Abstract: In one example, a method includes monitoring user interaction with a modified computing environment for a period of time and detecting a plurality of groups of users, each group of users corresponding to a different initial time of interaction with the modified computing environment. The method also includes generating a metric for each of the groups of users, the metric corresponding to an action in the modified computing environment initiated by the users in each group. Additionally, the method includes generating an impact curve corresponding to the modified computing environment based on aggregated metrics for each of the plurality of groups of users and disabling the modification to the computing environment in response to detecting values along the impact curve are below a threshold value.

Abstract: In one example, a method includes monitoring user interaction with a modified computing environment for a period of time and detecting a plurality of groups of users, each group of users corresponding to a different initial time of interaction with the modified computing environment. The method also includes generating a metric for each of the groups of users, the metric corresponding to an action in the modified computing environment initiated by the users in each group. Additionally, the method includes generating an impact curve corresponding to the modified computing environment based on aggregated metrics for each of the plurality of groups of users and disabling the modification to the computing environment in response to detecting values along the impact curve are below a threshold value.

Abstract: The present disclosure describes a method that includes retrieving segmented data relating to a selected factor concerning a user, retrieving real-time data relating to the selected factor, and providing a communication to the user if both the segmented data and the real-time data meet one or more preselected conditions.