Artificial Intelligence in Customer Value Management: Predictive Analytics, Personalization, and Strategic Implications for Sustainable Business Growth

Abstract

Artificial Intelligence has revolutionized customer value management by enabling predictive analytics and hyper-personalization at unprecedented scales. This research examines the transformative role of AI-driven technologies in enhancing customer lifetime value, retention rates, and sustainable business growth. Through analysis of recent empirical data and industry implementations, this study demonstrates that AI-powered predictive analytics achieves up to 98% accuracy in churn prediction while enabling personalized customer engagement strategies. Organizations implementing AI in customer relationship management report 33% increases in customer lifetime value and significant improvements in retention rates ranging from 15% to 89%. The research methodology employed systematic literature review and quantitative analysis of industry data across sectors including retail, telecommunications, and financial services. Key findings reveal that AI-driven personalization through recommendation engines, sentiment analysis, and dynamic pricing strategies significantly enhance customer satisfaction and operational efficiency. However, challenges including data privacy concerns, algorithmic bias, and implementation complexity persist. This paper contributes to understanding AI's strategic implications for sustainable business growth while identifying future research directions in ethical AI deployment.