Optimal Promotion Strategy With Application For Auto Industry

In recent years, domestic auto market keeps booming as the national living standard continuously improve. The number of car owners grows increasingly, and the competition in the auto market is fierce. Many car manufacturers have taken a variety of marketing tools to attract consumers, increase market shares, and increase the profits. Because promotion can provide such an incentive, not only to retain old customers but also attract new customers from competitors, so the promotion is often adopted by the enterprises. Manufacturers need to make decisions about the optimal strategy depending on their market position and customer loyalty. Yet they are often lack of the support tools for decision making. Existing literature had researched extensively the consumers’psychological impact on the promotion decisions. Little had studied about the strategy of promotion for auto market. There are several literature about the optimal strategy of fast consumables, but not about the bulk durables such as cars. In this context, this thesis studies the problem about the optimal strategy of family car promotion.Based on existing research, I apply a Markov decision model to study the car promotion strategy. I first study the customer transfer matrix for the cases of promotion and no promotion. Then, I derive how market shares change according these transfer matrixes. I apply Dynamic Programming to solve the problem. I compare the profits-to-go for promotion and no promotion cases in each periods to determine the optimal strategy. Finally, using numerical studies with applications on auto market, I provides managerial insights on the optimal car promotion policies taking into account of customer loyalty, market share and product life span. Although there are shortfalls and limitations in the study, I try to formulate a quantitative model for auto companies to make promotion decisions and provide some practical guidelines.