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

• Pinpointed those with best credit profile and propensity to purchase from Bank’s vast spectrum of credit, deposit, investment, insurance, merchant service offerings.

 

 

• Developed a simplified version of a 4-D model combining: customer, product, channel, seasonality factors to strategically map annual marketing campaigns and customer touches/touch points to maximize customer value and revenue.

 

• 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%.