Data-Driven Innovation for Sustainable Customer Relationships: Analyzing the Impact of Online Generated Content on Customer Lifetime Value

This study examines the impact of Online Generated Content (OGC) on Customer Lifetime Value (CLV) through advanced machine learning and text mining techniques analyzing User-Generated Content (UGC) and Marketer-Generated Content (MGC). Based on Social Learning Theory, our findings reveal that positive sentiment reviews and high ratings significantly enhance CLV, while review quantity demonstrates a non-linear relationship with CLV. Brand pricing and promotional activities also positively influence CLV. We propose a data-driven framework enabling businesses to optimize resource allocation through advanced analytics for more sustainable customer relationships. By integrating big data analysis with sustainable business practices, this research contributes to bridging data-driven innovation and sustainability in e-commerce environments, offering actionable insights for developing resource-efficient marketing strategies while maximizing customer value.