The predictive demand model: Bridging historical data and markdown optimization

How predictive demand models serve as the critical bridge between historical sales data and prescriptive markdown optimization, providing both demand estimates and uncertainty quantification

Cyril NoirotMarch 25, 20256 min read

Cyril Noirot

Analytics consultant specializing in marketing science, forecasting, and strategic data solutions. Passionate about bridging the gap between advanced analytics and business impact.

Data Science

From lifecycle limits to markdown rules: The product constraints behind retail profit optimization

Why retailers can't escape markdown pricing—a deep dive into the lifecycle, inventory, and pricing constraints that shape modern retail optimization strategies

May 156 min

Data Science

Concavity and Network Flow in Profit Optimization: How Diminishing Returns Enable Efficient Solutions

Understanding why retail revenue functions are concave, how this property enables convex optimization, and the network flow interpretation that powers modern markdown pricing algorithms

May 157 min

Data Science

Inside the profit optimization problem: From price uncertainty to prescriptive decision-making

How retailers transform predictive demand models into prescriptive pricing decisions through stochastic programming, jointly optimizing markdown prices and inventory allocation under uncertainty

May 15 min

Cyril Noirot

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From lifecycle limits to markdown rules: The product constraints behind retail profit optimization

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Inside the profit optimization problem: From price uncertainty to prescriptive decision-making