Identifying Instagram user segments based on privacy perceptions and attitudes towards online behavioral advertising
(A2025-130260)

AUTHORS

Beáta Sikó, University of Szeged

ABSTRACT

The evolution of the digital advertising and the effectiveness of personalised marketing are creating new challenges for advertisers, especially in the areas of privacy concerns and the need for relevant content. The aim of this research is to explore how Instagram users' attitudes towards personalised advertising and privacy perceptions differ from each other. The following six segments were identified through a cluster analysis: non-targeted skeptics, knowledgeable data providers, concerned data protectionists, resigned accepters, over-targeted haters, and non-utilitarian ad supporters. The research highlights that the effectiveness of data-driven advertising depends not only on the technical implementation, but also on the perception and control of users over data use. Precise targeting is not enough for the success of future digital marketing: it is important to ensure user satisfaction through authentic communication and real choices.