Research Based on AiMark Data: Using household panel data to model advertising wear-out, policy effectiveness and the consequences of researcher decisions
(A2026-134251)

AUTHORS

Oliver Koll, University of Innsbruck; bernadette van ewijk, university of amsterdam business school; Hans Risselada, University of Groningen; Karin Teichmann, University of Innsbruck; Harald van Heerde, University of New South Wales Sydney

ABSTRACT

This special session highlights the insights made possible by AiMark's international household and retail panel data, which is widely used in marketing and retail analytics research. The session features three very different research projects that will demonstrate the value of AiMark data in addressing timely topics. Household panel data captures all take-home purchases by a socio-demographically representative sample of households in a country. By linking detailed product information with characteristics of shoppers and retail outlets visited, panel data can inform research on, for example, marketing effectiveness, brand management, metrics, innovation adoption, or the impact of policies on consumer choices. The studies included in this special session are examples of the potential scope of panel-based research. Paper 1 focuses on the effectiveness of advertising by studying the behavioral consequences of wear-out and distinguishing between spending wearout a consequence of prior spending) and content wearout (a consequence of consumer satiation with the ad’s content). Paper 2 investigates the spillover effects by regulating plastic bag availability in supermarkets on plastic purchases across multiple FMCG categories. Paper 3 is a meta-scientific project requiring many analysts to answer the same research question. The paper tries to better understand the consequences of chosen analytical pathways on the heterogeneity of outcomes. The objective of this special session is to enhance the understanding of the suitability of panel data for academic research, and discuss research streams where this data can add to our understanding of the effectiveness of marketing practices.