The Value of Information in Targeted Advertising

Project: Research

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Firms today collect an abundant amount of customer data from various sources, and use this data to target their customers with a high precision. Therefore, it is important that firms know how much, as well as which types, of customer data they should use for targeted advertising. In this research, we analyze a game-theoretic model to identify the value of customer data of different types, and thereby provide practical guidelines for firms' optimal targeting strategy. We consider two types of customer data: category-preference and brand-preference information. These two distinct types of data have theoretically contrasting implications. The first type of data, such as a history of the search keyword laptop computers, indicates attractiveness of a consumer for all firms in a product category, and thus intensifies competition. On the other hand, the second type of data, such as the search keyword Lenovo laptop computers, reveals consumers' preferred brand, and therefore softens competition. By analyzing the opposing competitive effects, we will uncover how firms should design their targeting strategy based on different types of customer data. Our firm-side analysis is complemented by the consumer-side analysis. In particular, we analyze a model of consumer search in which consumers can draw information from targeted advertising and consequently become interested in the product category even though they had no prior interests. Then, consumers can collect more information by searching other firms in the category and decide from which firm to make a purchase. This implies that there is an important tradeoff in each firm's advertising efforts. On the one hand, a firm’s investment in advertising induces consumers' interests in the product category from which the firm can benefit. On the other hand, it induces consumer search for other firms which can benefit other firms. We analyze this main tradeoff in advertising through the consumer-side in order to identify the equilibrium strategy of targeted advertising. This research will make significant theoretical and practical contributions. Theoretically, this research will improve upon the literature in targeted advertising by exploring “how much” as well as “which type” of information used in targeted advertising. Practically, the equilibrium advertising strategy, which accounts for the main competitive effects, will help firms thrive in competition through advertising. Lastly, the research will address concerns of regulators about data privacy. By separately identifying the value of different types of data in targeted advertising, we will discuss which data is more prone to data breach. 


Project number9048159
Grant typeECS
Effective start/end date1/08/1923/06/21