From Data to Relationship: Exploring Consumer Data Sharing for Personalization
(A2025-125900)

AUTHORS

Mark Elsner, Wiesbaden Business School; Jessica Knauß, Wiesbaden Business School and Goethe University Frankfurt; Julia Kraft, Deutsche Börse

ABSTRACT

As firms increasingly rely on diverse data types for personalization, understanding consumers' willingness to disclose data is critical. This study investigates how different self-reported data types and personalized incentives influence data-sharing decisions, employing a choice-based conjoint analysis (N=164) across two product contexts. Our findings reveal that personalized monetary incentives are the most effective motivators, while content-based incentives significantly reduce sharing intentions. Online reviews authored by individuals are the most preferred data type for disclosure, whereas socio-demographic data shows context-dependent variability. These preliminary insights contribute to marketing literature by highlighting the role of personalization and the nuanced preferences for data types. From a managerial perspective, we emphasize the need to tailor strategies to align with consumer preferences and foster stronger relationships. Further research will extend these findings by exploring additional contexts and real-world settings.