Impact Analytics Enables a US-based Insurance Aggregator to Increase Customer Retention and Reduce Attrition by 22%
Churn Reduction and Intervention Strategies Deliver a 4% Incremental Growth to the Top Line
Marked by globalization and deregulation, insurance companies and aggregators are now accelerating to arrest churn in order to moderate existing process discrepancies, and equip themselves to mitigate future challenges.
Insurance organizations often tend to overlook the first step to tackle churn. They often treat all their customers similarly, and at par, causing the intention of retaining customers seem like a failed exercise. Understanding and addressing customer needs and wants, and anticipating customer intention to abandon are some of the means to arriving at and launching retention-focussed actions.
So what should be considered as a starting point to solving the challenging challenge of churn reduction? What are the key factors that needs to be considered to understand your consumers? How do we understand the needs of the customers?
The client’s marketing team was heavily focussed on both, customer acquisition and retention. The cost of customer acquisition and retention was steadily rising y-o-y. Despite its best efforts, the client experienced an incredibly high churn rate of 15%
y-o-y on its subscriptions. This was severely affecting the client’s bottom line and its growth prospects.
In its application of business analytics to churn as the challenge, IA determined that the first step to tackle churn was to understand their customers, address their needs and preferences, and ensure that profitable customers do not leave the client prematurely.
Impact Analytics identified the key drivers of customer churn in an attempt to understand their customers. Factors like payment methods, lifestyle indicators, social network activities, past customer care interactions, time or duration of the customer with the company and many others were identified as key drivers of customer behaviour and churn.
Once the segments were established, Impact Analytics determined customers that showed a higher probability of churn and assigned them risk probability scores using propensity modelling methods. This led to the identification of the corresponding levers of churn.
- Influencers on social media played an impressive role in the decisions that the customers were making
- Bundling offers helped in retaining clients
- Lifestyle and location-based promos were the best levers to arrest churn