LEVERAGING PREDICTIVE BI MODELS TO ENHANCE CUSTOMER LIFETIME VALUE ESTIMATION IN MARKETING CAMPAIGNS
Keywords:
Predictive Business Intelligence, Customer Lifetime Value, Marketing Analytics, Machine Learning, Customer Segmentation, Decision Support SystemsSynopsis
Predictive business intelligence (BI) models have emerged as critical tools for enhancing customer lifetime value (CLV) estimation in marketing campaigns. By integrating machine learning, advanced analytics, and real-time business intelligence, organizations can more accurately forecast customer behaviors, segment markets, and optimize resource allocation. This paper explores the role of predictive BI in improving CLV estimation through a structured review of the alongside a proposed framework for application in marketing technology environments. We present supporting evidence through models, tables, and figures that demonstrate how predictive analytics supports marketing decision-making and increases long-term profitability.
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