ChurnVis: Visualizing mobile telecommunications churn on a social network with attributes

Abstract

In this paper, we present ChurnVis, a system for visualizing components affected by mobile telecommunications churn and subscriber actions over time. We describe our experience of deploying this system in a network analytics company for use in data analysis and presentation tasks. As social influence seems to be a factor in mobile telecommunications churn (the decision of a subscriber to leave a particular service provider), the visualization is based on a social network inferred from calling data between subscribers. Using this network, churn components, or groups of churners who are connected in the social network, are segmented out and trends in their static and dynamic attributes are visualized. ChurnVis helps analysts understand trends in these components in a way that respects the data privacy constraints of the service provider. Through this two pipeline approach, we are able to visualize thousands of churn components filtered from a social network of hundreds of millions of edges.