Assembling a complete customer view has long been a struggle for the banking industry. Historically, banks have been product-centric both in their organizational and technological structures. Each product--savings accounts, home loans, credit cards and more--has its own systems, making it difficult to know that an unprofitable checking account has a million dollar trust account. Marketing has typically been focused on selling individual products, rather than determining customers' true needs.
Mergers and acquisitions have added to the dehumanizing of customer interactions. At the same time, nonbank competition and virtual banks have moved in to offer new choices for dissatisfied customers.
Turning Data into strategy
Given those challenges, it's only natural that there's a surge of interest in CRM by the retail banking community. Few organizations can access the quality and quantity of customer financial and behavioral data that banks have kept in their systems for years. But turning that data into actionable strategies can be a challenge for banks.
Banks that began investing heavily in data warehouses several years ago are finding they're ahead of the game when it comes to feeding multiple channels. "I think the interest in data warehousing is growing across all industries as people mature their idea of what CRM is about," says Simon Ayres, marketing manager for relationship technology solutions, NCR Corp., Dayton, Ohio.
By understanding customers' buying habits, banks can provide their front line people in customer service and branches with suggestions based on that knowledge. It could be as simple as suggestions on reinvesting a CD that's about to roll over, to explaining how moving extra checking account funds into a sweep account might better serve financial objectives. "There are scripting capabilities built into new front-end systems that are quite capable of doing that," says Paul Jameson, vice president of retail banking, North America, for New York-based Cap Gemini. "Then you can provide a very value-added service to today's extremely busy consumer."
Profitability analysis can be used to determine where marketing dollars should be spent and where to adapt marketing strategies on a customer-by-customer basis. Single-product customers could be targeted for additional products that would improve their profitability for the bank.
By integrating service cost information, banks can determine which products should be offered. For example, customers who call into the call center to check their checking account balance on a daily basis would probably be a poor candidate for a mutual fund, but an excellent one for a CD.
"Data modeling based on customer interaction and preferences can also help marketers know which types of offers customers will respond to, as well as how and when to make them," says Kevin Faulkner, vice president of marketing, vertical industries at San Mateo, Calif.-based E.piphany. "By profiling customers and understanding customer preferences I might find out that you're a type of customer that would open a checking account if I offered a subscription to Wall street Journal, whereas another customer may respond better to another type of offer.
Using Profitability at Royal Bank
For Royal Bank of Canada, with assets of $165 billion, measuring value at the account level plays a central role in its successful realization of CRM. "Client value measurement is critical to our CRM activity," says Cathy Burrows, senior manager of client relationship marketing at the Toronto-based bank. "It represents a definitive tool to refine service and product offerings, cost management, pricing initiatives and marketing spend."
Using NCR's Teradata platform and Value Analyzer, the bank is able to analyze how each client's inherent value to the bank is affected by the type and frequency of events, their balances and their channel usage. However, merely assessing profitability doesn't add value. It's the actions taken from a better understanding of individual client value that result in rewards to the bank.
The bank's nine million personal retail customers are segmented into discrete segments based on the attitudinal and behavioral factors, current and potential profitability, expected purchasing behavior, vulnerabilities and channel preferences. Strategies are then developed, not only for each segment, but also for hundreds of micro-segments within each segment--the ultimate objective of this quest being one-to-one marketing. Individual treatment strategies can be tested on small cells of customers to establish what works and what doesn't and to test refinements for a continuing basis.
Empowering the sales force. Integrating client value metrics into the bank's Client Sales and Service system allows sales personnel to put forward offers proactively and talk about opportunities with clients based on value at the individual level. This enables real account management and can be used to generate greater customer loyalty through product offers relevant to specific customers.
Assessing lifetime value. The use of current and historical client value measures allows the bank to assess its client segmentation in a more sophisticated way, by taking into account factors such as life-stage changes. Analysis showed, for example, that it was worth supporting relatively unprofitable college students with student loans based on the value of future relationships with those clients.
Integrating behavioral risk. Burrows says Value Analyzer has also created a new view of clients and portfolios of clients for risk management monitoring and modeling by integrating behavioral risk models and expected credit losses. "This has allowed the bank to enhance models over time and support the fundamental paradigm shift from market share to client value measurement in a critical way," she says. The bank is using two additional models to look at client vulnerability (attrition) and propensity to buy.
"We know we must differentiate ourselves or be marginalized," says Burrows. "Our customers have told us loud and clear that an integrated client relationship strategy is differentiating. That's the approach we are now taking."
Knowing the Customer at First Union
First Union Corp., with assets of $157 billion, has been using CRM tools from SAS Institute, Cary, N.C. to identify patterns of customer behavior that would then generate sales or service opportunities. Used in conjunction with data warehousing, these tools have allowed the bank to send highly targeted direct mail based on customers' individual survey responses, as well as provide bank branches with comprehensive profiles on their customers. The profiles, drawn from centralized company data warehouses, reveal the most promising areas for satisfying each customers' individual needs and concomitantly, increasing branch revenues.
"Having a greater awareness of customer relationships and the implications around retention and opportunity has really begun driving the bank's business strategy in the last year," says Bob D'Angelis, senior vice president, Enterprise Knowledge and Research Group, First Union Corp., Charlotte, N.C. "It's really about using that back office component consistently and providing content through each of the channels."
Segmenting customers. First Union has been analyzing customer behavior across various product sets and channels to identify common groupings. Particular customer records are labeled as belonging with a segment with a certain set of characteristics to assist sales or service representative in managing that customer relationship.
Predicting buying propensity. The bank is currently building predictive models around the likelihood to purchase based on existing attributes, particularly focusing on single-service customers in both consumer and small business customers.
Through response modeling to direct mail campaigns and building response models based on various attributes in its data warehouse, marketers are able to predict the response of a particular customer record to an upcoming offer. "Customer contact representatives could then touch the customer in a way that would potentially better serve that customer relationship, such as extending a unique product or service offer," says D'Angelis.
Analyzing profitability. Assembling account-level profitability into a customer view of profitability is also part of the bank's CRM strategy. It has put together programs looking at both customers with particularly low profitability, as well as groups of customers with higher profitability and are driving strategies on both ends of that spectrum. D'Angelis says the bank is also testing concepts aimed at making unprofitable customers profitable by determining which cross-sells might deepen the relationship and improve profitability.