The Future of Dataveillance in Advertising Theory and Practice

Abstract

Abstract Technological developments have changed the advertising landscape by extending the possibilities to collect, process, and share consumer data to optimize advertising. These developments have made data collection and consequently dataveillance—the automated, continuous, and sometimes unspecific collection, storage, and processing of digital traces—central concepts for advertising scholarship and practice. Studying the impact of consumers’ perceptions of dataveillance is important as perceptions about data collection practices have been shown to diminish the effects of data-driven advertising. This article advances advertising theory by conceptualizing the impact of consumers’ perceptions of dataveillance in digital data-driven advertising and applying long-standing advertising research theories to this new phenomenon to provide an overarching framework for future research. The current work presents the dataveillance effects in advertising landscape (DEAL) framework, with specific research directions for future research. This framework has practical implications as it shows how false or accurate beliefs about dataveillance impact consumer responses to digital data-driven advertising. Advertisers may adapt to ensure that digital data-driven advertising does not result in backlash or raise ethical questions. Finally, the framework has implications for privacy regulations, as consumer understanding of data collection is a core issue in current regulatory approaches to dataveillance.