Estimating and Optimizing the Impact of Inventory on Consumer Choices in a Fashion Retail Setting

Abstract

Problem definition: In fashion retailing, the display of product inventory at the store is important to capture consumers’ attention. Higher inventory levels might allow more attractive displays and thus, increase sales in addition to avoiding stockouts. Academic/practical relevance: By knowing how inventory levels affect consumer choices, retailers can adjust their inventory levels so as to maximize sales or profits. Methodology: We develop a choice model where product demand is indeed affected by inventory and controls for product and store heterogeneity, seasonality, promotions, and potential unobservable shocks in each market. We empirically test the model with daily traffic, inventory, and sales data from a large retailer at the store-day-product level. Results: We find that the impact of inventory level on sales is positive and highly significant, even in situations of extremely high service level. The magnitude of this effect is large: each 1% increase in product-level inventory at the store increases sales by 0.62% on average. This supports the idea that inventory has a strong role in helping customers choose a particular product within the assortment. Managerial implications: We describe how a retailer should optimally decide its inventory levels within a category and describe the properties of the optimal solution. Applying such optimization to our data set yields consistent and significant revenue improvements compared with policies that ignore the impact of inventory on sales.

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