Customer Lifetime Value Prediction: Using Machine Learning to Forecast CLV and Enhance Customer Relationship Management

In today's cutthroat corporate realm, consistent innovation and market adaptability don't cut it; mastering client relationships is key. A pivotal metric here is the Customer Lifetime Value (CLV), shedding light on long-term profit potentials per customer, an understanding of which is critical for business growth. A study delves into enhancing Customer Relationship Management (CRM) using machine learning to refine CLV predictions. Conducted collaboratively, it explores CLV's role in marketing, client segmentation, and resource optimization before delving into its measurement. Using advanced machine learning tools like regression, clustering, and neural networks on a rich dataset of customer transactions and behaviors, it's found that machine learning significantly outperforms traditional CLV estimation methods. This leads to better CLV accuracy and paves the way for enhanced resource allocation and targeted marketing, further emphasizing CLV's importance in crafting personalized customer journeys and refining CRM strategies amidst a constantly evolving market landscape.