There’s a lot of talk about customer centricity. What does customer centricity really mean?
Customer centricity means putting the customer first. Translated into the world of banking, a customer-centric bank designs its solutions for the end customer’s needs and desires.
It also refers to how banks interact with customers and the quality of service they provide. Customer-centric business practices differentiate banks from their competition and, when well executed, set the stage for solid and sustainable growth. This is particularly relevant in today’s competitive market, where banks have similar offerings but are vying for the same customers.
How can a bank be customer-centric during the client onboarding phase, which typically marks the first interaction a customer has with his bank?
The bank needs to take the customer ‘by the hand’ and guide him towards the product that best matches his needs and expectations, rather than impose its own agenda. This is true for online as much as in-branch onboarding, where the customer receives advice from a bank employee in person.
Nowadays, most customers initiate the onboarding process online…
Indeed, and in this case the bank needs to ‘virtually’ accompany the customer towards the best product fit. Let’s suppose the bank offers a range of 10 different banking cards. The customer expects guidance to identify suitable products quickly and easily. Where there is no guidance, he is likely to be frustrated and will drop out. This is obvious to anyone who has made an online purchase, but before buying a product, customers often find themselves confronted with an overwhelming amount of online information, complex product configurations, and forms that are too long and complicated.
How can a bank effectively guide the customer through the online shopping process?
The bank’s first goal of the interaction must be to find out the customer’s intentions. By asking her the right questions at the right time (i.e., only what is relevant to the actual shopping context), the bank can gather customer data incrementally and thereby pave the way for the customer to find appropriate products when they best suit her needs. The result is an Amazon-like shopping experience—intuitive, seamless, and powerful in terms of converting prospects into customers.
When you say Amazon-like shopping experience, what are the key learnings for retail banks?
Amazon teaches us how client onboarding can be subtle and run in the background. All the information gathered during the process is so precisely directed to the customer’s needs, that she hardly notices she is being onboarded by the service provider.
Amazon also offers lessons in meeting customers where they are. In tandem with its online store, Amazon has opened physical stores that are fueled by automation and analytics based on the data gathered through its e-commerce site. It realized that offering customers physical touchpoints in conjunction with online touchpoints enhances their shopping experience; retail banks should learn that positive shopping experiences extend over both physical and digital channels.
Why is this so relevant in retail banking?
Few customers complete a process through a single touchpoint. They usually prefer a mixed scenario, where they hop between channels. For instance, a customer may start an onboarding process online, but will switch to a personal interaction with a client advisor to get more detailed advice.
Therefore, the ability to provide coherent, cross-channel experiences is another crucial element of customer centricity. The bank of the future needs to master digital and physical channels separately and in combination, and use the data gathered from both channels to truly understand its customers.
What technologies can retail banks use to gain insights into their customers?
In the past, many banks have automated their processes using rules-based engines. These engines leverage the data the customer enters to move a defined process in the right direction. These processes are closed, however, and do not systematically adapt to evolving customer needs.
Over the next 3 to 5 years, machine learning will replace simple rule-based scenarios. Contrary to automated process-focused workflows, machines ‘learn’ from data they collect and can make predictions about future events. This is called predictive analytics. As an example, fragmented data from different customer interactions are used to identify typical behavioral patterns. This insight, in turn, enables banks to better understand customers’ preferences and design better products for them. With these new and customized solutions, banks will be in a better position to target new prospects. Thus, predictive analytics can help banks leverage customer data to achieve customer centricity.
How does Appway support retail banks in becoming more customer-centric?
For most banks, providing a coherent customer experience across different channels is challenging because traditionally, each channel has existed in isolation. Each channel has its own IT environment, a separate set of customer data, and unconnected teams managing the channels.
By orchestrating all communication channels across digital and physical interactions, Appway offers banks an integrated approach to managing customer needs and expectations. Users of Appway solutions—customers, client advisors, as well as the bank’s back office staff—benefit from better data quality as a result of coherent front-end customer communications. At the same time, Appway offers banks an agile platform, which allows them to adapt their service offerings in real-time without affecting legacy systems. Whether through new business rules, process enhancements, or additional interaction modes such as chatbots, changes can be deployed and applied independently of core software release schedules.