Inriver Masterclass: Episode 2 AEO: How to Fix What AI Sees on Your Product Page

Episode 1 showed you why most brands lose visibility to AI: the data already exists in your PIM, it’s just never been mapped into machine-readable output. That’s not a content problem, it’s a feed configuration problem. AI already answers 30–50% of product queries without a single click to your site, and its verdict depends on data most teams have never structured for a machine to read. 

Knowing where you fall short is only the first step. In this, 45-minute session, Steve Vink returns with Joakim Gavelin to show you how to close the gap, live inside a real Inriver PIM environment.  

Episode 1 gave you three actions to start on Monday morning. Episode 2 gives you the complete, repeatable system for scaling that across your entire catalog. 

What you will learn:

• A fast recap. A short refresher on the five dimensions of AI visibility, so the deep dive makes sense even if you missed Episode 1. 
• The five-step plan for structured data.  A concrete, repeatable process for turning unstructured, descriptive content into the schema types AI engines rely on 
• Where your data quietly breaks down before AI ever sees it. We’ll name the patterns most PIM teams never think to check. 
• How it looks inside a real PIM.  A live walkthrough, not slides, showing where to start, how to prioritize, and how to audit progress on an ongoing basis. 
• What “AI-ready” data requires.  Why strong product copy alone won’t earn you a place in AI-generated answers, and what must change in your data model instead.