In today's rapidly evolving retail landscape, driven by consumers demand for extreme levels of personalization, smart Digital Signage stands out as a game changer for enhancing in-store consumer experience. In this context, recent technological advancements are empowering the next generation of brick-and-mortar stores to leverage consumer-facing smart technologies that, integrated to smart Digital Signage, would allow to offer unparalleled personalization levels to their customer base. As smart Digital Signage with facial recognition has never been studied, this thesis aims to fill this substantial gap through a comprehensive approach that combines qualitative and quantitative analyses. Consumers’ associations towards the technology and their elasticity to be recognized were investigated, and the existence of strong generational differences have been highlighted. In particular, younger consumers had more positive associations towards the technology and were more willing to be recognized in stores. Then, when studying the incentives that would positively affect consumers’ elasticity to be recognized, the results showed how they do not have enough power to motivate those consumers who showed reluctancy towards the technology. Lastly, the conjoint analysis outlined the best-case scenario for introducing the technology in stores, while the cluster analysis identified distinct consumer clusters within the Italian market highlighting the existence of a specific cluster ready to embrace this innovation. This thesis can be considered the starting point of a new wave of research on smart Digital Signage with facial recognition, essential to be prepared for a retail future that will be shaped by technologies and extreme personalization standards.
- Smart digital signage
- Facial recognition
- Smart retail
- Personalization-privacy paradox
- Personalization
- Mestrado em Gestão e Administração de Empresas
Smart digital signage with facial recognition as in-store personalization enhancer: a study on Italian consumers’ perceptions and elasticity to be recognized during the shopping experience
D'Uonno, A. (Student). 16 Oct 2023
Student thesis: Master's Thesis