Sarcouncil Journal of Public Administration and Management

Abstract: The integration of artificial intelligence (AI) into SaaS product analytics and customer experience optimization has emerged as a game-changer in the software industry. This study explores how AI-driven analytics can transform raw data into actionable insights, enabling SaaS companies to enhance user engagement, predict churn, and deliver personalized experiences. Using a mixed-methods approach, we analyzed user interaction data, customer feedback, and predictive modeling outcomes to evaluate the effectiveness of AI in optimizing SaaS products. Key findings reveal that AI-powered tools, such as gradient boosting machines and sentiment analysis models, significantly improve churn prediction accuracy (92.5%) and customer satisfaction. User segmentation through clustering techniques further enables targeted strategies for different user groups, while A/B testing confirms the effectiveness of AI-driven interventions in reducing churn risk by 10% and increasing feature usage by 15%. Despite its potential, the adoption of AI in SaaS raises ethical and technical challenges, including data privacy concerns and model interpretability. This study highlights the importance of responsible AI implementation, emphasizing transparency and compliance with regulations like GDPR. By leveraging AI, SaaS companies can unlock new opportunities for growth, innovation, and customer-centricity, positioning themselves for success in a competitive market