Unleashing Branch Power at Fleet

• Creating a Marketing Customer Information File. This is the first step that many banks explored in the 1980’s. Accounts for many of the bank’s different products – many of them housed on different computers in different formats – were brought together once a month, reformatted, and householded, to produce a single consolidated statement for each customer. Many used that statement to produce a consolidated monthly report to the customer, although most did not.
• Computing customer profitability. This was the next logical step which many banks have been exploring in the 1990’s. For each product owned by each customer, the bank figured out the revenue and the costs involved. For banks the computations were quite complicated, involving interest revenue and costs, the cost of capital, transaction fees and costs, maintenance costs, product sales costs, provision for losses, etc. The software is extensive. Each variable (interest rates, capital hurdle rates, etc) is subject to monthly changes. The output of the process is a monthly new profit (or loss) figure for each customer in the bank.
• Segmenting customers by profitability. Once banks learn the profitability of each customer each month, they are often profoundly shocked. They discovered, as one large bank did recently, that half of their customers are unprofitable. In addition, they found that bottom 20% of their customers are very unprofitable – often involving sizeable losses for the bank. To get a grip on this situation, banks have begun to segment their customers into profitability quintiles. In these segments, typically 100% or more of the bank’s profits come from the top 20% of the customers. The other 80% represent a little more than break even or a dead loss.
• Managing customers based on their profitability segment. Once you know that a customer is losing you money every month, if you want the bank to prosper, something has to change. You can reprice the unprofitable customer’s products, try to change her costly habits, encourage her to buy additional profitable products, or find a way to gently ease her towards the door. Branch personnel are furnished with information about the profitability segment of each customer, and are trained to look for ways to change the situation. They also learn who the Gold customers are, and are trained to treat them well.
• Computing lifetime value and potential lifetime profitability. It is not enough to know the current profitability of a customer. You need to be able to predict the future by making accurate forecasts of each customer’s potential lifetime profitability. This is especially critical for the “middle profitability” segments – those for which the bank breaks even or loses a small amount of money today. Half of those “marginal” customers have the potential to become profitable. The question is, which half? To forecast the future, you determine for each customer, the likelihood of your being able to sell them additional profitable products, the expected net revenue from usage of those products minus the promotional expense involved in the sale of the products. This forecast is added to current profitability to create a reasonably reliable lifetime profitability forecast which can drive bank marketing strategy and tactics.

	Check & Savings	Home Equity	Credit Card	Mutual Funds	Total
Revenue
Net Interest	$210	$248	-$280	$0	$178
Fees	$18	$18	$396	$1,500	$1,932
Total Revenue	$228	$266	$116	$1,500	$2,110
Expenses
Amort. Sales Cost	$20	$120	$67	$75	$282
Acc. Maint.	$30	$75	$40	$900	$1,045
Transact. Cost	$193	$21	$0	$30	$244
Allocated Overhead	$0	$0	$0	$0	$0
Total Expenses	$243	$216	$107	$1,005	$1,571
Loss Provision	$0	$23	$160	$0	$183
Net Income	-$15	$27	-$151	$495	$356
Taxes	-$6	$11	-$60	$198	$143
NI After Taxes	-$9	$16	-$91	$297	$213
Cost of Capital	$1	$40	$32	$68	$150
NIACC	-$10	-$33	-$123	$229	$63
Annual Revenue and Costs for typical bank customers having these products.

• Half of all customers were unprofitable
• 20% were very unprofitable
• The balances that people maintained were only loosely correlated with profitability
• Demographics were even more poorly correlated with profitability
• Half of the new accounts being currently sold would never be profitable
• The bank staff was working hard every day to retain customers who destroy customer value

• It was almost impossible profitably to cross sell the most profitable customers. Most of these sales cannibalized existing profitable products. For these top customers, marketing should focus on retention, not cross or up selling.
• Some customer profits and losses were temporary, not permanent
• Some low profit customers had great potential, sometimes because their assets were elsewhere, and they were, in fact, high profit customers at another bank
• Some unprofitable customers could be nudged into profitability if they were offered the right products at the right prices
• There were, however, many customers for whom there was very little potential for profit.

• Lifetime Profitability
• Potential Profitability
• Potential Customer Value

• Many customer’s business with the bank cuts across business lines. Organizational profitability is computed by adding up the profits from each line of business.
• Some costs, such as overhead, are not allocated to each customer, since the methods for doing this involve arbitrary decisions which may distort the real profitability of the customer to the bank.
• For those costs that are allocated to the customer, the allocation had, of necessity, to use standard cost factors (such as the cost of a branch visit, telephone call, or product sale) for which it was not cost effective to determine accurately based on each specific event.
• Customer profitability does not “roll up”. If two customers share the same account, the bank gave full credit to both (which one is the decision maker?). Organizationally, of course, each account is only counted once, not twice.

An auto loan	12%
A home equity loan	16%
A personal loan	12%
Mutual Funds	21%
A Certificate of Deposit	3%

• For retention programs and preferred customer efforts
• For product design analysis and decisions
• For channel reconfiguration and service introductions
• For product pricing

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