Abstract
As traditional bricks-and-mortar retailers reach maturity, it becomes increasingly difficult to keep up with the growth expectations of shareholders. Outperforming the competition requires chain stores to continuously improve shelf productivity and profit contribution. This paper develops a data-driven shelf-space management approach to maximize category profit. It is the first academic contribution to integrate stockout-based substitution with the dependence of demand on allocated space and vertical product positioning into a single shelf-space planning model. To overcome the drawbacks of previous models, we employ a competitive interaction framework distinguishing between effects on total category demand and on products' market shares, resulting from space allocation and product positioning decisions. Moreover, we incorporate merchandising constraints – commonly implied by category managers – into the problem formulation, to ensure the acceptance of the resulting planograms by practitioners. We validate our approach at a leading German grocery retailer, enabling us to obtain all model parameters from solicited customer insights and sales data. We implement the planogram obtained with our method for the packaged bread category at a pilot store of the chain. The realized benefits come very close to the estimates obtained with our model, emphasizing its practical relevance.
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