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A Conversation About Social Media

Customer Equity Management in Banking

Many banks follow one of the two mainstream growth strategies: harvesting their existing customer base or pursuing competitors’ customers.

Large banks usually opt for the former strategy, while smaller banks often choose the latter. In either case, banks are fishing for the same fish in the same pond. Banks of every size bombard customers and prospects with marketing communications and aggressive cross-sell efforts—steadily deteriorating customer experience. Yet all indicators on a CEO’s dashboard may be positive, so a bank’s eroding customer equity is overlooked. The result is frustrated customers.

Logic underlying these banking strategies is usually similar: Entice the customer with an offer he can’t turn down, sell the first product, then try to deepen the relationship by selling more banking products, and do this while the bank is reducing costs. When departments are evaluated on this basis they are ostensibly working towards their individual targets. Branch management is happy about branch profitability, the alternative channels department sees a migration of customers to less costly channels, and the marketing department is pleased with the outcome of cross-sell campaigns. The bank’s earnings are on track.

What, then, is the problem?

The problem with the way banks judge their performance is twofold: 1) Customer equity is nowhere in the picture, and 2) targets are set so as to propagate previous years’ mistakes. True, the bank may be hitting its earnings growth targets, but is it really creating maximum value from its customer base? As long as the question remains unanswered, management may be destroying shareholder value.

Measuring and managing customer equity is a means for answering this question. It is arguably the next frontier in how banks set their targets and craft strategies to reach those targets. In fact, it should be the basic criterion in every business decision made in a bank.

Unfortunately, few companies apply customer equity in everyday management. However, even with their complex operations, banks can integrate the basics of banking business with customers’ needs and preferences.

Imagine two banking customers: Customer A is female, 28 years of age, single with no kids. She has €45,000 in her savings account and averages €3,000 on monthly credit card charges. Customer B is male, 45 years of age, married with two kids. He has the same products and about the same volume as Customer A. Which customer is more valuable to the bank? How should their value be managed? Exceptions notwithstanding, many banks will answer as follows: “Both customers are of the same value and we should try to increase the value by cross-selling new products.” Both customers are then bombarded by offers ranging from no-commission mortgage offers to auto loans to checking account services.

The picture may look very different when viewed through the eyes of the customer: Suppose Customer A’s intention is to own a home of her own within the next five years and then plan for her retirement. She likes simplicity in her life and works with no other bank. Customer B, on the other hand, is a bargain hunter and keeps his money wherever he finds the highest interest rate. His only aim in life is to save for his kids’ college tuition. He has many credit cards and flits from offer to offer.

Customer equity is very different for each of these customers, and so is the way to retain and grow this equity. But banks seeing only part of the picture treat both customers the same way, missing an opportunity to grow customer equity.

Increasing the return on each customer
Return on Customer, a proprietary methodology developed by Peppers and Rogers Group, helps banks manage their customer equity by asking a simple question: Are you creating more net present value (NPV) from each customer than you spend on him? The idea is to manage the bank’s customer portfolio as if customers were assets on the bank’s balance sheet. If the bank can see a customer’s full profile, it can attach a value to that customer that represents the NPV of possible cash flows from the customer.

If Customer A’s intention is known, for example, the bank can safely assume that she will probably use a mortgage product when she has reached an adequate level of savings. In fact, the bank can even assign probabilities to the price range of the apartment the customer is likely to buy. Customer A’s rate of savings accumulation provides the timeframe during which she is most likely to use the mortgage loan.

Obviously, we are only talking about probabilities here. She may end up not using a mortgage loan at all. That is why managing a customer portfolio is the same as managing a portfolio of securities. Customer A’s inability to increase her savings at her usual rate, her getting married, and her transferring a chunk of her savings elsewhere are all indicators that will change the value of her “stock,” i.e., her customer equity. Stock traders are trading billions of dollars’ worth of bank stocks daily based on what they think banks will be doing in the future. Why not replicate the same on a customer portfolio?

All of this requires that the bank take a different look at how it interacts with customers, as well as how it collects and analyzes customer data. Despite the seemingly complex nature of their retail products, banks are really selling only three products: credits, deposits, and credit cards. Reasons for use of these products depend on each customer’s demographic and needs profile. There are surprisingly few variables that draw from 80 percent of the profile, including marital status, age, gender, children, and home ownership.

Probabilities for future banking behavior can be assigned with much less uncertainty than one might believe if the bank sees the full profile of a customer rather than just the trail he has left on the bank’s systems through transactional data and basic demographics. This is only part of the picture.

Banks need to step away from highly complex data mining methodologies that seek to derive meaningful insights from incomplete data. There needs to be three components of data analysis: 1) a properly structured market research program that maps customer equity across the market; 2) a carefully devised customer interaction program that asks the “golden questions” that complete a customer’s needs and preferences profile; and 3) transactional data—a customer’s imprint—left on the bank’s systems. Most, if not all, banks see only the third component. More often than not the result is customer segmentation that provides little insight and unrealized customer equity.

Applying customer equity management and Return on Customer will change everything banks do—from setting next year’s targets to reporting financial statements. Even the design of a new campaign and the evaluation of its performance should hinge on whether the campaign creates more customer equity than the investment made. This will be the next frontier in banking, and early adopters are sure to gain an advantage that cannot be replicated by their competition.