A key challenge facing banks today is how to offer the service provided by the old one-to-one relationship a customer had with their bank manager,1 but at service delivery costs shareholders will support. Bank services and products have largely become commodities, so banks, looking to differentiate, may choose to further define their brand, follow a lowest cost delivery strategy, look to offer a more personalized service to the customer, or a combination of all three.
Finance with a personalized touch once existed in all banks—the customer went to the bank manager to conduct business and to work with the bank to fulfill financial needs. The manager was usually a member of the local community and knew many customers through long-term relationships. Using knowledge gained through this relationship, the manager tried to match the services offered by the bank to the individual needs of the customer. This model is still used extensively in the commercial and private banking sectors where the banks deal with corporations and very high net-worth individuals. However, in dealing with customers in the personal and small business sectors, most financial organizations are facing some key competitive pressures:
- Customers are no longer tied to a physical location, and can deal online with any organization, anywhere.
- The services and products offered by an organization have largely become commodities and they have to deal with specialized competitors offering the same product range.
- In any commodity market, profit margins are low, so the cost of providing these types services and products is under pressure to be as economical as possible.
This has resulted in banks moving to deliver their products and services through low-cost channels that automate the process and remove the expensive human element. It is that human element that really understands the customer and offers a personalized touch. Without this personalization, what differentiates one organization from another? Is it the product, the content packaged around that product, or is it a flashy Internet site? In reality, none of these offer a good basis to inspire customer loyalty. With this strategy, the key differentiation becomes cost. In this arena, many new financial organizations, without the overheads of branch networks, can offer much lower cost options.
The alternative strategy is to recapture the personalized service to the customer. The key is to understand each customer along with his or her needs and goals. Helping customers satisfy their goals effectively helps to develop customer loyalty. Knowing the customer can help the business to target its products and services to the best effect of both the customer and the business.
For example, a bank might know a customer invests in the stock market through buying activity, but is the customer doing this for retirement, or is it to make money quickly for a new car? The old-fashioned bank manager, knowing this second piece of information, would treat the customer quite differently. So the technical challenge is how to create a system that can do what the bank manager once did—apply intelligence and reasoning to each case.
We are currently seeing an emergence of two types of personalization on the Internet: One offers users the ability to become GUI editors by allowing them to construct personalized pages; the other targets marketing of products and services based on information held about an individual. Neither really meets the needs of the customer.
In the first case, the Internet site will often present a series of boxes to check. Often the list is so long and confusing that customers leave before finishing the process. This results in an uneasy feeling, or worse, an unpleasant feeling on the part of customers that causes them to abandon the site never to return. Equally awkward, the resulting sites often separate their personalized sections ‘my.com’ from the rest of the site giving the feeling the personalized piece has simply been tacked onto the side of the site.
In the second more advanced case, sites will often collect data about the customer’s behaviors, apply a series or rules to the site, and as a result radically change the content of the site when the customer returns. This results in a jarring experience for the customer, who might wonder upon return, “Did I ask for this new information?” Again, the very thing the site was trying to achieve was not achieved because of a clumsy implementation. Instead of drawing customers back to a site, the experience drove them away.
We believe these two approaches, however, hold kernels of goodness and when refined and combined will produce the type of experience that encourages repeat visits, and more importantly, encourages visitors to turn into actual revenue-producing customers.
Returning to first principles, the goal is simply to understand the customers’ desires (want to live in a big home) and needs (plan for retirement) so to better match the presentation and sales process to the right customer at the right time. And doing so through automation so this sophisticated capability can be projected across a mass market.
The key is understanding the customer and in data-processing terms that means organizing and building customer data stores and attaching those stores close to the customer interaction to effect the interaction and personalize, really personalize, the experience.
These multiple logical data stores necessary to fulfil the total requirements of the customer experience are defined in an information model. The model encompasses traditional customer details (name, address, place of work, income), family situation (children), financial history, transaction history, and behavior. Customer behavior is the piece that is not reliable and consistently captured today, but it is a critical element. It must be captured across every channel touched by a customer (brick-and-mortar branch bank office, call center, Web site, mobile device, ATM) organized and stored.
Information can be gathered in many ways. One of the best ways is simply to ask the customer for it. When applying for a mortgage, for example, a customer must disclose significant amounts of information. It is easy enough to ask the customer whether this information can be saved, and if they agree, it can be used during future customer interactions.
Further, the model also captures information describing the style of customer behavior. For example, some customers want advice, and wish to be led through a process that terminates with a sale. Whereas others want to remain very much in control of their experience and want to make all the decisions explicitly. The fact a customer operates in one of these two ways (and any number of variations and shades) must be gathered and recorded and evolved as indicators change.
We believe the answer is to return to the core values that made banks respected institutions in the community: trust, privacy, and personalized service.
The information model will also have several traditional data warehouse-style processes applied to it. These processes will, for example, cluster customers in behavior domains, they will examine the customers current and potential profitability to the bank, decipher the customers life-cycle points, and determine where they are on the typical track through life.
Governmental regulation and consumer advocacy groups have described rules that limit the ability of financial institutions to use information gathered in one business line (say, medical insurance) for use in other lines (mortgage decisions). These privacy and various protection laws and guidelines must be adhered to, but in general do not severely limit the ability of a well organized information model to deliver enough data to properly personalize a customer experience.
Once operating, the information model will be connected to customer touchpoints (ATMs, call centers, Web sites) and be used to control the customer experience. The linking, however, must not be done using traditional programming languages, as logic implemented in this fashion simply takes too long to design and deploy.
Rather we wish to provide specialized business representatives and customers the ability to write rules that drive the experience. These are then implemented straight into the system and executed immediately in the live environment. In the end, there may be several rules engines tailored for specific types of experience interaction.
The fundamental challenge facing financial institutions is cost pressure, margin compression, and the growing mass market. Competitors are emerging everywhere, providing specific low-cost products and are poised to chip away at our core franchise.
We believe the answer is to return to the core values that made banks respected institutions in the community: trust, privacy, and personalized service. In 1925 these values were delivered face-to-face over a bank managers’ desk; in 2001 these values and capabilities must be delivered where the customers are today—on the phone, at the cash machine, and increasingly, on the Internet and other emerging channels.
Properly engineered computer systems can capture and process information describing customer behavior, desires, and needs and then use that information to present it back in formats that draw a customer in to return and buy more services from the financial institution.
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