A leading manufacturer and distributor of paper products was facing significant customer churn, negatively impacting both revenue and long-term growth. The company lacked an integrated data platform to identify and retain at-risk customers, resulting in lost business opportunities. We implemented a centralized data solution that unified customer data from various sources, allowing for real-time analysis of customer behavior. By automating machine learning pipelines and deploying a sophisticated churn prediction model, the company could take proactive steps to retain at-risk customers. Self-service analytics tools empowered business teams to explore customer data and make data-driven decisions, increasing operational efficiency and improving customer retention strategies.