Business Opportunities for Banks based on Customer Segmentation
Banks today are constantly under pressure in this high-competitive industry to innovate. Even if the market is concentrated, entry restrictions are low for new banks and exit conditions as easy for unprofitable institutions. Add to this, with technology available at everyone’s finger tips, offline banking & personal relationship management has taken a back-burner. With lesser visibility on the customer and understanding their needs closely with F2F communication & relationship building, understanding the customers’ needs via their online footprint and its augmented parameters has become mandatory for banks and a tricky proposition to deal with.
Customer Segmentation is a way of bifurcating a large and extremely diverse customer base, in every way possible, into smaller focused groups of customers with related attributes that are overlapping and relevant to the bank’s marketing of their products and services. Segmentation criteria varies from geography to demography to behavioral. Through customer segmentation, banks can get to know their customers’ needs better and provide them more customized products and services.
However, prior to reaching a conclusive direction, we need to understand the basic aspects which are leveraged today for targeting the customers’ ROI and how it is failing on considering some critical areas.
Background
Return on Investment (ROI) is one of the critical metrics used by the business owners and banking marketing department heads. They need clear visibility on how their investments are contributing towards business objectives and their bottom line. A better & focused way to calculate it will help companies define their direction and amount of their spends.
Traditionally, ROI gets calculated by:
However, this equation doesn’t provide the required depth of understanding on every customer’s lifetime value, his engagement with the product or a customized marketing strategy which needs to be implemented.
For a better insight, especially from marketing perspective, an approach to calculate it is:
Again, this is too simplistic to identify the specifics or getting the appropriate directions. For closing these gaps and achieving the appropriate ROI value, Customer Lifetime Value (CLV / CLTV), Lifetime Customer Value (LCV), or Life-Time Value (LTV) are commonly used to determine the profitability of customer relationship and how much the company should ideally spend on their marketing and customer acquisition.
To understand a more detailed perspective to calculate this formula, we need to understand the internal metrics:
1. Average Order Value (AOV) = Total Sales Revenue / Total Number of Orders
2. Purchase Frequency (F) = Total Number of Orders / Total Number of Unique Customers
3. Gross Margin (GM) = Total Sales Revenue — Cost of Goods Sold (COGS) / Total Sales Revenue
4. Churn Rate = (# of Customers at End of Time Period — # of Customers at Beginning of Time Period) / # of Customers at Beginning of Time Period
5. Customer Lifetime Period (LTP) = 1/Churn Rate
Immediate advantages are visible with this formula and how it can be leveraged further:
1. Smaller Micro-Segments
2. Dynamic Segmentation Models
3. Future model strategy
Hence it is evident the Customer Lifetime Value is crucial for providing a deeper insight into the customer behavior. Value that customers bring to the organizations is one important aspect. However, can we segregate customers further to have them under pin-pointed focus groups based on their personas and behavioral attributes?
Understanding Personas and their Banking Needs
Every generation predominantly brings different flavors as customers. However, with the advent & adoption of technology, the bifurcation lines between customer personas has blurred.
For this article purposes, below are the 5 category types of customers assumed for simplicity purposes:
1. Money Movers: Long-time Bank customers who have good understanding of Bank’s products and services
2. Emergents: Migrated customers exploring services and products for greater adoption
3. Senior Traditionalists: Senior citizens, HNIs
4. Mid-income Loyalists: Average Bank Customers
5. Potentials: Typical Gen Z customers
As seen above, dividing customers based on their banking needs helps banks understand their behavior better. In very simplistic terms, Money Movers will necessitate customized products, Emergents will need to be informed about latest products & services, Senior Traditionalists will eye for personal relationships, Mid-income Loyalists will look for better loan rates and Potentials will look for trust factors.
Business Opportunities for Banks
With the understanding of Customer Lifetime value and with better understanding of the customers’ needs, can Banks segregated of their customers to specific groups and identify good business opportunities for improving their engagement & business potentials with the customers.
Once a bank is able to categorize and understand the customer they are working with, they can use software and bring in appropriate experiences to learn how to best assist them. To name a few examples of these banking segments and how they might be approached by Banks for relevant services and marketing:
· A young family living in the city outskirts in a small house, who have a high net worth. This customer segment could align with candidates looking for home loans to move into a bigger house.
· An existing bank customer who owns a business and has so far availed only one car loan from the bank. This customer segment can be targeted for multiple new services and products like onboarding in business banking, enabling new line of credit, or providing loans for acquiring new equipment.
· A customer who has lesser amount in accounts but who has also been flagged as an accredited investor. This customer segment can be a potential candidate for private banking or wealth management services.
· A long relationship holding customer who has a high net worth and a teenager child and having a debit card provided. This customer segment can be targeted with student loans for their child or information sessions on how to help their child build credit history using a credit card.
This customer segmentation, combined with business analytics and Artificial Intelligence/Machine Learning, can help financial institutes calculate precise Customer Lifetime Value and ROI. Digital transformation techniques to build an intuitive & engaging experience across various channels can enable this data segregation to be spotted and leveraged in an optimal fashion, but that’s for another day!
