The use of digital channels is skyrocketing in financial services. New technologies serve customers in unprecedented ways while driving internal efficiencies. And according to market research company Ovum, U.S. banks will spend $41.5 billion on technology through 2013, with much of it on digital tools.
Customers now have access to accounts and can transact across mobile, social, and other self-serve channels. The branch's role is changing to focus on more complex issues while consumers use Facebook, mobile apps, and virtual wallets to conduct financial business in a new ecosystem.
Today's consumers share more information about their needs, risk tolerance, and personal profile than ever before. Their expectations are higher, shaped by experiences outside banking. They are better informed as they use internal and external channels to research products and services. They look beyond banks to fulfill financial needs, engaging players such as Google Wallet, PayPal, Mint.com, and even Costco and Wal-Mart. And consumers connect to brands and one another through social and mobile channels, communicating their experiences broadly. They're willing to take advantage of low cost channels if they find them valuable and relevant to their daily lives. Many actually prefer them.
There is much potential to balance internal efficiencies with a superior customer experience in this new reality. But achieving the balance requires banks to optimize the unprecedented amounts of customer data now generated to make information actionable and relevant. New sources of customer Big Data consist of:
• Transactional data
• Product usage data
• Web registration data
• Customer value data
• Channel usage data
• Web clickstream data
• Third-party data
• Social media data
Banks are beginning to explore the opportunity to differentiate with insight. For example, the business press reports that one of Capital One's top priorities is to be a data-driven organization and use insight to differentiate in customer service and product development, though specifics are hard to come by. And it is not alone. Investment firm State Street Corp. is using semantic data models on the client side to optimize investment strategies, while also improving regulatory reporting and risk calculation internally. Even a smaller player like Midwest regional bank Great Western Bank is leveraging predictive analytics for its marketing activities.
The industry is still in its nascent stage, however. According to a recent study by Celent, only 24 percent of banks surveyed had implemented a Big Data solution, most commonly around risk and fraud monitoring or product and service marketing. But of those who have had a Big Data initiative in place for more than a year, 70 percent had met or exceeded business expectations. And to highlight data's potential, 90 percent of those surveyed said they think that successful Big Data initiatives will define the financial services winners in the future.
So how can banks make the most of Big Data? By optimizing the collection and use of customer data, banks and other financial institutions can simultaneously improve the customer experience while driving efficiencies. Some examples include:
Provide consistent multichannel experiences. Consumers can now interact with a bank through multiple channels for information and transactions. Banks must provide a seamless experience across whatever channels are used. Employees in the branch must know if a customer has called the contact center or visited the website; transactions started in one channel can be completed in another. This will create satisfied, engaged customers.
Acquire new, mobile-savvy customers. Young, digital native consumers are beginning to open accounts and create lifelong relationships with financial services firms. They're mobile and they expect the companies they do business with to be mobile, too. Banks will succeed reaching this new customer group if they deliver insight-driven experiences through mobile devices.
Sense and respond with effective targeting. Reaching the right customer with the right offer at the right time is the holy grail of sales and experience. And banks can generate new revenues through proactive engagement and outreach to certain customers groups at the proper time.
Rightsize the customer experience. Use Big Data to find the most appropriate channels based on customer needs, value, and behavior, and then go deeper to understand the best way to migrate customers to serve them in the most efficient and effective channels.
Identify new sources of revenue and acquisition. Mine unstructured social data to activate advocates and identify new customers. Optimize pricing based on customer segments, products, channels and geographies, and remove any revenue leaks such as ineffective lead generation, poor follow-up, low conversion ratio, or high attrition to achieve sustainable revenue sources that are less sensitive to risk, sticky, and recurring.
Build loyal relationships. Surprise and delight by knowing customers more intimately than ever before and meeting their needs, whether they are verbalized or not. Show that your bank has its customers' best interests at heart, and they will reward you with their loyalty.
Improve service to sales. By mining customer service data and defining trends, banks can respond to customer needs and make systemic changes to processes that can even result in up-sell success. For example, rather than responding to and resolving complaints around monthly service fees, offer direct deposit or other products and services as part of the care response that would eliminate these charges.
Invest smartly in the retail branch. Understand branch-level data and optimize investments in the network. Learn what types of customers visit the branch and why. Focus branch initiatives on what matters most to those customers.
With so many opportunities for revenue enhancement and relationship strength, why don't more banks take advantage of the Big Data potential? Because acting on these opportunities is a non-trivial matter. Making sense of so much data is a challenge, as is where to prioritize efforts. Companies also want to make sure to invest in the most effective initiatives while staying agile enough to meet changing customer expectations. It can be a daunting undertaking.
Five Ways to Attack Big Data
We at Peppers & Rogers Group have outlined five steps to guide financial leaders as they craft smart data strategies:
1. Elevate the importance of business-savvy data scientists. While there's always a high demand for quantitative professionals to be part of the team, progressive banks are looking to complement that talent with creative business professionals who see business opportunities in trends that produce bottom-line results.
2. Organize for one version of the truth. Too many banks are still organized in product- or channel-centric silos. The bank can't knit together a comprehensive picture of the customer. Silos need to be redefined along with analytics practices. Online and offline data must be integrated into platforms across channels that facilitate a comprehensive understanding to enable predictive analytics and inform real-time interaction strategies.
3. Don't underestimate the integration challenge. Today banks need to extract insights from structured and unstructured data, statistical data, social media streams, click stream data, smartphone data, videos, etc. Small-scale experiments using Big Data are recommended to start, with slow rollout from there.
4. Integrate intelligence into customer-facing business practices. The biggest opportunity for Big Data is the potential to identify and integrate insights into customer-facing applications in real time. Analytics have come a long way, but many banks neglect to push the intelligence to front-line applications.
5. Use Big Data to accelerate the customer-centric transition. Customer centricity is no longer a nice to have strategy for banks, it's the only differentiator. And data is the backbone. It's critical to think beyond technology and analytics to what organization, process, and people-related changes are necessary to really put the data and insights to work.
A successful Big Data strategy must be coordinated across the enterprise. It's not the domain of one department or business unit. The chart above illustrates a hypothetical use of Big Data to harness and harvest customer data for an improved customer experience and greater efficiency.
Conclusion
Big Data shows so much promise for banks willing to consider it strategically. Those that do will be able to understand customers more intimately and act in real time to meet their stated and perceived needs. On the efficiency side, they will harmonize channels by defining multichannel journeys that make sense to the user and eliminate redundancies. And overall, banks that create Big Data dominance will influence customer behavior across channels to make interactions more effective and efficient, gaining loyalty and financial strength in the process.
