Investigating The Effective Factors In Enhancing User Experience Through Real-Time Recommendation Systems

Improving user experience is one of the main goals of real-time recommendation systems. In competitive markets, providing a superior user experience through advanced recommendation systems can differentiate companies from their competitors. By focusing on the identified effective factors, businesses can allocate their resources more efficiently. Instead of making broad investments across various aspects of recommendation systems, they can concentrate on specific areas such as algorithm accuracy or user customization features to achieve the greatest improvements in user experience. This study investigates the effective factors in enhancing user experience through real-time recommendation systems. Using exploratory factor analysis, five key factors have been identified that significantly impact user experience: Personalization, Timeliness, Algorithm Accuracy, Diversity of Recommendations, and User Control and Customization. Personalization enhances user satisfaction and engagement by providing content or products relevant to user preferences. Timeliness ensures that users quickly access relevant recommendations at the appropriate time. Algorithm Accuracy improves user experience by increasing the correctness of the recommendations. Diversity of Recommendations prevents user fatigue and boredom by introducing a wide range of options. User Control and Customization allow users to adjust and refine their experience based on their specific needs. The results of this study indicate that focusing on these factors can substantially improve user experience and increase user satisfaction with real-time recommendation systems.

Keywords:

user experience , real-time , recommendation systems