Part 1A: How Do I Better Market to my Existing Customer Base?

New Call-to-action

Part1A: How Do I Better Market to my Existing Customer Base?
In the lending world, everything revolves around customers -- It is the customer who borrows money, the customer who makes deposits, and the customer who either makes payments or defaults. Each of these scenarios ultimately leads to the success or failure of your institution.


So what innovative and cutting-edge methods are available to understand and predict customer behavior? The answer is found as we push past static reporting and rely on Customer Analytics, a data-driven marketing approach to better understand the behavior of individuals and groups of customers.


In this two part series, we explore both sides of Customer Analytics - targeting those within an existing customer base and bringing in first-time customers. In Part I we address this question: How do I better market to my existing customer base?  We’ll outline three practical applications of using data to enhance marketing efforts for financial products: (1) Using wallet share to identify “leakage”, (2) employing pricing gap analysis for targeted marketing, and (3) calculating propensity scores for targeted marketing


Wallet Share


Let’s start with a personal inquiry - do you as a creditor know what portion of the pie you are actually getting among your customers? Meaning, what portion of your customers’ overall financial activity occurs with your institution? Understanding the idea of wallet share helps visualize exactly where and how loans are distributed. Further, it helps a portfolio manager understand where market share is high, and where it is low.


We begin by looking at loan activity within the institution and cumulate the total count and balance of all loans. Applying the same process with loan counts and balances outside the institution, we can compare these two figures side-by-side and get an idea of the share of wallet.


To make the share of wallet most valuable, we can then “slice and dice” the data by different customer demographics (i.e., age, income, credit score, etc.). This would allow an institution to identify and recapture “leakage”, meaning potential business that is being lost to other financial institutions. If an institution is able to identify where this leakage is high, it can use that information to recapture market share by targeting new or existing customers.


Let’s look at an example. Using a demo institution’s data set, say we want to see the share of wallet across customers of a certain age. Merging in data from one of our three credit bureaus, we could stratify this data set into four specific age groups:



With the data segmented in such a way, we can see the overall wallet share across not only our institution, but all institutions (this data is often easily accessible from the credit bureaus). In the top and bottom left figures of the graphic below, we see the overall wallet share by loan count and loan balance. Gray represents the overall wallet share, while blue represents our institution’s portion. On the right, we see these figures as percentages.




From this analysis, we gain perspective on what is really happening. We see that this demo institution has a high penetration among 18-30 year olds when it comes to loan count, but a much smaller penetration when it comes to loan balances. This might suggest that we are losing out on larger balance loans, like mortgage type loans, to other institutions. So one potential targeting strategy might be to make offers to this younger group to recapture some of that leakage. Taking these reports further, we could also see our share of loan count by specific loan type (i.e. autos, mortgages, credit cards, etc) to narrow in our marketing efforts and know exactly what to promote to our customers of this age group.


Our conclusion above is further corroborated by the plots below. Here we see that our institution is only capturing 4% of the younger age group who have first mortgages, compared to 6%, 7%, and 13% of the other age segments.





Using Customer Analytics, we can break down these segments to identify areas of leakage to improve marketing efforts and to ultimately provide the best offers to customers, which in turn improves institution performance.


Keaton Baughan

Product Manager