Optimizing Decisions in Agent-Led Commerce
Agentic Commerce
E-commerce is moving from search & scroll to predict & approve. As AI assistants increasingly act as the first buyer, websites lose relevance and decision systems take center stage. This session explores how agent-led shopping works in practice: from intent detection and shopping graphs to prediction, optimization, and human approval. It shows why retailers must shift their focus from storefront optimization to decision quality, providing high-quality data, clear constraints, and economic targets so AI systems can select them profitably. Drawing on real-world experience from large-scale pricing systems at Zalando and current work at 7Learnings, the presentationoffers a concrete playbook for pricing, marketing, and inventory in a post-website commerce world.
Time & Place
Wed, March 25
16:30 - 16:45
The Ritz-Carlton Berlin
Grand Ballroom II
Roundtables & Theatre Seating
Max. Capacity: 150 Seats
Meet Your Intructors

Felix Hoffmann
CEO, 7Learnings
Felix Hoffmann is CEO of 7Learnings, where he builds AI systems that automate and optimize commercial decisions in retail, especially pricing, promotions, and demand. Previously, he led pricing initiatives at Zalando, giving him a practitioner’s view on how predictive models translate (or fail to translate) into margin, sell-through, and operational reality. Today his work focuses on decision automation: turning fragmented commerce data into decision-grade signals that AI agents can act on.
What To Expect
Who Is This For?
E-commerce leaders
Pricing leaders
Retail strategists
AI product teams
Marketing leaders
Pre-Requisites
No Prerequisits
What You'll Learn & Do?
How agent-led shopping decisions work
From search to prediction commerce
Building high-quality shopping data systems
Optimizing pricing for AI buyers
Decision systems beyond storefronts
Agenda & Activities
Agenda for this session
10 min presentation
.png)