Podcast | From Complex to Connected: Making Commerce Data AI‑Ready  

About This Podcast

Now available on demand, this LinkedIn Live session hosted by The FMCG Guys and featuring experts from NIQ and Henkel dives into one of the most critical enablers of AI‑driven commerce success: connected, high‑quality commerce data.

As brands face an explosion of data across offline, online, retail media, and digital shelf environments, this conversation cuts through the hype to focus on the real work required to make data usable, actionable, and AI‑ready.

The experts explore why data abundance does not equal data advantage, how fragmentation and complexity are slowing decision‑making, and what foundations brands must build to unlock AI’s true commercial impact from measurement to activation.

What You’ll Learn

From Data Abundance to Data Usefulness 

• Why having more data no longer guarantees better decisions 
• The challenge of complexity across omni‑commerce data sources 
• How connectivity transforms fragmented data into actionable intelligence 

Why Commerce Data Complexity Has Exploded 

• The impact of off‑platform channels (social, programmatic) and on‑platform ecosystems (retail media networks) 
• How walled gardens, regulations, and disconnected platforms fragment insights 
• Why misalignment across teams prevents insights from turning into action

AI Readiness Starts with Foundations—not Algorithms 

• Why most complexity lives in data acquisition, structuring, and harmonization 
• The foundational role of complete sales, retail, and consumer data 
• How robust infrastructure and causal modeling enable AI to work effectively

Data Connectivity: A Prerequisite for AI Impact 

1) The three core commerce data layers:  

• Offline data 
• Online & digital shelf data 
• The ability to connect both cohesively

2) Why AI value collapses without connected dataset

3) Understanding the “garbage in, garbage out” reality of AI systems

Why Data Completeness Is Non‑Negotiable 

• Why AI cannot fix incomplete or inaccurate data 
• How AI scales errors when inputs are flawed 
• The role of accuracy, consistency, and completeness as minimum standards     

Governance, Quality & Organizational Readiness 

• Why speed without data quality leads to poor decision‑making 
• Readiness as a strategic capability, not just a technical one 
• How AI will widen the gap between mature and immature organizations

From Measurement to Actionability 

• How AI is shifting focus from insight generation to execution 

• The link between strong data foundations and faster commercial activation 

• Why AI‑driven agents still depend on clean, connected systems

Defining the Minimum Standard to Move the Needle 

1) The growing need for an industry baseline across:  

• Data accuracy 
• Granularity 
• Update frequency 

2) Why correlating search visibility, ratings & reviews, and content performance is essential 

3) Clarifying:  

• Which teams must be involved 

• Which partners and platforms matter most

The Pragmatic Path Forward 

• Why perfection is unrealistic—but progress is achievable 

• How iterative improvement delivers value faster than waiting for flawless data 

• Why brands that start now will outperform those that delay