Two of the hottest buzz phrases among financial marketers are "relationship management" and "customer management."
Massive data bases have given marketers an unprecedented amount of information about their customers, and that has altered the way banks define, segment, and approach their customers.
But every tool is only as effective as the craftsman who wields it, and data-base marketing is still new to many bank marketing professionals. To maximize its benefits, here are five common pitfalls to avoid:
1. Focusing on the data instead of the information. There has been a tremendous surge in data warehousing - billions of bits of information, all cross-indexed, cross-referenced, and statistically analyzed. Marketing is not an exact science, and those rows of hard numbers can give you the comforting feeling of being on solid ground when committing to a million- dollar ad campaign.
Unfortunately, those lengthy reports may not be generating useful information.
For example, most retail banks have begun to focus on the expense of teller activities versus electronic, telephone, and PC banking transactions. They are able to create detailed reports about how many customers tellers see, and what transactions tellers perform. The data is useful in supporting retail branch cost accounting, but provides no insight for a senior manager's next step.
Information is understanding which customers use tellers over and over, which use them infrequently, and which have made the transition to lower- cost electronic banking. Information is knowing what these repeat customers need from tellers, and whether their needs extend to all bank products or just selected services.
When guided by this intelligence, marketing and product managers can devise sound strategies for new products and services. This kind of information enables management to take ownership of the distribution and delivery strategies and be released from the relentless cycles of cost cutting in a vacuum.
2. Developing strategies that aren't rooted in reality. Now that it is abundantly clear how much more profit affluent customers contribute to the bottom line than everybody else, most banks want to pursue that market segment to the exclusion of mass-market customers.
Unfortunately, mass-market customers are five to 18 times more numerous than affluent customers, depending on the neighborhood. Mass-market customers are the bread and butter of the banking business.
The answer is not to ignore them or drive them away with higher fees. Instead, segment not by income but by profitability. Find a way to understand your profitable mass-market customers so that you can attract and keep more of them.
3. Focusing on immediate profit instead of long-term relationships. Data warehouses are helpful in identifying slumps in products sales by divisions, retail sales sites, calendar periods, and other selected variables. Frequently, management's response is a marketing promotion aimed at boosting sales.
Suddenly, platform staff are back in the "pieces" business, selling the weakened product over and over as the flavor of the month.
What is missing from the equation is an appreciation of the customer's overall relationship with the bank. Is the customer's current and long-term profitability such that discussing the featured product today is out of context? Which customer segments should not be sold the product because of high and costly attrition?
4. Not letting information trickle down to front-line people. It's wonderful if bank officers understand what products and services world travelers need, or how they can best serve the special financial interests of parents. But how many customers does a bank officer speak to on a daily basis?
For this information to have an impact, put it in the hands of tellers and other front-line people. If a teller sees that a certain customer writes 30 checks a month, the teller can suggest a business account. If an officer sees overseas activity, the officer can suggest PC banking of automatic bill payment.
The ground floor of the bank lives and breathes on numbers: "Your last deposit was .... You earned interest of ...." It is challenging to insert qualitative, inferential marketing concepts into this numbers-driven world, but it must be done.
5. Expecting to learn everything from your customer data base. The past provides the strongest data for predicting behavior, but it is useless if not seen in context. Counting behavior is not the same as understanding behavior.
Your data base can tell you that Stan wrote 11 checks, made three deposits, and ignored your direct mailer pushing home improvement loans. But it tells you nothing about why he did these things.
Let's take the home improvement loan. Stan is not the only one ignoring your offer-everyone is. You might infer that there simply is not much demand for this product and adjust your marketing activities accordingly.
But if your offer is not competitive, your inference would be wrong. You could buy external data showing your market share and see that you are underperforming in the home improvement loan category.
When properly executed, relationship management might mean that banks earn less per product per customer.
But-and this is a big but-they will earn a larger share of each customer's wallet, they will keep that customer longer, and they will ultimately attract more customers who want to be treated not as a collection of account numbers, but as individuals. Mr. O'Grady is executive vice president and general manager of Claritas Financial Services Group, an Arlington, Va., marketing firm that serves the financial services industry.