AI in High-tech: Predictive Analytics and Customer 360

Authors

  • Arthi Rengasamy Independent Researcher, USA Author

DOI:

https://doi.org/10.32628/CSEIT251112224

Keywords:

Predictive Analytics, Customer Intelligence, Artificial Intelligence, Machine Learning, Data Integration

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.

Downloads

Download data is not yet available.

References

Fabio, "The Impact of AI on Customer Relationship Management," 2024. Available: https://clouddevs.com/ai/customer-relationship-management/

MarketsandMarkets, "Artificial Intelligence (AI) Market in 2024," 2024. Available: https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html

Vaibhav Kumar, et al., "Predictive Analytics: A Review of Trends and Techniques," 2018. Available: https://www.researchgate.net/publication/326435728_Predictive_Analytics_A_Review_of_Trends_and_Techniques

Salesforce, "New Salesforce Customer 360 Innovations Help Businesses Go Digital Faster and Drive Efficient Growth with Automation and Intelligence," 2022. Available: https://www.salesforce.com/news/press-releases/2022/09/14/salesforce-customer-360-automation-intelligence-announcement/

BizAcuity, "Customer Risk Profiling using Machine Learning in Lending," 2024. Available: https://bizacuity.com/blog/customer-risk-profiling-using-machine-learning-lending/

Keith O'Brien, "6 ways AI can influence the future of customer service," 2023. Available: https://www.ibm.com/think/insights/customer-service-future

Nexla, "Data Integration Architecture: Modern Design Patterns," 2024. Available: https://nexla.com/data-integration-101/data-integration-architecture/

Innovative Solutions, "Data Governance in the Age of AI: Ensuring Fair, Transparent, and Accountable Systems," 2024. Available: https://innovativesol.com/data-governance-in-the-age-of-ai/

Anton Ivanchenko, "Measuring the ROI of AI: Key Metrics and Strategies," 2024. Available: https://tech-stack.com/blog/roi-of-ai/

Michelle Slevin, "Measuring Success: AI-Driven Key Performance Indicators (KPIs) and Analytics for Go-to-Market Strategies," LinkedIn Pulse, 2023. Available: https://www.linkedin.com/pulse/measuring-success-ai-driven-key-performance-kpis-slevin-ma-msc--qjv4e

Hemant Kapoor, "The Next Wave of Analytics: Emerging Analytics Trends for 2025 and Beyond," 2024. Available: https://www.grazitti.com/blog/the-next-wave-of-analytics-emerging-analytics-trends-for-2025-and-beyond/

Laurence Goasduff, "Ten Steps to Plan a Next-Generation Customer Engagement Hub," 2016. Available: https://www.gartner.com/smarterwithgartner/ten-steps-to-plan-a-next-generation-customer-engagement-hub

Downloads

Published

10-02-2025

Issue

Section

Research Articles