Many institutions today are investing heavily in database marketing. In most cases, several million dollars are required for design, software and database construction. Some banks are finding, however, that early paybacks are not as high as expected.
Marketing databases do not generate revenue by themselves. They must be used in an active program of profitability analysis, customer segmentation and marketing tactics that build retention, loyalty and increased sales.
Data into knowledge
The key requirements of any successful database marketing project are collection of relevant, accurate data about customers and construction of a comprehensive marketing customer information file (MCIF); development of an accurate and credible system for determining the profitability of each customer, at least monthly, using day-to-day inputs on interest rates and costs; development of schemes dividing customers into useful, actionable segments based on profitability; and creation and implementation of tactics, based on customer segments, to modify the behavior of employees and customers to increase sales, improve retention, lower costs and improve profits.
There are three basic steps to database marketing:
Collecting data. This means gathering relevant, accurate data on prospects and customers; storing and updating it in a database; making it available to marketers and other company staff in a form useful for database marketing. Few financial services companies have gotten beyond this phase. Most of them feel they are successful if they have built a customer marketing database and conduct a few surveys of customers.
Turning data into knowledge. This requires developing methods for data analysis so that the data collected can be understood and converted into actions. This process involves developing appropriate customer and prospect segmentation schemes, modeling, scoring, and profiling, as well as conducting tests and setting up control groups. Companies have experimented with solutions to this problem, but most have not yet solved the collection problem.
Developing strategies and tactics to modify behavior. This means using knowledge gained from solving the first two problems to modify the behavior of employees, customers and prospects to improve long-term profits of the institution. Tactics can include reallocation of resources, communications, loyalty programs, customer-specific pricing, frequent buyer programs, special services, performance measurement and incentives. All companies have experimented with various aspects of behavior modification, but most have tried it without first solving the three basic problems.
Some companies today have been able to develop profitability at the customer level, integrating this data with other data in the customer database and use the resulting knowledge to segment their customer base.
With this knowledge, these companies can develop targeted marketing strategies and vary service levels based on customer value. The process can be highly satisfying to customers and improve profits for the company.
This can be accomplished by capturing customer data on all product accounts in a single MCIF that determines the profitability of every product owned by every customer on a monthly basis.
In addition, product profitabilities must be fed into a customer scoring and segmentation system that ranks all bank retail and commercial households into one of several profitability segments. Segment designations are recalculated monthly and made available to marketing staff and bank personnel who have customer contact.
Finally, segment designations drive an active behavior modification program including cross selling, up selling, resource allocation, retention building, product pricing and provision of special services.
To understand the process, assume that the typical bank s customers break down into five profitability groups, based on monthly profit contribution. The numbers are based on pretax profits. The five groups are not of equal size. The top group consists of only 5 percent of households and contributes 80 percent of monthly profit. The second group represents 11 percent of households and contributes 25 percent of monthly profit. Together, 16 percent of customers produce 105 percent of profit. Group five, representing 28 percent of customer households, erodes profit by 22 percent. Many banks suspect that their bottom quintile is costly to them; few have the information to prove it.
Profitability calculation is the heart of the system. It is complex, but it is computed for every product, for every customer, every month and includes factors like cost of funds, funding credit, loan loss provision, capital allocation, capital charge, overhead and FDIC expense. The profitability determination is the foundation for development of advanced database marketing segmentation and behavior modification processes.
After computing every customer s monthly profitability, it is necessary to create customer profitability segments. The analyst should allow the data to specify the segments based on groups with similar profit characteristics. For example, the data might suggest approximately 5 segments. Every customer in the bank, therefore, can be classified as either a 5, 4, 3, 2, or 1, where 5 represents most the profitable customers and 1 represents the least profitable customers.
Once each customer is segmented by profitability, it is possible to study the behavior of certain segments. Customers are ranked by number of products owned.
predictive modeling
Once all customers are segmented and their various behavioral characteristics are captured in a database, a personal profile of each bank customer can be made available to all customer contact personnel, through technology, at the very point of sale. The profile can include addresses and telephone numbers, birth dates and social security numbers, home ownership with date at present address, occupation and employer, other financial institutions where the person banks, the bank officer assigned and the branch, whether the customer has filed a financial statement, accounts with current balances, line amounts, and amount owed, the profitability segment to which the customer belongs and suggested next best action for the customer.
Armed with database knowledge, statistical analysts can build models to predict such things as the profit propensity of customers, what products a customer is next most likely to need and which behavior change will improve the customer s profitability. This information is made actionable by using technology solutions to deliver knowledge to personnel at the point of customer contact. Personnel can utilize the knowledge to improve cross- and up-sell opportunities, to make better pricing and fee waiver decisions and to suggest alternative channels for transactions.
The marketing and sales activity at the branch level can be channeled into customer focused activities by profitability segments. There are separate goals for each of the five profitability segments.
Since the profit segment 5s and 4s represent only 16 percent of customer households, but up to 105 percent of the monthly profit, the bank will want to allocate substantial human and marketing resources to retain these customers. And since human resources are limited, particularly those resources devoted to sales, the bank should attempt to direct the acquisition activities of their calling officers to prospects who have the potential to be profit segment 5s or 4s.
In addition, the bank desires to expand the relationship of all customers by selling additional products and, thereby, improving the household profit.
Finally, in lower profit segments, actions should be taken to reprice unprofitable products such as CDs and loans as they mature or are renewed. Employees should refrain from reducing or waiving service charges and fees, and concerted efforts should be used to migrate these customers routine transactions to less expensive alternative channels of delivery.
There are a wide variety of retention solutions, each based on the customer s relative value. They include identifying and assigning the most valued customers to appropriate relationship officers and establishing higher service standards including priority problem resolution, priority telephone response and discretionary pricing initiatives. Separate communications strategies include proactive contacts from the local relationship officer, special mailings, product offers and reward programs.
The wealth of information now available to banks adopting a profitability and segmentation system enables them to take broader strategic steps, such as developing market potential analysis, ranking markets based on profit potential, targeting the most profitable markets for expansion, exiting low potential markets, reallocating human resources away from markets with low potential into those markets with high potential and developing incentive plans that incent increased value instead of increased volume.
Robert James is a group manager of Centura Bank. Arthur Hughes is an evp of ACS, a database marketing firm in Reston, VA. Gordon Goetzmann is a senior consultant of First Manhattan Consulting Group.
