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, a SaaS-based insurance aggregator with headquarters in the US, works with more than 300 insurance partners and offers more than 120 different product categories to its 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.
Impact Analytics was engaged by the client to help identify drivers of customer attrition and develop unique analytics-led strategies for customer retention.
In its application of business analytics to churn as the challenge, Impact Analytics 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.
Step 1: Identifying drivers of customer churn
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.
Step 2: Customer segmentation
Impact Analytics then applied advanced statistical models such as a mix of absolute and fuzzy k-means clustering to classify customers with similar behavior patterns into segments.
Step 3: Identifying levers of 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.
Step 4: Developing intervention strategies
Some of the key insights that emerged from the analysis are:
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
Impact Analytics developed robust intervention strategies which recommended a shift in target from massive new customer acquisition to preservation and retention of existing ones. These intervention strategies enabled the client to formulate and deploy targeted retention strategies.
Impact Analytics’ analysis of customer behaviour and product preferences, and strategies for customer segmentation and risk identification enabled the client to considerably reduce attrition by 22%.
The resulting churn reduction delivered an incremental 4% top line growth to the next quarter.
Intervention strategies recommended by Impact Analytics and deployed by the client ensured retention of high value customers.