Estimating the rate of unplanned purchasing for small sample categories in retail stores

Abstract The authors proposed a model to accurately estimate the rate of unplanned purchasing of purchased items for each product category. The model is a hierarchical item response theory model that considers consumer heterogeneity and product category hierarchy. Simulations were run using the proposed model for a small sample of in-store survey data that improved the estimation accuracy compared to the conventional method. Analysis was also conducted with the real data, and the rate of unplanned purchasing for each product category was estimated. By reducing the estimation error using the proposed model, retailers and other practitioners can reduce the possibility of errors when creating a sales floor and conducting sales promotions.