Shelf gaps, out-of-stock events, and pricing errors are visible, universal, and costly, and they are the fastest place to prove what agentic AI can actually do. Yet most retailers and brands still catch these signals in dashboards long after the sale is lost, slowed by cross-functional misalignment and a real-time visibility gap. Closing that loop, turning signals into action automatically, is where the next wave of grocery value lives - and it depends on a measurement and intelligence foundation built for the task.  That foundation unifies fragmented retail and media signals into an integrated Media Data Lake, then layers on AI-powered insights, audience and journey analytics, and multi-touch attribution to move brands and retailers from seeing a problem to acting on it in real time.

Join this Strategic Lab to work through how autonomous retail execution turns real-time signals into recovered sales, using a simple Detect, Decide, Act framework- with a privacy-safe data foundation and AI intelligence that powers each stage. This is a highly interactive, peer-to-peer workshop, not a set of presentations. You will see a live demo of agentic retail execution, work the same problem from both the retailer and brand perspective, and leave with a playbook, plus optional design tables to scope a first project for your organization.

Shelf gaps, out-of-stock events, and pricing errors are visible, universal, and costly, and they are the fastest place to prove what agentic AI can actually do. Yet most retailers and brands still catch these signals in dashboards long after the sale is lost, slowed by cross-functional misalignment and a real-time visibility gap. Closing that loop, turning signals into action automatically, is where the next wave of grocery value lives - and it depends on a measurement and intelligence foundation built for the task.  That foundation unifies fragmented retail and media signals into an integrated Media Data Lake, then layers on AI-powered insights, audience and journey analytics, and multi-touch attribution to move brands and retailers from seeing a problem to acting on it in real time.

Join this Strategic Lab to work through how autonomous retail execution turns real-time signals into recovered sales, using a simple Detect, Decide, Act framework- with a privacy-safe data foundation and AI intelligence that powers each stage. This is a highly interactive, peer-to-peer workshop, not a set of presentations. You will see a live demo of agentic retail execution, work the same problem from both the retailer and brand perspective, and leave with a playbook, plus optional design tables to scope a first project for your organization.

Shelf gaps, out-of-stock events, and pricing errors are visible, universal, and costly, and they are the fastest place to prove what agentic AI can actually do. Yet most retailers and brands still catch these signals in dashboards long after the sale is lost, slowed by cross-functional misalignment and a real-time visibility gap. Closing that loop, turning signals into action automatically, is where the next wave of grocery value lives - and it depends on a measurement and intelligence foundation built for the task.  That foundation unifies fragmented retail and media signals into an integrated Media Data Lake, then layers on AI-powered insights, audience and journey analytics, and multi-touch attribution to move brands and retailers from seeing a problem to acting on it in real time.

Join this Strategic Lab to work through how autonomous retail execution turns real-time signals into recovered sales, using a simple Detect, Decide, Act framework- with a privacy-safe data foundation and AI intelligence that powers each stage. This is a highly interactive, peer-to-peer workshop, not a set of presentations. You will see a live demo of agentic retail execution, work the same problem from both the retailer and brand perspective, and leave with a playbook, plus optional design tables to scope a first project for your organization.

Shelf gaps, out-of-stock events, and pricing errors are visible, universal, and costly, and they are the fastest place to prove what agentic AI can actually do. Yet most retailers and brands still catch these signals in dashboards long after the sale is lost, slowed by cross-functional misalignment and a real-time visibility gap. Closing that loop, turning signals into action automatically, is where the next wave of grocery value lives - and it depends on a measurement and intelligence foundation built for the task.  That foundation unifies fragmented retail and media signals into an integrated Media Data Lake, then layers on AI-powered insights, audience and journey analytics, and multi-touch attribution to move brands and retailers from seeing a problem to acting on it in real time.

Join this Strategic Lab to work through how autonomous retail execution turns real-time signals into recovered sales, using a simple Detect, Decide, Act framework- with a privacy-safe data foundation and AI intelligence that powers each stage. This is a highly interactive, peer-to-peer workshop, not a set of presentations. You will see a live demo of agentic retail execution, work the same problem from both the retailer and brand perspective, and leave with a playbook, plus optional design tables to scope a first project for your organization.