How We Increased Incremental Sales by +18% for a Leading European Retailer
How we turned thousands of untracked promotions into a measurable, optimizable channel and proved that personalization beats blanket discounting.
The Story
Promotions are one of the most complex levers in retail. Run too few and you lose traffic. Run too many and you train customers to wait for a deal, quietly eroding your margins. For this retailer, the problem wasn’t the volume of promotions. It was that they had no reliable way to know which ones were actually working.
With thousands of short-term promotions running simultaneously — BOGOs, percentage discounts, loyalty offers — there was no framework to separate genuine incremental sales from discounts given to customers who would have bought anyway. The result: inefficient allocation and margin cannibalization hiding in plain sight.
We solved this by building an MMM framework designed specifically around promotional complexity; capturing both the reach and depth of each promotion, while controlling for seasonality, competitive pricing, and baseline demand. For the first time, every promotion could be evaluated on its true incremental contribution.
Our Impact
+5% Promo ROI Uplift
through smarter budget allocation and reduced cannibalization
+18% Incremental Sales Uplift
through targeted personalized loyalty offers, validating a shift away from blanket discounting toward precision promotion
How We Solved This Large Retailer’s Problem
Problem
With thousands of simultaneous short-term promotions running across SKUs: BOGOs, percentage discounts, loyalty offers, there was no reliable way to distinguish promotions that drove genuine incremental sales from those that simply discounted purchases that would have happened anyway. Spend decisions were based on intuition rather than evidence, leading to inefficient allocation, margin cannibalization, and no clear framework to optimize promotional intensity or targeting.
Solution
We built a rigorous MMM framework purpose-built for promotional complexity, modeling effectiveness along two dimensions: reach (SKU-level availability) and depth (discount size). Full controls for seasonality, baseline demand, and competitive pricing allowed us to isolate the true incremental impact of each promotional mechanic. The model also enabled a direct performance comparison between broad blanket promotions and targeted personalized loyalty offers, giving the client the tools to optimize not just how much they spend on promotions, but how and where.
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