How can a CSM identify a customer at risk of churn?

Identifying a customer at risk of churn is a proactive process that hinges on understanding customer behavior and interaction with the product. Analyzing engagement and product usage data is essential because it provides insights into how customers are utilizing the services or products. This analysis can reveal patterns indicative of dissatisfaction, such as a sharp decline in usage or lack of engagement over time.

By examining metrics like login frequency, feature usage, and service requests, a Customer Success Manager (CSM) can detect early warning signs that a customer may be considering leaving. This data-driven approach allows the CSM to take targeted actions to address concerns before they result in churn, fostering a healthier relationship and ultimately improving customer retention.

In contrast, the other options either rely on a passive approach (waiting for the customer to reach out) or fail to address the customer's underlying issues (offering immediate discounts or ignoring negative feedback), which won’t effectively mitigate churn risk. These strategies may overlook the need for meaningful engagement and understanding of customer satisfaction.