Churn analytics is a critical tool for businesses seeking to understand and reduce customer attrition, which is when customers stop using a product or service. This analysis helps companies identify patterns and reasons behind customer departures, thereby enabling them to devise strategies to enhance retention and maximize customer lifetime value. The cost of acquiring new customers is significantly higher than retaining existing ones, so understanding churn is economically beneficial. Churn analytics involves measuring different types of churn—such as subscription, non-subscription, and revenue churn—across various business models. Employing churn analytics software allows companies to track user behavior, identify risk factors, and segment users into cohorts for targeted interventions. By utilizing data-driven insights, companies can make informed adjustments to their products, marketing strategies, and customer service efforts to prevent churn. Through case studies from diverse industries, such as food delivery, messaging apps, and online education, the text illustrates how companies have successfully applied churn analytics to improve retention rates. Ultimately, reducing churn requires a company-wide effort where every department plays a role in ensuring customer satisfaction and loyalty.