Companies, large and small are using
Xurmo to improve decision making and
create long-term impact. But across all
industries, decision makers face the kind of
problems that machine learning excels at
solving. Problems like churn, fraud and
A large insurance provider wanted to cluster customers into unique segments and then to identify within those segments, which customers were likely to churn.
The solution involved the Clustering, Classification and Visualization modules of Xurmo. We created a clustering model that allowed our customer to segregate their clientele into eight distinct segments. Classification was used to create a model that could predict with a certain probability estimate as to whether a customer would churn or not. Once the models were created, they were tied to visualizations and presented as an end user application (Dashboard) for the Client's Analysts.
Lowered rate of churn by 20%
Enabled pre-emptive measures to be implemented to prevent a customer churning