO work doesn't usually show: visibility reaching pipeline. The added ACV grew quarter over quarter, opportunities came in pre-qualified with higher value per opportunity year over year, and the client was ahead of their yearly goals by mid-2026.

The Great Blogging Collapse: What 100 Blogs Tell Us About Surviving AI SearchThe Great Blogging Collapse: What 100 Blogs Tell Us About Surviving AI Search

Coffee break

LinkedIn $$$ Engine: Land High-Paying SEO clients without cold pitching

This talk will help SEOs understand what’s going wrong with their LinkedIn content and why potential clients aren’t reaching out. They may be getting plenty of likes and engagement from the SEO community, but that engagement isn’t turning into actual client conversations.

They’ll learn the top five mistakes SEOs make with their LinkedIn posts, along with practical examples of how to fix them, attract the right audience, and turn their content into premium SEO clients.

SEO Analytics: When the Numbers are right but the Conclusions are wrong

Being on the other side of the SEO stick, the analytical one, I often see the results of SEO fuckups or misconceptions SEO professionals have when it comes to real human behavior and digital analytics data.

Some of those mistakes come from comparing numbers that should never have been compared in the first place. Others come from trusting data without understanding how it was collected, or from assuming that a change in organic performance must have been caused by SEO.

In this session, I’ll go through some of the mistakes and misconceptions I encounter most often, explain why they happen, and show how easily perfectly valid data can lead to completely wrong conclusions.

Why? Because analytics is rarely about finding a number; it is about understanding what that number actually means.

Croatia AI Index: How AI Sees Croatia, and Who It Does Not See at All

Since LLM tools started spreading, at Risely Digital we have been logging what AI models answer in Croatian and about Croatia. The result is the Croatia AI Index, the first broad look at how AI sees the Croatian market.

We start with topics that concern everyone. How much a weekly grocery basket for a family of four costs according to AI, and how far that is from real prices. Who it names as the best Croatian singer, and where that verdict comes from. How it describes the same politicians in Croatian and in English. Where it sends a tourist asking about the coast. Whether it recommends restaurants, hotels and local businesses by name.

The second angle is foreigners. What they ask about Croatia, and what picture of the country the model builds out of that.

The third part is the Croatian tech scene, where all of this is easiest to measure:

which Croatian startups AI recommends to foreign investors, and whether it is only Rimac, Infobip and Photomath or newer companies too which companies it names as the best employers, and based on which sources how it explains the ecosystem to an outsider, which funds, accelerators, conferences, media and people it points to who actually shapes that picture, which media get cited most and how much of that is domestic press how current the information is, whether it knows about recent investments, acquisitions and leadership changes whether Croatian companies are more visible in Croatian or in English

The closing question is whether an AI elite exists, meaning the same companies and the same names every time, while everyone else stays invisible. And what it takes in practice to get in.

No theory, all the data is fresh and collected right up to conference day.

Lunch break

Mapping the Limits of a Page’s Ability to Answer

How much of SEO comes down to just simply answering the question, and how do you know when your page has stopped doing that?

A page can perform brilliantly for its core queries while struggling with searches just a few words away. Those words can change what the user needs: a different explanation, a specific condition, a comparison, or a decision. The subject stays familiar, but the answer required shifts.

In this session, I’ll explore whether the precision of that answer explains more of organic performance than our usual content audits reveal. Using thousands of pages, their Google Search Console data, and competing pages extracted from thousands of SERPs, I’ll show how to examine the relationship between what people ask, what content actually delivers, and which results Google ranks.

We’ll combine semantic representations, passage-level relevance scoring, and LLM-assisted intent classification to distinguish topical similarity from a sufficiently complete answer. Then we’ll connect those measurements to performance, looking for nonlinear patterns, points of diminishing returns, and boundaries where a competing page becomes a better fit.

The interesting questions begin at those boundaries. Does the page lack information, miss a crucial condition, bury its answer, or address a fundamentally different task? Can one additional section close the gap, or does the query deserve its own page? And when does broader coverage create useful depth versus a collection of partially answered questions? Throughout, we’ll put a deceptively simple SEO proposition under scrutiny: how far can providing the right answer take you?

What Really Works in SEO Today? The biggest SEO Meta SEO Study

I compiled 30,000 documents, filtered them down to 9,249, and found 182 tactics with evidence behind them.

I spent the summer trying to solve SEO, AEO and GEO with actual science. I did not solve them. What I did get is 182 tactics that have real evidence behind them, and a much better idea of which numbers in our industry you can stand on.

TBD

After party