Any type of activity such as with on-site browsing and conversions are indicators of engagement and therefore play a role in how we score users from Active to At Risk to Churned.
Definition of Churn Score: A statistical machine learning prediction value that estimates the state of churn for a given user at any given time, evaluating user demographic info, browsing behavior, and historical purchase data among other signals, and factors in our unique and proprietary predictions for how long a user will be a customer. Updated daily for all users who have a minimum of one conversion. These values are supplied in three bands: high, medium, and low Churn Score for campaign targeting and reporting. Values can also be aggregated to the entire user base to arrive at a network-level Churn Score.
Definition of Churn Time: A statistical machine learning prediction estimate of the number of days from the current date that a given user is likely to cease making any future purchases. This model evaluates time data from user browsing and purchase behavior (e.g. sign up time, last time made purchase, last time browsed site/app). The values are aggregated into three cohorts: high, medium, and low Churn Time for campaign targeting and reporting. Values can also be aggregated to the entire user base to arrive at a network-level Churn Time.