Insurers need to be diligent when trying to reduce the churn. They have to question whether it is worth trying to retain all the customers who have the tendency to churn.
Let me try to explain this using a scenario from Life Insurance Industry. For example, Assume a set of customers have been identified whose churn probability is higher than others. All these customers had cleared financial underwriting conditions originally. If Life time value (LTV) is refreshed for such customers before initiating churn reduction activities, it may turn out that some of them are not profitable at all.
In these circumstances, Insurers would be better off if they focus only on profitable customers.
In the past, it used to be a major challenge to identify customer profitability at the customer level. Typically all customers would be contacted for renewal of their policies simultaneously based on the previous personal data available within the Insurers' systems. Now with abundant technical capabilities in the analytics space (SAS or R or any other platform) built on the basis of strong statistical models and data from internal / external sources, it will not be that difficult to track the profitability at individual customer level. Carrier may increase their focus on profitable policy owners.
Here is a simple approach.
Step 1: Identify set of customers who are likely to churn
Step 2: Refresh their life time value (in other words refresh the customer segment)
Step 3: Check the profitability of customers and map them to benchmark values
Step 4: Identify key reasons why profitable customers want to breakaway
Step 5: Initiate cross sell if the churn reason is either 'under-coverage' or 'does not meet the need'.
Step 6: Launch customized campaigns to promote cross-sell opportunities within profitable customer segment
This approach assumes that the insurer has benchmark values for profitability, agreed customer segments, good quality of data and strong technology capability like SAS or R or any other platform for executing the models