Churning is the movement of customers from a company to another. For any company, being
able to predict with some time which of their customers will churn is essential to take actions
in order to retain them, and for this reason most sectors invest substantial effort in techniques
for (semi) automatically predicting churning, and data mining and machine learning are
among the techniques successfully used to this effect. In this paper we describe a prototype
for churn prediction using stream mining methods, which offer the additional promise of …

… Show potential of stream mining techniques in churn prediction scenarios: Able to keep
prediction rules updated at all times Business value of fast reaction to changes Show
current churn patterns and profiles for detailed analysis Ability to suggest optimal retention
actions … Prediction Manager: Based on the MOA (Massive Online Analysis) stream mining
software “Adaptive Hoeffding Tree” prediction method Processes records from active
customers (Events) and injects occasional records for inactive customers Keeps queue of …