Enhancing User Experience and Satisfaction in Robo-Advisor Platforms: A Multi-Dimensional Analysis of Usability Factors and Interface Design Elements

This research aims to investigate the user experience of customers interacting with robo-advisors and assess their satisfaction levels. The study will identify key usability factors, interface design elements, and personalized features that influence customer satisfaction and loyalty in robo-advisor platforms. By conducting a multi-dimensional analysis, incorporating qualitative and quantitative research methods, this research seeks to provide actionable insights for improving the user experience and enhancing customer satisfaction in robo-advisor services. Robo-advisor is the initiative taken by the many banks to enhance the customer experience also reduce the cost of services. This can be done by using chat bots and there are many other AI enabled services that is provided by banks like face recognition, voice assistance, biometrics etc. Voice-assistance and chat bots are the mostly used robo-advisor services by customers of banks for mitigation of risk. This study conduct to explore the relationship between user experience, satisfaction levels and long term loyalty to robo-advisor platforms. This study used primary and secondary data and secondary data collected from research papers, journals and articles. The investigation synthesises and evaluates pertinent articles and research papers released between 2011 and 2023 using a comparative exploration pattern.