Strategies for Delivering Personalized Digital Experiences Using Modern Content Platforms

Authors

  • Sai Phaneendra Manikantesh Kodete College of Arts & Sciences, Sacred Heart University, Fairfield, Connecticut, USA Author

DOI:

https://doi.org/10.32628/IJSRST251307

Keywords:

Strategies, Delivering, Personalized Digital Experiences, Modern Content Platforms, Machine Learning

Abstract

The evolving digital landscape requires viable strategies for tackling the rising issues associated with the digital world. Besides, to attain appreciable success in digitalized customer services, engagement and relations, and brand differentiation, user experience has to be strategically personalized. This study explores the strategies for delivering personalized digital experiences using modern content platforms, focusing digital experience platforms (DXPs), AI-driven personalized engines, and headless content management systems (CMS). The study demonstrates how organizations can leverage content intelligence, user data, and behavioral analytics for the creation of vibrant context-aware user experiences across diverse touchpoints. It analyzes real-time personalization, modular content architecture, and omnichannel delivery. The study also shows how machine learning predicts user preferences and automates content recommendations. It helps address issues of content governance in personalization, the complexities of integration, and data privacy. By virtue of the foregoing coverage, the study shows that strategic and tech-driven organizations are not only integrating technologies at a significant extent, but also deploying content strategy, customer data, and technological infrastructure to effectively deliver personalized experiences and attain scalability, which both foster positive business results and user engagement.

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Published

15-07-2024

Issue

Section

Research Articles

How to Cite

Strategies for Delivering Personalized Digital Experiences Using Modern Content Platforms. (2024). International Journal of Scientific Research in Science and Technology, 11(4), 687-695. https://doi.org/10.32628/IJSRST251307