When you use a tool or AI Tracker, you only see what that tool was designed to show you. But the moment you play with the raw data behind a single ChatGPT or AI Mode answer, a completely different reality opens up: the patterns your competitors never see, because their tools were never built to surface them. Take AI visibility. What even is it? Every tool hands you a number, almost none of them agree, and almost none tell you the truth. That's what we learned building our own AI stack across 200+ client cases and two years of experiments.

In this session, Stijn Bergmans breaks down 7 tactics from those cases, no theory, just what's actually working right now. What does "AI visibility" really mean when everyone defines it differently, and how do you measure Answer Share properly? Why tracking streaks beats any one-off visibility score in a world where every answer comes out different. How to find the needle in the haystack: the handful of influential citations that actually shape the answer, while everyone else counts noise. And how to SERP-analyse an AI answer itself, so you can see exactly why you're in it or why you're not.

Then it gets weirder on the shopping side. Agents search far wider and deeper than anything you'd ever prompt yourself, fanning one query out into dozens of sub-queries you never wrote. That's where the pure gold is hiding, and where you can give your products a real head start: you'll see how to uncover those hidden sub-queries, how to force your products into AI comparison tables, and how to reverse-engineer from a product spec straight back to the prompts that surface it.
You'll walk out with 7 tactics you can use on Monday, and the blueprint for an AI stack you can build yourself, so you stop guessing from screenshots and start seeing the data your competitors can't, in a world where nobody googles the way they used to.