How a Fortune 500 brand recovered $130M in growth from the same marketing budget, using POEM365's unified causal model. Same spend, very different result.
I have been to many conferences recently, and the question that keeps coming up is a version of the same thing: “We’ve already spent the budget. How do we get more from it?”
This is a real answer to that question. Not a projection. Not a model output from a demo environment. A Fortune 500 brand. $1.93B in total marketing and growth spend. Every dollar already allocated. Every channel already funded.
POEM365 didn’t add budget. It re-allocated what was already there.
Forecasted revenue: $2.06B. Same total spend. 0% budget variance.
Siloed models optimize each channel in isolation. TV, retail media, trade, pricing — each model maximizes its own ROI. None of them see what the others are doing.
But marketing doesn’t work in isolation.
+11.1% Synergy revenue generated when paid media, retail media, and trade promotion activate together.
Real money sitting in the interactions between channels. Invisible to every siloed model in the stack.
A causal model runs across every driver, every channel, every retailer simultaneously. It sees the interactions. It re-allocates toward the combinations that compound — and away from the ones that cannibalize.
The incremental sales result:
Brand’s own plan forecast: $687M in incremental sales.
POEM365 plan: $809M. +$122M. Same budget.
Not more data. Not more budget. Only unified decisions.
The $130M didn’t come from a bigger budget or a better team. It came from seeing the whole system at once — and optimizing for the interactions, not just the individual channels.
The architecture was the variable. Everything else stayed the same.
Same budget. Different architecture. +$130M.
Founder & CEO
Founder Bharath Gaddam had a clear diagnosis: the problem wasn't data or talent, it was architecture. Correlation-based models were never going to cut it for the complexity of enterprise growth. The industry wasn't under-resourced. It was fundamentally mis-built.
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