Segmenting consumers based on willingness to share data for marketing purposes

Martin P. Block and Don E. Schultz
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Martin P. Block: Professor of Integrated Marketing Communications at the Medill School, Northwestern University, USA
Don E. Schultz: Professor (Emeritus-in-Service) of Integrated Marketing Communications at the Medill School, Northwestern University, USA

Applied Marketing Analytics: The Peer-Reviewed Journal, 2020, vol. 5, issue 3, 243-255

Abstract: Despite new privacy rules and regulations, such as the European Union’s General Data and Protection Regulation and the pending California Consumer Protection Act, not all consumers feel the need for data protection. Recent research has shown that 20–25 per cent of the US adult population are willing to share their personal data with marketers they ‘trust’. The marketing challenge thus becomes how to identify these willing ‘data sharers’. Using a widely available data set, this study illustrates several ‘Big Data-based’ segmentation methodologies to screen this important segment out of the general population, ranging from factor analysis to chi-squared automatic interaction detector (CHAID) decision trees. The results of these analyses identify some unexpected potential segments among these ‘data sharer’ groups, most notably young men who participate in team sports. Thus, the paper argues that rather than looking at privacy regulation as a burden, marketers might well consider it a key element in their toolbox.

Keywords: data privacy; GDPR; CCPA; Big Data; data-sharers; market segmentation (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2020
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