
AI in FMCG: The top use cases transforming global brands
Eight AI use cases global FMCG brands run today, from pricing to agentic AI, and why they need one causal model.
Guides, case studies and research on Enterprise Decision AI, causal modeling and unified growth planning from DATA POEM.

Eight AI use cases global FMCG brands run today, from pricing to agentic AI, and why they need one causal model.

How CPG brands use causal AI to plan trade and retail-media investment across Amazon, Walmart Connect, and Kroger in one model, not three.

A CMO's playbook for reallocating an existing marketing budget by causal contribution, defending it to the CFO, and holding it in a downturn.

What geo lift and holdout incrementality tests actually measure, where each falls short, and where always-on causal measurement fills the gap.

Predictive analytics tells you what will happen; causal AI tells you what to do about it. The methodology difference, and when each one fits.

See the mechanism behind causal AI's replacement of MMM, MTA, and forecasting models for enterprise revenue decisions, and where each still falls short.

AI agents execute marketing decisions at scale. But can they own them? Why LLM agents recommend but don't decide, and what causal reasoning changes.

We define the Large Causal Model, and how it differs from three academic uses of the term and from a standard large language model.

Consolidating data into one warehouse does not stop teams getting different answers. The real fragmentation is in the models. Here is how to fix it.
Let’s talk about how we can help you grow your business.