THE VALUE OF DETAILED CUSTOMER DATA
UNDERSTANDING + PERSONALIZATION
“ We are not utilizing the power of statistical analysis on unavailable data for making decisions with long term consequences ”
“ Credit cards aren’t banking -- they’re information. ”
“ Banks are not utilizing IT to collect data ”
Richard Fairbank + Nigel Morris Stanford and London Business School MBAs (both at Mercer Management Consulting) worked together on a project where they researched unprofitable operations at a bank.
Credit card companies in the 1980s charged everyone the same interest rate: 19.8% . Let’s think about why charging all credit card customers the same interest rate might be a problem. WHY PERSONALIZE ?
For illustration, let’s imagine a simple world in which the average customer defaults on their credit card with a 15% probability. As a credit card issuer, we might choose a single interest rate that is fair for that level of risk.
Generic Applicant 15% default probability
Mountain Biker 10% default probability
Baseball Dads
20% default probability
But suppose in reality there are two types of people in this world: mountain bikers , who are low-risk customers with a 10% default probability, and baseball dads , who are high-risk customers with a 20% default probability.
by charging a single interest rate we are undercharging the high -risk baseball dads & will lose money on these customers. IN THIS CASE,
We are also overcharging the low-risk mountain bikers . Over time, they may leave us for competitors who offer them better & more accurate prices...
AND WE’LL BE STUCK WITH ALL THE BAD CUSTOMERS.
WHY SEGMENT ? The point is that we will better compete in this marketplace the better we can understand our customers and their risk profiles. Of course, the real world is much more complicated in that a real credit card company has a lot of variables on which to segment its base of customers and so we can potentially CATEGORIZE OUR CUSTOMERS into lots of tiny buckets.
Single Female age 35-39, zip codes 27500-27599, income $50K-$70K, holds another Capital One card, annual charges between $5000 - $7500, rejected a previous offer in the last 6 months, & purchase frequently from Amazon.com
How can a company understand the behavior of its customers at such a granular level? Certainly it requires lots of data + sophisticated analytics.
To make matters worse, customer behavior changes over time , so Capital One needs to be constantly learning about its customers.
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