Challenges and Future Directions of Computational Advertising Measurement Systems [journal]

Three people with connection above they head illustration

Conference

Journal of Advertising – August 5, 2020

Authors

Joseph T. Yun, Claire M. Segijn, Stewart Pearson, Edward C. Malthouse, Joseph A. Konstan (professor), Venkatesh Shankar

Abstract

Computational advertising (CA) is a rapidly growing field, but there are numerous challenges related to measuring its effectiveness. Some of these are classic challenges where CA offers a new aspect to the challenge (e.g., multi-touch attribution, bias), and some are brand-new challenges created by CA (e.g., fake data and ad fraud, creeping out customers). In this article, we present a measurement system framework for CA to provide a common starting point for advertising researchers to begin addressing these challenges, and we also discuss future research questions and directions for advertising researchers. We identify a larger role for measurement: It is no longer something that happens at the end of the advertising process; instead, measurements of consumer behaviors become integral throughout the process of creating, executing, and evaluating advertising programs.

Link to full paper

Challenges and Future Directions of Computational Advertising Measurement Systems

Keywords

computational advertising, social computing, human computer interaction (HCI)