Guides, case studies and research on Enterprise Decision AI, causal modeling and unified growth planning from DATA POEM.
AI is reshaping marketing mix modeling, from open-source Bayesian models to causal structure learning. What's changing, and what it means for your budget.
See how Fortune 500 retailers use AI for demand forecasting, personalization, and supply chain, and where most retail AI investment still falls short of the P&L.
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.
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