David & Goliath: Big Bank Deposit Acquisition Tech for Community Financial Institutions
In the previous two articles, we’ve discussed strategies for growing deposits from the existing customer/member base. It’s now time to look outside the financial institution for new deposits and beyond traditional advertising practices.
One of the advantages of working with a lot of financial institutions is the ability to overcome data scarcity problems that enable the use of algorithmic techniques that have historically been confined to larger financial institutions with tens of millions of customer records. For example, a financial institution with 25,000 customers and a 10% annual attrition rate has to spend marketing money to replace 2,500 customers per year. Let’s further assume that only 20% of those lost customers are profitable, that means that only 500 of those lost customers have desirable characteristics for new account acquisition. That’s just not a large enough sample to build a robust lookalike audience in most major social media sites (e.g. Meta), which require on the order of 5,000 records to build a robust lookalike audience for target marketing.
Why is the ability to build a lookalike audience important in the quest for new customers? Answer: Because customer/member acquisition cost and the quality of those acquisitions matter. Lookalike audiences are important because they allow a desirable audience to be defined using one set of attributes (e.g. deposit balances, credit scores, profitability), and then find a similar and desirable audience using different attributes (e.g. interests, group membership, political affiliation).
These ideas come together into a powerful acquisition strategy when aggregated data sets containing tens of millions of customer deposit records are used to create a seed or source audience from which the major social media platforms can build a robust lookalike audience.
For example, let’s say a financial institution’s operating footprint is 25 counties across 2 states. And that financial institution wants to acquire deposit customers who demonstrate the capacity to make large deposits into the bank as shown in Figure 1.
Figure 1 – Anomaly large depositors make deposits that are far above their average deposit balance over previous periods.
The financial institution knows who these people are but, unfortunately, there are only 95 of them in the database; far below the threshold to build a robust lookalike audience. However, for Micronotes, this is a soluble problem because we can find about 10,000 anomaly large depositors in our aggregated client database. Once those 10,000 records are published as the source or seed audience for the lookalike audience, the remaining work in creating a target audience is to impose the requirement that lookalikes be confined to the two states and 25 counties in which the financial institution operates. Then, of course, a compelling offer must be made to convert those lookalikes into customers or members.
In future articles, we’ll discuss the performance of lookalike campaigns and how they enable small financial institutions to fully compete with larger financial institutions in new customer/member acquisition.
