Enhancing User Engagement through Adaptive Interfaces: A Study on Real-time Personalization in Web Applications
DOI:
https://doi.org/10.70393/6a6574626d.323332ARK:
https://n2t.net/ark:/40704/JETBM.v1n6a01Disciplines:
Human-Computer InteractionSubjects:
Real-time PersonalizationReferences:
50Keywords:
User Engagement, Real-time Personalization, Adaptive Interfaces, Machine Learning, User Behavior Analysis, HCI, Web ApplicationsAbstract
This study explores the potential of real-time personalization to enhance user engagement in web applications through adaptive interfaces. Although traditional static interfaces are reliable, they often fail to meet the dynamic and diverse needs of users, leading to a decline in user interaction over time. This article proposes a comprehensive model that utilizes machine learning algorithms to adjust network content based on user behavior, preferences, and contextual factors, providing a more personalized experience. Empirical data from experiments shows that adaptive interfaces significantly improve key engagement metrics such as time spent on the platform, click through rates, and user satisfaction. The research findings emphasize the importance of adaptive design principles in enhancing user experience, cultivating user retention, and maintaining competitiveness in the digital environment.
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