True or False: Predictive models can only be used to identify potential churn.

Predictive models are versatile tools in data analytics and can be utilized for a variety of purposes beyond simply identifying potential churn. While they are indeed effective in predicting churn—helping businesses recognize which customers might leave—they have broader applications across many domains.

For instance, predictive models can forecast customer behavior, such as purchasing patterns, customer lifetime value, and even upsell opportunities. They can also be employed to enhance marketing strategies by determining which customers are more likely to respond to specific promotions or offers. By analyzing historical data, these models can provide insights that help optimize decision-making processes in areas such as customer service, sales forecasting, and inventory management.

Thus, the assertion that predictive models can only be used to identify potential churn is inaccurate. They serve a much wider range of applications, making them valuable tools in various decision-making contexts within business operations.