Improving services with life-cycle systems
Life-cycle engagement models allow targeted communications, and the customer experience is richer and more meaningful
There are many ways of delivering superior customer service. One of them being identifying and understanding customer need, whether latent or overt, and matching that need with appropriate solutions. While this testament holds good for every product line, it manifests itself copiously when it comes to the banking and financial services industry.
Customer engagement as a concept has evolved to a very different level in banking. A decade ago, when a mutual fund new fund offer (NFO) would be announced, a relationship manager would start calling customers one by one from his/her contact list in an effort to get the maximum number of applications. There was no effort made to map customers’ need or propensity.
A superior experience for the customer unfolds when a bank is able to aptly map the engagement theory in a life-cycle format. Thanks to the use of analytics for insights on consumer preferences, engagement with customers is targeted and sharp, and the customer experience that we can now deliver is richer and more meaningful.
The use of analytics in the banking industry in the country is still evolving. From macros to statistical tools to machine learning, the world of analytics is undergoing a transformation and, in its wake, infinite opportunities are opening up.
Why life cycle
For a large proportion of the population, life unfolds in a set pattern. It is the individual’s initiative and ambition, on the one hand, and circumstances on the other that may alter the course by varying degrees. A bank’s analytical framework should be able to pick these variations/deviations, map the corresponding next best offer (NBO) and communicate this to the customer. In other words, while one would have assigned a sequence to NBOs linked to a customer’s stage of life cycle, one also has to be alert and cognisant of the events simultaneously taking place in a customer’s life and realign communication accordingly.
Further, life-cycle-linked engagement cannot follow a standard pattern across the customer base. It is important to identify different personas and sub-personas within the customer base, powered by certain homogeneous attributes. At the most basic level of segmentation, a persona can be built around the combination of age-gender-job profile. As you delve deeper, one can bring in behavioural dimensions, powered by text-mining and data-scrapping. The need to map customers’ behavioural dimensions has its relevance in the realization that consumers are also evolving with time. As they move forward in their life cycle, their behaviour undergoes a change, linked to their learning curve and capability enhancement.
How to use life cycle
There are small cues and nuggets that provide hints around changes in one’s life cycle. To take a simple example, a woman account holder who wants to change her name from maiden to married. Or a male account holder who converts his singly-held account into a joint account with his spouse. The data engine should be able to map these changes and immediately update the NBO algorithm to make it a win-win for both the customer and the service provider.
Incidentally, the NBO is not restricted only to products, but covers services and, in the context of banking, regulatory fulfilment as well. For example, a minor turning into an adult needs to update his/her know your customer (KYC) forms. It also gives the bank an opportunity to proactively reach out to the young consumer with some customized offerings and enables the customer to get a head start in financial planning.
Today, powered by behavioural insights, offers through alliances also play a big role in maintaining the continuity of engagement with consumers and providing relevant value addition to customers. For example, when the nature of debits in a savings account indicates spending on dining or entertainment, it is immensely relevant to extend discount offers around these categories. It not only helps in ensuring repeat payment engagement and increasing share of wallet, it also help foster greater affinity with the customer.
Finally, service providers can increase efficacy of engagement when they communicate through a medium that the consumer is most likely to connect with. Driven by the emphasis on digital in current times, it is standard practice to resort to emails or notifications on mobile apps as the preferred way to communicate. But there is a section of customers that still prefers an in-person conversation rather than interacting with faceless mediums. If we ignore this dimension, there is a high probability that we would lose out on those customers. Hence the importance of mapping channel affinity in the overall life-cycle engagement model.
These tenets extend to cover data privacy and customer convenience as well. There are customers who have registered their numbers on the National Do Not Call Registry and every service provider has to be mindful of this and respect a customer’s preference. This includes giving customers an ‘unsubscribe’ option on email-based communication.
The more successful service providers are the ones that have been successful in understanding and implementing the principles of customer engagement through the lens of life-cycle management.
Puneet Kapoor is the senior executive vice-president at Kotak Mahindra Bank Ltd.
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