Essays on consumer promotion timing expectations and promotional response and manufacturer\u27s sales promotion decisions

Forward-looking behavior of consumers is important for modeling consumer response to promotions of frequently purchased consumer products as well as manufacturer’s optimal promotion schedule. The first essay studies consumer’s promotion timing expectations and promotion response. In previous studies, consumers’ price promotion expectations have been modeled using a first-order Markov (FOM) process. However, theoretical analyses and empirical evidence of the timing of promotions suggest that price promotions occur in cycles whose periodicity is stochastic. If promotions are cyclical, consumer expectations can be expected to incorporate this cyclicality. Therefore, in contrast to previous studies, we utilize a Proportional Hazard model (PHM) to characterize consumers’ expectation of future price promotion. Consumers are assumed to incorporate their expectations consistent with this model into their dynamic brand and quantity choices. Using scanner panel data from the canned tuna category, we first empirically show that the PHM fits the price promotion incidence data better. Second, our estimation results indicate that a structural model employing a PHM specification for promotion expectations fits the data better than one that assumes only a FOM price promotion expectation. Third, we show that promotion elasticities are overestimated by a structural model that assumes only a FOM promotion expectation. Fourth, we show using an analysis of promotion policy changes that a structural model with a FOM expectation can lead to suboptimal managerial decisions. Lastly, we consider policy simulations in which consumers learn about policy change in a Bayesian fashion. The second essay investigates a manufacturer’s optimal timing and depth of price promotions over a planning horizon in a frequently purchased packaged goods context. Promotion policy is the equilibrium outcomes of a dynamic game between consumers and the manufacturer. Consumers form expectation over future promotions and strategically time their purchase to coincide with the manufacturer’s promotion events. The forward-looking manufacturer takes this consumer behavior into account and dynamically evaluates promotional response of consumers in each choice segment based on their inventory levels when making optimal promotion decisions. Our analysis comprises of two steps. In the first step, we obtain heterogeneous demand side parameters with a dynamic structural model. Consumers decide whether to buy, which brand to buy and how much to buy conditional on their rational expectations of future promotions. In the second step, we specify a dynamic game between consumers and the manufacturer and solve for the optimal promotion policies, taking the structural demand-side parameters from the first step as given. Our empirical analysis is based on household level panel data in the canned tuna category, which comprises two major brands—StarKist and Chicken of the Sea. We focus on studying StarKist, the market leader’s promotion decisions. The estimates of the demand-side model imply that there are two segments of households in the investigated market. Households in segment one have a strong preference over StarKist and are less promotion sensitive. We name households in this segment loyals. Households in segment two are very sensitive to promotions and have weak preference over StarKist. We name households in segment two brand switchers. Conditional on these demand characteristics, we find that it is optimal for the manufacturer to promote when the mean inventory for brand switchers is sufficiently low and the optimal discount depth decreases in the mean inventory for brand switchers. We empirically measure the extent to which forward-looking behavior by consumers affects the manufacturer’s optimal promotion policy. We find that StarKist promotes less often with shallower discount when consumers become myopic. StarKist benefits from consumer’s forward-looking behavior by allowing switchers to stockpile. Moreover, StarKist’s profit can be greatly hurt if it assumes forward-looking consumers to be myopic