Analysis of operational strategies driven by customer analytics: Models and empirics (2012)

This dissertation investigates the underlying customer behavior, (i) conspicuous consumption, (ii) subscription vs. occasional purchase, and (iii) consumption based on online product reviews which have self-selection bias, from both theoretical and empirical perspectives, and address implementable operational strategies for the firms. Consumers often exhibit different purchase behavior due to changing economic environment and unexpected operational actions set by the firm. For example, consumers may derive an additional value from the consumption of an exclusive good unlike the rest of the population. Depending on the customer class, consumers' tendency to purchase a ticket for an orchestra performance may change throughout the season due to ongoing discounts, date and day of the concert, and popularity of the show. If consumers read online product reviews, and if they do not account for the bias in these reviews, they may overvalue the product, hence pay more than necessary. In all such circumstances, pricing with the consideration of distinct consumer purchase behavior, not only helps the firm to control for the unexpected changes in the demand, but also helps the firm to derive additional margins from the changing behavior. To address these issues in detail, we construct both game theoretical and statistical models in which consumers choose whether or not to purchase the product and firms decide on price and quantity strategies. In the first part, we examine a firm's tradeoff between revenues obtained by deciding on a premium pricing with exclusivity vs. pricing with volume with strategic consumers engage in conspicuous consumption. Making the product exclusive follows by an increase in the price, hence an increase in the underage cost. However, high underage cost increases the likelihood for a firm to produce more in order to sell more which contradicts with exclusivity. We investigate a luxury producer's pricing and quantity decisions in the presence of such tradeoff. In the second part, we analyze a consumer's tendency to purchase a ticket for a show using an individual level transaction data from a reputed symphony orchestra in the United States. We explore how subscribers' and occasional buyers' tendency to purchase a ticket change over time due to ongoing discounts, date and day of the concert, and popularity of the show. Using the predictive capabilities of the model, we provide dynamic discounting strategies, which match with the purchase behavior of different customer classes, to increase the revenue generation capability of the organization. In the third part, we explore the impact of self- selection bias inherent in online product reviews on consumers' purchase behavior, and firm's tradeoff between increasing vs. decreasing the price after the posting of biased reviews from an economic perspective. We investigate the more profitable price strategies in such cases by considering the degree of bias in the reviews, the dispersion of consumers' preferences over product attributes and quality attributes, and the capability of consumers to defer their purchases up until they see the reviews.