Predictive Churn Analytics


New subscriber’s have a higher risk to churn in the first few months of joining a CSP. Reducing the rate of churn on new subscribers is important, having won them. 


PCA uses network data to monitor new subscribers to pick-up poor configurations, poor service KPI’s and network issues to provide an indicator of a likelihood to churn. This compliments other churn models which use billing, recharge and level of credit in subscriber balances as data pointers. New subscribers are also profiled to give an early indication of their categorization.


CSPs will be able to reduce the churn rates in new subscribers and retain on-going revenues.


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