Financial services companies are embracing customer relationship management to fuel their future growth. Customer analytics, distinctive value propositions, a well-trained and properly incented customer-facing staff as well as enabling technology form the basis of an effective CRM strategy.
Determining the best products to cross-sell. Analyzing customer data — transaction activity, product usage behavior, demographic patterns and lifestyle attributes — provides insight and an empirical basis for driving customer decisions. Association and induction analyses identify cross-selling opportunities among underpenetrated customer segments by examining customers with similar descriptive profiles or affinities but who exhibit different levels of product holdings and usage activity. Analogies for financial services include checking account plus overdraft and credit cards; and mortgage plus home equity line of credit plus mortgage insurance plus property insurance plus checking account.
Principal component analysis and clustering can help you identify customers with common sets of product holdings and needs. Analyzing customer migration patterns across the various product holding groups over time will reveal natural migration patterns. It will also reveal opportunities for more proactive cross-selling and uncover any weaknesses in the product line or communication strategy, which could be potential causes for account or customer attrition. Analyzing profitability of the various product holding groups and migration paths will indicate the product groupings and sequencing to emphasize cross-selling strategies and tactics.
Product-focused response, activation and usage/revenue models identify customers who will respond to an offer and generate balances. Response scores are constructed from prior marketing promotion and response files. Response models are highly sensitive to the population targeted, the competitive environment and the offer made in the campaign used for model development.
Activation and usage/revenue models are more refined targeting tools, requiring 12 or more months of performance data. These models will rank customers in terms of activation rate and propensity to buy. The predictive variables are often based on life stage, socio-economic and lifestyle factors as well as recency, frequency and monetary variables for related products, drawing from both internal and external (credit bureau and demographics) data sources.
Stemming customer attrition. Event triggers signal changing interests, needs and preferences i.e., change of address, information requests and balance withdrawals. Models predicting customer as well as account-level attrition evaluate the flow of funds, key events and transactions to provide an early warning of attrition likely to occur in the next three to six months. Combining attrition models and event triggers with a customer value metric will help ensure that your marketing dollars are being invested wisely in retaining the right customers. By researching why the high-value customers are moving their balances, where the balances are going, and how the balances could be retained, you will gain insight into how to make both products and messages more compelling.
Customer credit risk. A predictive customer risk model is essential to qualify existing customers for new credit products as well as to identify high-value customers with acceptable credit risk who require proactive retention actions. The predictive factors are derived from deposit, loan, credit card, mortgage, insurance and investment account historical data. The customer risk model can be constructed to predict risk on a single credit product or to predict risk across all of the customer's credit products with the institution.
Implementation strategies. In order to swiftly translate the knowledge about customer behavior into something actionable, a decision-making framework that leverages the event triggers, customer value indicators and prediction models must be very responsive. Along with precision customer analytics, an operationally efficient, event-driven marketing automation process, will help you quickly identify and act upon new opportunities signaled by changes in customer behavior, life events, or product lifecycle.
To realize the full potential of customer relationship management, you need to give sales and service representatives screen prompts with cross-selling suggestions, a customer value indicator and other relevant customer data.
Sales representatives also need training on the best ways to capitalize on this information. Product guides, sales tools and incentives should reinforce cross-selling, retention and servicing objectives. First Union has redefined the roles of branch personnel, putting a greater emphasis on selling through elimination of servicing calls and doubling the commission-based portion of the compensation structure.
To appeal to customers and enhance bank profitability, you need to offer product and service packages with distinct value propositions. Norwest offers a bundled package that includes a no-fee, interest-bearing checking account and discounts on loans when the customer maintains a combined deposit account balance of $3,500 or greater or remits mortgage payments electronically. First American Corp.'s First American Select Rewards program provides frequent flyer points for any business a customer does with the bank. Lloyd's Bank offers frequent flyer miles for stock trades. Other banks offer a half-point discount on loans to customers who agree to directly debit the loan payment from their checking account with the bank. Similarly, some banks offer fee discounts to customers who sign up for direct deposit of their paychecks. Charles Schwab commands a premium price for its discount brokerage services by providing extra benefits such as a mutual fund supermarket and various levels of advisory services.
Liza Kirby is a director, credit division at Fair, Isaac and Co. Inc., San Raphael, CA.
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