Pilot programs constitute the best method for getting the most of information-based marketing, a critical skill as customers do more business outside of the branch.
Across the industry, it is clear that the branch is losing steam as a prime destination for retail banking customers. This introduces an important new challenge in marketing and sales, formerly branch-centric activities that now must become effective in the virtual space if banks are to preserve customer ties and revenues.
Underscoring the profound shift in customer behavior, our research indicates that about a fourth of retail banking customers almost never visit a branch after opening their initial accounts. A further 50% of customers avidly use remote channels — Internet and mobile banking, automated teller machines and contact centers — as a branch supplement.
The problem is that while banks have decades of experience in engaging customers in the branch lobby, that expertise has not yet been recreated in remote channels. As a result, growth-hungry banks are losing sales opportunities — and at a time when they can least afford it. Credit cross-sell ratios for phone-oriented customers, for example, are only half of what is seen among branch customers.
The situation shines a bright light on information-based marketing, which seeks to enhance customer interaction by analytically identifying sales prospects and their likely needs and sensitivities. Formerly organized as a supplement to the branch experience, this type of marketing now must play a lead role in winning business online, over the phone, and even via the ATM.
Increasingly, banks will need a full multi-channel understanding of customers, not only to identify their priority needs but also to effectively deliver remote offers in the manner they prefer. This is a leap from today‘s data applications, which often are limited to specific products, channels or certain aspects of customer needs.
To succeed in this emerging form of competition, banks will need new levels of expertise in customer data analytics. But rather than work on the internal technical requirements and try to back into applications, the better path is to begin immediate work on identifying the customer-facing initiatives that will drive profitable revenue growth in multi-channel competition.
For many major regional banks, pilot programs will be the key to gaining traction in 2013. Such programs will be critical in retaining the focus on customer-centered innovation and not getting lost in the intricacies of managing the supporting data.
Wide Angle Customer View
In previous expansion eras marked by healthy demand and strong margins, banks could more feasibly concentrate on promoting individual products, particularly when extensive branch networks were the locus of customer interaction. Internally, this helps to explain why product silos (and their data sets) have flourished with only loose interconnections.
In the current era of tepid demand and weak margins, however, product push has given way to the more nuanced exercise of relationship expansion. With less new business to be had, the emphasis is on winning market share, essentially a household-by-household quest to capture “share of wallet.” The goal is to reach target customers wherever they are and however they like to interact with the bank, present timely and relevant offers, and establish easy fulfillment arrangements — with the huge complication that progressively less of the effort will be supported by the physical branch.
All told, retail customers now conduct roughly six of every seven banking transactions outside of the branch, mostly through electronic alternatives (Figure 1). While much of this is basic activity, such as depositing checks, getting cash, making payments and verifying account balances, the volume of online account origination and cross-sell is rising as people become more comfortable with online shopping for financial services.
To guide their marketing efforts in the new environment, banks will need a wide-angle view of core customers, including segment profiles and corresponding behaviors across multiple products and channels. In drawing this full picture, a lot of information needs to be unified, including funds movement among products; channel usage; deposit, purchase and payment transactions; shopping patterns; demographics and credit usage with providers outside of the primary bank (Figure 2).
This groundwork can unlock a world of opportunity in sequencing a customer‘s consolidated activity, essentially translating scattered data vignettes into full movies that portray customer lifestyles, attitudes, needs and preferences. By analyzing time-ordered spending and savings patterns, for example, a bank can uncover a world of difference between households with equally thin checking balances. One household may be loading up on consumer electronics and racking up expensive restaurant tabs; a second may be purchasing household appliances; and a third simply is shoving funds into savings.
The first customer profile, more risky, might value a higher-priced revolving credit card; the second might prefer a short-term installment loan; and the third might be receptive to investment products. For major players, the ability to parse such behavioral differences will become a permanent requirement.
Realistically, such nuanced analysis can prove a tall order for the typical bank. Just the basics of melding and cleansing data feeds from multiple areas pose a big undertaking, and then there are the challenges of honing customer data analytics and building platforms for various communities of users. The managers of data and product silos may be slow in cooperating, moreover, and technology teams can easily drift off course in trying to set up systems that will prove useful in tangible performance improvement.
Such factors introduce a very real risk that expensive and well-intentioned efforts will fall short in preparing the institution for the new era of data-driven multi-channel marketing. This introduces the question of how to proceed in a pragmatic way that will much more strongly assure tangible performance gains that will justify the effort.
The backward step, in our view, is to accept the default position of incremental progress pursued by separate teams. This often is how technology-led projects get mired in operational details, dating all the way back to the advent of the data warehouse.
Pilot programs offer a better approach, in that they marry development with practical goals (in this case associated with improved customer outcomes). With channel-targeted marketing, for example, the first step is to assemble a team specifically tasked to build out the business case for performance improvement, incremental revenues versus incremental costs, supported by field-tested propositions. This effort becomes the initial roadmap for priority initiatives and near-term performance improvement. As pilots in the field proliferate, successes can be scaled up to drive revenues and productivity.
As concepts further solidify, the development team needs to flesh out the organizational requirements for long-term success, including the infrastructure plan, the analytical plan and the delivery channel plan:
Infrastructure planning. Pilot programs provide an initial view of the most critical gaps in the bank‘s data infrastructure, exposing areas where it is difficult to access data quickly and efficiently, or where it is in a form that is not immediately useful for business applications. In some cases, the bottleneck is that source information is organized and managed by specific product, functional or channel organizations having a narrow agenda. In other cases, data will be confined in a centralized organization that has grown unresponsive to business needs. In still other cases, pilot programs will expose situations where a sufficient history of relevant data is not preserved or, in the extreme, never collected in the first place.
Importantly, these gaps will be exposed within the context of specific programs to enhance revenues or reduce costs. Over time, findings will become the basis for a data strategy that captures and retains all relevant information, makes it available to all of the business lines, and organizes it in a form that is useful for their needs.
Analytical plan. The assembly of wide-angle data for pragmatic applications will create new demands for analysis and insight. This includes descriptive profiles and predictive models that address the patterns of customer behavior across multiple products and channels, and the evolution of behavior over time. Ultimately, banks will need to understand how all these factors come together to drive “customer lifetime value,” a measure of performance which will likely become increasingly central to managing the bank on a relationship basis. Delivery system. Analytical insight only has value when translated into constructive action. This is why the most critical success factor may well be the operational delivery of new data-driven insights.
At most banks today, for example, the analytical ability to drive an effective dialogue with phone customers is surprisingly primitive. Elsewhere, online interactions have the potential to be highly personalized, yet the ability to exploit that potential is often non-existent. Banks will need to manage a coherent and consistent personalization logic across multiple channels (including the branch) in order to compete effectively.
More than ever, banks need to capture the full value of the primary bank relationship, yet the manner of achieving this is changing radically as one-on-one customer interaction in branch lobbies steadily yields ground to multi-channel banking. While branch sales generalists will play a diminishing role, the good news is that electronic channels unlock new possibilities for targeted direct marketing and sales, replete with high levels of customization, both individual and segment-based.
Jim Bramlett and Alan Schiffres are partners in the New York office of Novantas LLC, a management consultancy.