Prof. Dr. Christine Eckert

Marketing analytics enables firms and policymakers to make data-driven decisions by uncovering patterns in consumer behavior, quantifying the impact of marketing activities, and forecasting outcomes under different scenarios. The range of phenomena I investigate is broad, from detailed models of individual consumers’ psychological processes to models that link firm performance back to marketing activities. Research in this context has been published in the Journal of Marketing Research, the Journal of the Academy of Marketing Science, and the International Journal of Research in Marketing. My current focus is on modeling the impact of technology-enabled service personalization on consumer behavior and firm performance. 

This interdisciplinary project develops consumer-centred approaches to mitigate the harmful effects of confusion in complex financial decisions, such as home loan choices. These decisions often involve high stakes and cognitive overload, leading to individually and socially costly outcomes. We build comprehensive models that capture financial product complexity, consumer heterogeneity in preferences and capabilities, and the role of advice-taking in shaping decisions. Our research examines how and when consumers seek, trust, and follow financial advice, and how this behavior interacts with confusion and market outcomes. Using advanced statistical methods, we estimate the benefits of clearer decision environments and effective advice. Outcomes include new models of complex financial choice, insights into the mechanisms of advice-taking, and evidence on the behavioral and welfare impacts of decision confusion. Results of this research have been published for example in Management Science, Review of Finance and Journal of Economic Behavior and Organization and have been cited in government reports (e.g., Treasury Australia).

This research stream focuses on understanding how tobacco control policies shape perceptions and behaviors among smokers and non-smokers. Across studies, the unifying aim is to empirically test how regulatory interventions such as plain packaging, graphic warnings, flavor capsule bans, and differential risk messaging influence tobacco appeal, initiation, and cessation. The work usually employs choice modeling techniques to detect differences between consumers and evaluates whether industry claims about market behavior hold against behavioral evidence. Taken together, these studies aid in the design of targeted, evidence-based policies that reduce tobacco harm without unintended consequences. They have been published in the journal Tobacco Control and influenced the public debate on the development of warning labels, particularly the inclusion of social warnings.