Customer churn is a big problem for most organizations. 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 of 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 need to be considered to understand your consumers? How do we understand the needs of the customers?
Impact Analytics was engaged by the client to help identify drivers of customer attrition and develop unique analytics-led strategies for customer retention.
Step 1: Customer Segmentation
IA’s segmentation solution help formulate better customer centric strategies by refreshing current segmentation modules. New segments were created based on multiple parameters like the patients value, need, insurance and demography. The IA advanced segmentation model took into account complex purchase and engagement activities to calculate cluster scores for customers and allocate them into segments. IA 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 2: 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.
Some of the key insights that emerged from the analysis are:
- Proactive identification of 44,827 at risk patients into low, medium and high risk category, and ensuring adherence to their upcoming appointments
- Identified a $1.1M revenue savings opportunity from 3,413 Extremely High Value & High Value High-Mid Risk patients
- 75,126 ‘likely churned HV customers’ identified to understand their root causes for churn
- 16% of the patients do not pay using insurance; amongst those who do, identified the most popular providers
- Although some of the insurance providers contribute most to the clients patient count, there were other insurance providers having patients with the highest avg. number of patient visit.
- 9.5% of all transactions done through self pay either fail or are cancelled, presenting an opportunity to educate and move patients towards usage of insurance
- Impact Analytics’ analysis of customer behaviour, and strategies for customer segmentation and risk identification enabled the client to considerably reduce patient churn
- The resulting churn reduction delivered an $3.5 Million in revenue boost
- Intervention strategies recommended by Impact Analytics and deployed by the client ensured retention of high value customers.
- Helped client identify potential insurance providers for their salesforce to target
$3.5 Million in revenue boost for a major dental chain through improved customer retention and churn reduction enabled by IA’s AI based customer segmentation solution