Data POEM

Same Budget. Different Architecture. +$130M in Recovered Growth.

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.

Why Siloed Models Leave Money on the Table

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.

How a Causal Model Sees What Siloed Models Can’t

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.

That’s Enterprise Decision AI

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.

Bharath Gaddam

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.

See what Data Poem can do for you.

Let's talk about how we can help you grow your business.