This article focuses on the estimation of the total price-elasticity of demand, decomposed in brand choice and quantity price-elasticity, and it discusses the implications of such decomposition for a specific product category, using a scanner data sample of Brazilian households. Two models were used: the brand choice decision was modeled through the conditional logit based on household utility maximization; the decision of how much to buy was modeled through classical linear regressions. Regarding the validity, the first model demonstrated a satisfactory prevision power of brand market share. Managerial implications include specific price decisions to each brand, as the nature of the price-elasticity decomposition varies among brands.
price-elasticity; logit model; scanner data