Can artificial intelligence help operators prevent customer churn and revenue drain?
Global mobile operators collectively lose tens of billions of euros annually, to customer churn. The impact of churn on a mobile operator’s profitability is of consequence.
Churn impacts the operator’s financials in several ways. Firstly, operators lose the future revenue that a churned customer can provide. Secondly, all the marketing investments and resources used to acquire the customer are lost.
Operators typically spend astronomical amounts on getting customers, even though the cost of retaining an existing customer could be as much as 50 times lower than acquiring a new client. This is a vast, yet relatively unexplored and potentially profitable opportunity for mobile operators.
Systematic churn prevention requires predicting and behavioural modelling based on a vast amount of data living in several locations on the network, and gets continuously updated.
Could artificial intelligence and big data be applied in an economical way to help operators turn around their churning customers? This needs dedicated resources and investments in big data analytics and machine learning, which would be able to detect low signals and see correlations that normal rule engines or humans cannot see.