Digital is disrupting value chains and compelling organizations to redesign their business models, processes and systems, especially in the banking sector. Technology is now the bedrock of everything from customer sourcing to enhancing customer service at reduced costs. As customers need to evolve, they want to define the terms of engagement with service providers.
In the new paradigm, customer relationship management (CRM) has transformed into customer managed relationship (CMR)—with the focus on convenience and flexibility of availing services through an omni-channel experience. Digitization helps organizations to achieve this at a fraction of the costs, thereby offering higher profitability.
A ‘homogenous industry’ such as banking requires a differentiated digital strategy that will give banks a sustainable competitive advantage. We are now at a digital tipping point, where all aspects of banking can be conducted online. Customer expectations are also evolving in tandem. They want to transact at their convenience, with information and advice available at a single click. Organizations, therefore, need to offer customers an enhanced user experience—across platforms—to ensure a differentiated user experience. This can be achieved through micro-personalization wherein the various digital platforms will need to be personalized for each customer.
Organizations can now self-determine the needs of customers through behavioural analytics. Analytics can help them understand not only what customers say they want vis-a-vis what they don’t say they want but also what they really need. It can help organizations understand the profile of customers and their behaviour across digital touch points. These insights can then be used for driving sales, services, and personalizing their digital channel experience.
Making sense of crucial data
Banks are analysing various customer data points such as payment history, products held, and credit history to determine the credit worthiness of a customer and digitally embed it in various channels to offer pre-approved loans and instant disbursements. By tracking the spending patterns of customers, many banks also understand their value potential and make targeted offers on credit cards in real time.
In addition, analytics and Artificial Intelligence (AI) are being integrated with digital channels to provide instant recommendations on products that will best suit the customer. For example, a college graduate can be offered an education loan while a married couple with young children can be offered child investment plans and life insurance policies along with relevant loan products.
While banks are still trying to achieve this effectively, many organizations have already taken the lead and set awe-inspiring benchmarks—a case in point being recommendations provided by Netflix and Amazon based on the customer’s viewing and purchase/browsing history.
Digitization and analytics are converging to enable real-time cross-selling and servicing. Locational intelligence is further empowering digital channels to show relevant merchant tie-up offers and services to the consumer based on their location. Over and above, social information is providing a rich data of hitherto unknown insights about the customers, such as interests and hobbies, which further helps in offering relevant services.
One of the most important areas where I believe analytics will help shape digital strategy is in anticipating the needs of the customer and offering relevant products. With reference to banks, they want to feel like their bank is anticipating their needs, not bombarding them with product offerings. Remember, the customer is spoilt for options. Why run the risk of letting him choose one, especially if that one is not you?
Digital disruption through cognitive analytics, AI
Last but not the least, analytics is fuelling the user experience (UX) of digital platforms, resulting in development of newer ones. Click-stream analytics and page analytics are being used to personalize and optimize the UX and the menu options on various digital platforms. AI, coupled with cognitive analytics, has led to the evolution of chat bots which, I believe, will become the norm.
Advancements in digital technology go hand in hand with disruptive technologies in analytics. Today, one has an array of tools—Hadoop, Spark and noSQL databases, and statistical packages like R—which, coupled with data science, can help in analysing structured, semi-structured and unstructured data to personalize recommendations. These analytical technologies, together with advanced AI and proliferation of application programming interfaces (APIs) will result in next-generation digital experiences for customers. However, we need to exercise caution. Advanced analytics should not be used at the cost of infringing on the privacy of customers. There are concerns about organizations becoming too intrusive, which leads to customers becoming extra-cautious in parting with their information.
The author is chief information officer of Yes Bank.