Centralized Analytics Helps You Personalize Your Customer Contact and Build Your Brand

How much do you know about your customers? More companies today recognize that capturing wallet share from existing customers is as important as capturing market share with new customer wins. At a large national bank, for example, an enterprise-wide customer strategy has focused on developing long-term relationships as a way to increase wallet share and bank profitability with a focus on customer service.

Although a major player in the industry, the bank had not performed on par with its competitors with regard to customer wallet share. The bank provides a range of financial products including insurance; investment; and personal and commercial banking services, but its main competitors averaged 2.8 products per customer for every 1.2 of the bank’s products.

Worse than that, bank leaders recognized that they were operating blindly when it came to marketing to their customers. Too often customers received generic mailings because the bank wasn’t able to segment accounts and tailor offers to their needs.

Bank leaders had a vision to develop long-term customer relationships through creating a brand identity as the most convenient, most familiar and easiest-to-use bank. They turned to a CRM system capable of capitalizing on all customer data, including demographic and behavioral information, so they would have a 360-degree view of their customers. They wanted to be able to make personalized offers through each contact channel, whether inbound—when customers access bank web sites, call centers, IVRs, ATMs and points of sale—or outbound through direct mail, email or other channels.

Bank executives selected a CRM system that uses centralized analytics to provide an individualized approach for each customer by integrating inbound and outbound marketing. They implemented the CRM system’s outbound marketing module in 2002 and integrated this with inbound marketing in 2006, with both modules working from the same database of customer information.

Using algorithms and data-mining capabilities in the CRM system, the bank can pinpoint cross-selling campaigns that address the needs of each customer. The system segments customers based on current and potential profitability and creates a lifetime value model for each segment. The system also provides 18 cluster models that segment customers according to their transactions, products and other factors and calculates monthly profitability for each customer based on what products are purchased or used.

Armed with this detailed analysis, the bank now proactively sends targeted outbound campaign offers. Customers receive only what would be of interest to someone in their segment. This increases the chances that they’ll act on the offer, and because they’re no longer getting irrelevant offers, it increases loyalty.

Personalization

If a customer walks up to an ATM, the system analyzes all available customer attributes and preferences, simplifying and speeding the interaction. The typical ATM interface we are all accustomed to is better than it was just a few years ago but still presents only a limited number of options for the customer: withdrawal, deposit or balance inquiry. The bank can now present the customer with more options and more services. For example, in addition to “remembering” that a customer always deposits to his checking account, the ATM can make him a personalized offer, based on his recent interactions. If another customer goes online to research a loan to buy books for school, the CRM system on the back end triggers the event and adds “loan” as an option to the ATM’s menu of activities for her, simplifying her experience in future visits.

The system’s detailed segmentation can now help create products that fit each customer segment. Let’s say a customer with two young children has a checking account and a savings account. The bank can now develop an offer for a higher-yielding savings account for the kids’ college education. Before, the bank and its customers were missing out on those opportunities. The hope is that soon the system could even analyze spending habits and recommend the amount a customer should set aside each month along with the offer.

Additionally, bank employees can now act when account balances change and send out such customized, event-based offers as reduced credit card fees or new product incentives that reward customers.

Customers receive personalized offers each time they visit an ATM, phone a call center, navigate to the bank’s web site or visit the local branch. The bank uses analysis of the customers’ credit scores to create pre-approved offers before the customer initiates contact. The bank offers pre-approved mortgages over the Internet and was one of the first to give pre-approved credit cards through ATM, call center and Internet channels.

Because the CRM system is integrated, inbound and outbound offers are consistent for each customer and across all channels, helping create a bank brand that projects familiarity with all of a customer’s financial needs, rather than focusing on the use of just one product.

To boost its cross-sell ratio, the bank capitalized on the integrated CRM system by creating a fee-based product bundling offer that has allowed the system to perform extensive customer analysis. A simple monthly fee gives customers access to more than 10 different financial products, including credit card, checking account, line of credit, family insurance, mutual funds, and Internet and phone banking. The customer signs a contract that allows the bank to obtain all credit score information and authorizes it to send multiple offers through direct mail, email, SMS, telemarketing, direct channels and mobile forces. In exchange, customers receive 5 percent cash back for every transaction made. The offer was so well received that it attracted a million customers—91 percent of whom were new—in under two years.

With help from cross-selling campaigns indicated by the integrated CRM system, the bank’s premier customers now have an average of five financial products, while regular customers average three, both of which far surpass the previous 1.2. The bank attributes 61 percent of total credit card sales and 89 percent of personal loan sales in 2006 to CRM system-generated offers. In 2007, 20 percent of the mortgage sales were the result of such offers.

The bank finds that CRM-generated offers create quality leads that increase the customer retention and value. On average, customer profitability has increased by 30 percent for customers in cross-selling campaigns, and ATM offer-acceptance rates have risen as high as 35 percent. Branch offer-acceptance rates grew as high as 30 percent, and car-loan sales have grown from 9 percent to 16 percent.

Through analytics and segmentation, the bank can now build relationships with its customers.