Allocation AI
A Bayesian budget-allocation engine that decides where Heineken's marketing money earns the most — steering €3.2B in annual spend from intuition to evidence.
What Allocation AI does
Every year Heineken's operating companies face the same question: where should the next marketing dollar go? Five million on TV, or on trade promotions? More weight behind Heineken, or a local power brand? Historically these calls leaned on experience and last year's plan.
Allocation AI answers it with evidence. It builds a Bayesian response model for each OpCo, brand and channel, learning how sales actually react to investment. The core output is a set of response curves — spend on one axis, expected volume or ROI on the other — that let teams test budget scenarios before committing a cent.
An optimizer then reads those curves and proposes the allocation that maximizes return within real strategic constraints: brand-role rules, long-term brand-building floors, and short-term sales limits.
A powerful model no one outside data science could use.
Response curves and Bayesian priors are trustworthy to statisticians and invisible to the commercial leaders who actually sign off budgets.
Asking a market director to hand budget authority to a black box is a hard sell. The output has to be legible, arguable, and overridable.
Whatever we built for one pilot market had to hold up across dozens of OpCos, each with its own brands, channels and data quality.
Owning the layer between the model and the decision.
From three years of data to one allocation.
Regression models trained on 3+ years of data separate sales growth into ATL, BTL, commercial levers and control factors.
Bayesian priors are built and updated per touchpoint, then models are trained and aggregated for each distinct channel.
Each curve maps spend to expected volume and incremental ROI, simulating impact at every spend level.
The optimizer weighs 250+ ROI projections at once, allocating to the best touchpoints within the Brand Role Framework.
A structural shift, staged over years.
Replacing intuition-based budgeting with precision modelling compounds — pilots prove the lift, global rollout scales it.
First deployments established the baseline: measurable revenue gains from smarter allocation alone.
Optimizing ABTL allocation across top OpCos, at a cost-to-achieve of roughly €16M — a ~19× return.
The enterprise-scale target as the capability rolls out across every applied market under the EverGreen strategy.
The KPIs behind every allocation.
- ›Return on Investment (ROI)
- ›Gross Profit (GP) impact
- ›Gained volume
- ›Sell-out volume per channel
- ›ATL touchpoint spend
- ›BTL budget contributions
The macro engine of a three-part system.
Allocation AI sets the sandbox — how much each channel and brand gets — that Smart Flighting and Promo Advisor then execute against. Allocation secures the funding; Smart Flighting schedules the impact; Promo Advisor executes the offer.
Sets the annual budget across OpCos, brands and channels.
Stretches each budget across the calendar for maximum pressure.
Fills the calendar with the specific winning promo mechanics.