Author
Abstract
The integration of predictive analytics with Customer 360 platforms marks a transformative shift in how high-tech enterprises understand and engage with their customers. This technological convergence enables organizations to harness real-time customer insights, automate decision-making processes, and deliver highly personalized experiences across multiple interaction channels. By leveraging advanced machine learning algorithms and sophisticated data processing capabilities, businesses can now predict customer behavior, optimize retention strategies, and enhance service delivery with unprecedented precision. The implementation of AI-driven solutions has revolutionized traditional customer relationship management, introducing automated risk assessment, intelligent market segmentation, and proactive support systems. Through the synthesis of edge computing, federated learning, and quantum computing capabilities, organizations can process vast amounts of customer data while maintaining privacy and compliance standards. The emergence of next-generation customer engagement hubs, coupled with sophisticated analytics frameworks, has established a new paradigm in customer intelligence, enabling businesses to remain competitive in an increasingly digital marketplace.
Suggested Citation
Arthi Rengasamy, 2025.
"AI in High-tech: Predictive Analytics and Customer 360,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 1960-1968, February.
Handle:
RePEc:jbh:ijsrcs:v11:y2025:i1:id:861
DOI: 10.32628/CSEIT251112224
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112224
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