Targeted Advertising Strategies on Television

Abstract

The personal video recorder (PVR) facilitates the use of targeted advertising by allowing companies to monitor television viewing behavior and to build demographic profiles of viewers from the data that are collected. Our research explores the extent to which an advertiser should allocate resources to increase the quality of its targeting. We present a game-theoretic model that extends the conventional measurement of targeting quality by exploring the trade-off between two measures: accuracy and recognition. Accuracy measures the likelihood that any target segment prediction is correct, while recognition conversely measures the likelihood that any member of the target segment is identified. We find that the relative resources allocated to improving accuracy and recognition depend upon the size of the population of viewers, the propensity of viewers to skip commercials, the overall cost of airing commercials, and the competitive environment. Furthermore, the incentives to improve accuracy are markedly different from those to improve recognition. Although improving accuracy does not affect the extent of price competition, improving recognition leads to intensified price competition and reduced profitability in the product market. Thus, when facing a competitor that pursues a strategy to improve its recognition of potential customers, an advertiser should choose to reduce its investment in recognition and increase its investment in accuracy.