For banks that don’t specialize in a particular market, it can be difficult to truly know every customer’s changing wants and needs. And while there’s significant customer research available on retail consumers and large corporate clients, there’s less help available when it comes to understanding mid-market corporate customers.
Despite the lack of information readily available, mid-market companies are a fast-growing segment of customers that banks can’t afford to ignore. In fact, a recent Citizens Commercial Banking survey found that a quarter of mid-market companies, defined as having $500 million to $2 billion in annual revenues, are actively engaged in raising capital, while another 40 percent are looking for opportunities to do so. Additionally, more than half of the mid-market companies in the US alone indicated they are actively seeking M&A deals in 2016.
In an effort to capture and better understand commercial customers, banks have historically tried to segment companies based on the value of their annual sales or revenue range (e.g. less than $5 million, $5 million to $20 million, etc.). However, these revenue estimates are extremely unreliable, because typically, mid-market companies aren’t public companies. They have no obligation to report revenue and are not subject to strict audit guidelines. This means that the main metric banks are using to understand their mid-market customers is self-reported, without any independent validation.
But more important than yielding unreliable data, revenue segmentation really doesn’t give banks much insight into a customer’s needs, aside from their credit need or credit worthiness. This is a severely flawed approach to understanding customers because there are so many non-credit products that banks can profit from.
Take payments, for instance. With payments, the needs of a $5 million construction company have little in common with the needs of a $5 million healthcare services company. While technically in the same revenue segment, the two companies have vastly different payment transaction numbers, payment processes and workflow, payables vs. receivables, and enterprise resource planning and accounting systems.
Simply put, revenue is a misguided way for banks to segment their corporate customers, particularly when it comes to the mid-market. Except in rare cases when revenue estimates are actually reliable and indicative of customers’ needs, the knowledge gleaned from a single revenue figure is minimal, and it doesn’t help banks better understand and serve their customers.
The good news is, there are other ways for banks to effectively target customers and strengthen customer relationships. One approach is to use transactional data as a means to develop detailed portraits of customers and their needs. By identifying and segmenting customers by need (rather than revenue), banks can establish stronger relationships and drive new fee income by offering solutions to address those needs. For example, banks could learn a lot about a customer by looking at their outgoing payments. How many payments are they making each month? What methods are they using to make these payments—paper checks, ACH, credit cards, debit cards?
Understanding the volume and value of payments for specific businesses can be extremely valuable for determining how to market and sell existing products more effectively. It can also expose areas where a bank might be failing its customers and losing good grace with otherwise loyal organizations. For example, seeing that a large group of customers is making payments through third-party solutions is an obvious sign that it’s time for a bank to develop a new or better payments solution of its own.
Banks are sitting on literally millions of customer records that can offer invaluable insights into customers’ wants and needs, however this data is often unused or under-leveraged. It’s an unfortunate reality, but one that can be easily addressed.
In today’s golden age of big data and analytics, banks need to leverage far more than just revenue figures to better understand their customers. By failing to fully understand customers, banks won’t be able to serve customers well, and they’ll run the risk of losing customers to hungrier and more innovative competitors as a result. Luckily, the treasure trove of existing transactional data can provide banks with infinite ways to better segment customers, and the breadth of that data will allow them to serve their customers more precisely and comprehensively.