Biometric Tools in a Computational Advertising Context: An Overview of Use and Application

Abstract

Biometrics advertising research describes various measures of consumers’ physiological responses to advertising messages that often use computational methods to make inferences about consumers’ psychological processing of these messages. These measures can also be used to fill gaps in our understanding of consumer psychological processes left by the use of traditional computational methods. In this article, we articulate which biometric resources are available to advertising researchers, which psychological processes these measures assess and how they do it, how biometric resources can be applied in advertising research, relative advantages and disadvantages of these measures compared with self-report measures, and how computational processes facilitate their use in advertising research. To frame their application, we organize our discussion of biometric application within a traditional advertising framework, the hierarchy of advertising effects within the attention–interest–desire–action (AIDA) model. We end our discussion by considering laboratory set-up, research design, and data collection considerations, as well as recommendations for advancing advertising research using biometric resources.