Nudges are simple and effective interventions that alter the architecture in which people make choices in order to help them make decisions that could benefit themselves or society. For many years, researchers and practitioners have used online nudges to encourage users to choose stronger and safer passwords. However, the effects of such nudges have been limited to local maxima, because they are designed with the “average” person in mind, instead of being customized to different individuals. We present a novel approach that analyzes individual differences in traits of decision-making style and, based on this analysis, selects which, from an array of online password nudges, would be the most effective nudge each user should receive. In two large-scale online studies, we show that such personalized nudges can lead to considerably better outcomes, increasing nudges’ effectiveness up to four times compared to administering “one-size-fits-all” nudges. We regard these novel findings as a proof-of-concept that should steer more researchers, practitioners and policy-makers to develop and apply more efforts that could guarantee that each user is nudged in a way most right for them.
Eyal Peer, Serge Egelman, Marian Harbach, Nathan Malkin, Arunesh Mathur, and Alisa Frik. Nudge Me Right: Personalizing Online Security Nudges to People’s Decision-Making Styles. Computers in Human Behavior, Volume 109, August 2020, 106347.