Concentrix implemented a comprehensive AI and machine learning strategy to transform their customer retention approach:

• Predictive Payment Models: Developed ML models to identify customers’ propensity to pay on due dates or within grace periods, enabling proactive engagement with at-risk accounts.
• Revival Strategy System: Created specialized propensity models for lapsed policies to determine which customers were most likely to respond to revival campaigns.
• Surrender Prevention Framework: Implemented predictive analytics to identify policies at risk of surrender, allowing for timely intervention with personalized retention offers.
• Optimized Customer Interactions: Operationalized models to determine the ideal channel, timing, and messaging for each customer interaction based on individual preferences and behaviors.
• Performance Analytics Platform: Deployed interactive dashboards providing real-time insights on performance metrics and highlighting focus areas for continuous improvement.
• Technology Modernization: Re-architected their data infrastructure from legacy SAS systems to a modern Customer Intelligence Platform (CIP), enabling faster analysis and more agile response to market changes.