This study explores the transformative potential of machine learning (ML) in digital marketing, focusing on its application to customer segmentation. It aims to identify and analyze key performance indicators (KPIs) such as model accuracy, customer retention, and marketing ROI, which measure the effectiveness of ML-driven segmentation. By examining the influence of technical and organizational factors, including data quality, algorithm selection, and company culture, this research proposes actionable and sustainable strategies for deploying ML solutions. Emphasizing scalability, governance, and environmental impact, the study bridges the gap between theoretical frameworks and practical adoption, offering a comprehensive approach to responsible and effective ML integration in diverse organizational contexts.