In our last post, we discussed why analytics will become a necessity to compete in an evolving banking industry. In that article, we promised to follow up with a series of posts that contain specific examples of how analytics can be applied. This first post will discuss how analytics and business intelligence can be used for member segmentation analysis and developing member/customer insights.
Using Analytics for Member Segmentation and Insights
If a member calls into a contact center asking about a fee they were assessed, what would your staff see about this person? If your organization is like most, the contact center staff would see this member’s basic accounts, current balances and maybe recent interactions with the credit union that were tracked in a CRM system. But would they see that this member also had $2 million with your wealth management unit? Or that this individual has a $500,000 mortgage with the credit union on a home worth over a million dollars?
Most banks and credit unions do not possess a complete 360-degree profile of a member’s products and services. This poses several issues that can negatively affect the organization.
Member Segmentation and Insights by Overlaying Profitability
Without a complete picture of the costs and profitability associated with all products and services, member segmentation is at worst impossible and at best incomplete. Overlaying product and service profitability with all products and services owned and used by a member allows you to segment your membership based on net profitability.
What is more profitable – the member with a share draft, a primary share, and a new auto loan who transacts in branch or the member with a primary share, a home equity loan, a debit card, a credit card who transacts using only digital channels?
By segmenting based on profitability, we gain greater insights into our membership while also furthering our understanding of the product and service offering.
How can we leverage this information?
Take one of Progressive’s best features – the competitor price comparison. If you go to Progressive’s website, you can get a quote from them and their competitors all at once.
Why would Progressive want to show you the price of competitors when Progressive might be higher?
They are so confident in their ability to calculate risk-based pricing that they believe if a competitor can offer you a lower rate, then you don’t fit into their desired risk profile. By not fitting into their desired risk profile, Progressive is creating a natural filtering of customers that might end up costing them more in claims payout than in premiums received. They are, in essence, saying “if someone can offer you a lower rate, then we feel you are too risky to be our preferred customer”.
What does this have to do with member profitability segmentation?
Not every member/customer is going to be profitable. But wouldn’t we want to maximize the number of profitable members in our membership? By identifying unprofitable members, we can target market to entice them into more profitable products and services. If your primary marketing effort to acquire new members involves a free checking account with other free benefits, is that really the best strategy? You are most likely acquiring members that tends to be predominantly unprofitable. Consider offering free checking and other benefits if they sign up for a more profitable product or service. Instead of gaining unprofitable members, your marketing now acquires profitable members which your CFO will most certainly be excited about.
These relatively simple business strategies can only be accurately designed with profitability data that allows for member segmentation.
Member Segmentation by Channel Usage
What about channel usage?
How does a primarily digital member, like myself, differ from a member who does all of their banking in a branch? What about one who frequently contacts the call center? By understanding which of our members use digital channels – and how frequently – it allows us to design marketing and member experience strategies to leverage this information.
If you want to convince me, a digital member, to get a new credit card, the best strategy is not to send me something in the mail. But, what if you could add a credit card offer to the header or a call-to-action in online/mobile banking next time I log on? Your conversion rate will be much higher using this approach than simply blanketing everyone with the same message. The ability to leverage this targeted marketing approach is only possible after segmenting your membership by channel usage.
What would the value be to your organization to identify a member who used to have $10,000 in savings and an average balance of $3,000 in checking but now has only $1,000 in savings and has closed their checking account? This would seem to indicate that this individual has shifted their primary banking operations to another financial institution.
With share of wallet being such a critical metric (especially in highly competitive and saturated markets), being able to identify these individuals is critical. Unfortunately, credit unions and banks tend to struggle when it comes to understanding their member/customer lifecycle.
Ideally, we would want to define triggers that would initiate customer retention measures to re-engage this member/customer before they have completely switched their primary banking activity to another FI. Using analytics and the various techniques that can be employed, an organization can relatively simply identify these individuals and potentially regain a greater share of wallet.
The shift from reactivity to proactivity is a major paradigm shift that analytic organizations embrace. By investing in business intelligence and analytics, banks and credit unions are able to make more effective strategic and marketing decisions through improved member segmentation analysis and insights. These are but a few of the many examples and applications of how you can employ analytics within your FI.
To learn how The Knowlton Group can help you define the proper business intelligence and analytics strategy or if you need help implementing an analytics solution, contact Brewster Knowlton at firstname.lastname@example.org or call 860-593-7842.