PREDICTIVE PERSONALIZATION: HOW AI CAN PERSONALIZE FRONT-END EXPERIENCES IN REAL-TIME

Authors

  • Nithish Nadukuda Software Engineer, PayPal, USA Author

Keywords:

Predictive Personalization, rtificial Intelligence (AI), Real-time Personalization, User Experience (UX), User Behavior, Machine Learning, Data Analysis, Content Personalization, Recommendation Engines, Customer Engagement, Conversion Rates, Customer Satisfaction

Abstract

Personalized user experiences are becoming a need rather than a luxury in today's digital environment. The idea of Predictive Personalization is examined in this white paper, which is a potent strategy that uses Artificial Intelligence (AI) to customize front-end experiences in real time. AI systems can forecast the requirements and preferences of each individual by examining user data, behavior patterns, and contextual elements. As a result, content, suggestions, layouts, and interactions on websites and applications can be dynamically altered to provide users with a more personalized and interesting experience. The advantages of predictive personalization are explored in detail throughout the study, including higher customer satisfaction, conversion rates, and user engagement. It also examines the many AI methods used, such as data analysis and machine learning. Lastly, the topic of possible difficulties and factors to take into account while applying predictive personalization is covered.

References

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Published

2024-04-30

How to Cite

Nithish Nadukuda. (2024). PREDICTIVE PERSONALIZATION: HOW AI CAN PERSONALIZE FRONT-END EXPERIENCES IN REAL-TIME. INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY (IJCET), 15(2), 176-181. https://mylib.in/index.php/IJCET/article/view/IJCET_15_02_021