Key Promotional Drivers for Market Leadership
A leading insurer faced persistent customer attrition, notably during the Annual Election and Open Enrolment Periods. Mu Sigma responded with advanced analytics, revealing key drivers for a focused retention strategy during critical periods.
Our response aimed to address the immediate attrition challenges and provide our client with a robust framework for continuously refining their retention strategies.
Understanding Customer Profiles
We analyzed behavioral and demographic data and created distinct segments based on product type, usage, and payment patterns. We then evaluated promotional activities targeted at various customer segments to optimize our approach and better cater to specific customer groups.
Choosing the Right Predictive Model
We evaluated three predictive model algorithms — Survival Analysis, Logistic, and Recurrent Approach Models — to determine the most suitable fit. The selected model enabled the concentration of retention efforts, ensuring the optimal utilization of available budgets.
Refining Messaging for Better Targeting
We then analyzed retention drivers, identified potential customer attrition, and devised strategies to maximize the return on investment (ROI). Our recommendations included adjusting the product mix and timing of promotions to optimize ROI for customers at risk of attrition effectively.
Business Impact
-
11%
Increase in sales from at-risk customers
-
Delivered
Key customer retention metrics to ensure future-readiness
-
Retained
High-value customers
Mu Sigma is the world's largest pure-play big data analytics and decision sciences company. Through our Art of Problem-Solving, we strive to scale and systematize better decision-making through business intelligence services. Mu Sigma works across the entire decision support ecosystem (data sciences, data engineering, and decision sciences) with Fortune 1000 companies worldwide, including 140+ Fortune 500 companies.
The firm's is derived from the statistical terms "Mu" and "Sigma," which symbolize a
probability distribution's mean and standard deviation, respectively.
