Interpreting conditional probability

You're analyzing data for a subscription-based company to predict whether a customer will cancel their subscription, also called churning. Initially, 10% of all customers churn. The company also tracks engagement behavior and finds:

Customer Behavior	Probability
Churn rate among low engagement customers	40%
Churn rate among high engagement customers	5%

A customer is flagged as low engagement. The probability for low engagement is 30%.

Using a Bayesian approach, how should you interpret this customer's churn risk now that you know engagement is low?