Using Data Analytics to Find and Grow Highest Potential Customers
Customer Segmentation – Product & Channel Selection – Profitability
Executive Summary
Provided leading global commercial bank with an innovative marketing and customer relationship management strategy that helped maximize the revenue and profit potential of a select segment of under served, small business customers.
Business Challenge
The retail arm of a commercial bank had no formal pro-active customer relationship management strategy in place to maximize revenue and profit potential of over 200,000 small business customers.
Challenged to create revenue growth from the bottom 60% of the customer-base with limited resources,historically under-performing sales channel, and poor customer data.
Insights
• Recognized, quantified and assigned current wallet and potential value to each of these 200,000 customers using SAS predictive modeling team.
• Data mined and examined over 30 profile variables to pinpoint 3 most important for customer revenue/profitability maximization.
Actions
• Provided customer and product training, goals/incentives, and re-engineered retention and growth programs to most ideal, but under performing channel: telephone sales.
• Communicated and built groundswell support of new strategy with regional sales management and product management partners.
• Created new branch based and service to sales channels increasing customer outbound sales touch by 500%.
Value/Impact
This multi-channel customer relationship optimization model:
- Grew assets under management by $1B.
- Reduced attrition of best 25% customers by 75%.
- Increased loan revenue 37%.
- Moved the number of customers with 3 or more products 40%.