Observation:

PIM is often viewed as the system of record for product data, while DAM is treated as a separate repository for creative assets. In reality, they're two sides of the same product experience.

Opportunity: 

When product information and digital assets are connected, each becomes more valuable than it could be on its own.

Application:

Most companies believe their product data operations are in good shape. In a 2026 benchmark of 405 manufacturers and distributors, 117 organizations rated themselves fully ready for AI-driven commerce. When tested against operational evidence, not self-reported confidence, zero cleared the bar. 

This session unpacks why the gap between what leaders believe and what their operations show is so wide, and so consistent, across company size and maturity. 

Attendees will leave with three diagnostic questions they can ask their own teams this week.

The challenge:

Selecting the right PIM and PXM solution is one of the most important technology decisions an organization can make. The right choice can transform how product information is managed, improve data quality, accelerate product launches, and enable seamless syndication across every sale and marketing channel.

In the race to scale global marketing footprints, accelerating content delivery is a non-stop climb. Modern marketing requires seamless content distribution globally across a number of channels and essential automation of product data information.

Exploring how the leading technical apparel brand achieves true data continuity through PIM synchronization across the entire content and distribution ecosystem:

DAP is a 160-year-old industrial manufacturer and long-time PIM user. When Kenya Czerwinski joined as the PIM/DAM administrator last year, she inherited a system that had launched but hadn't yet proven it could run the business. The primary issue was a retail syndication effort with major partners that had cost the program credibility.

In this live Q&A, Kenya talks candidly with Justin Alvia of Ntara.   

They’ll discuss:

Share experiences. Network and visit the exhibition live demos to contrast and compare, and talk to those who have the solution you might need.

Across AI, In-Store Experiences, and Online

Context:
Found isn't enough anymore, products need to get chosen. And today, that choice happens across more surfaces than ever before: 

• AI bots and assistants, 
• Generative engine optimization (GEO), 
• In-store experiences, 
• Social commerce, 
• Traditional online shopping.

 Each running on a different kind of product content, even though it all starts from the same source.

How one consumer packaged goods’ company is taking a fresh look at best practice - data quality and integrity are paramount for any PIM integration to be successful. 

Covering:

• The challenges of disparate, disconnected data systems.
• Identifying data gaps between systems.
• Deploying requisite workstreams to achieve data integrity prior to integration implementation. 
• Building a business case for integration.

Context:

Rolling out a PIM strategy might look straightforward on paper. In reality, it's an act of people, processes, technology, and change.

Seen it, done it before:

Experienced practitioners who have met the challenges of PIM transformation share what they know about what it really takes to make it work.