Identifying actual customer potential set against customer value exploited by the bank
HDFC Bank Limited (Housing Development Finance Corporation) is an Indian banking and financial services company headquartered in Mumbai, Maharashtra. It has 88,253 permanent employees as of 31st March 2018 and has a presence in Bahrain, Hong Kong, and Dubai. HDFC Bank is India’s largest private sector lender by assets. It is the largest bank in India by market capitalization as of February 2016. It was ranked 69th in the 2016 BrandZ Top 100 Most Valuable Global Brands.
As of October 9, 2018, the bank’s distribution network was at 4,805 branches and 12,260 ATMs across 2,657 cities and towns.
Before working with KENTRIX, HDFC Bank classified its customer base mainly by the business its clients did with the bank. Thus, HDFC Bank could not securely identify customer potentials where income proof was not available to the bank. Further, insufficient transaction data from individual clients did not yield enough data for profiling and customer segmentation.
HDFC Bank is required for the next level of customer acquisition and customer service with reliable profiles of their individual customers. As per RBI (Reserve Bank of India), customer names and contact details cannot be shared outside the bank.
The KENTRIX Solution
KENTRIX profiled the total HDFC Bank customer base by geo-coding the residential addresses. The client IDs were then allocated to the KENTRIX micro-market cells. From the KENTRIX profiling data HDFC Bank acquired the consumer lifestyle affinity segmentation data, income, and a range of product purchase affinities.
Based on the customer profiling delivered by KENTRIX, the bank identified approx. 30% “undersold“ customers, i.e., clients having a significantly higher potential to bank with HDFC valued against their current customer value to the bank. Within three months of the project’s start in 2017, the bank realized an average 24.8% conversion rate on re-targeting these identified customers, a significantly higher conversion rate than it used to be before.