Analytics for the New-Age Customer

Who is a new-age customer? Is it my son, who thinks an internet breakdown resulting in Netflix breakdown is more severe than a bubonic plague? Or is it my mom, who still uses mobile like a landline telephone (“only in case of emergencies”) and does not have a smart phone yet? Or is it me, who works to build state-of-the-art digital systems for banks and convince customers to adapt to the same while at the same time, thinks twice before registering for an UPI address? (“Fear of online fraud”)! Well, it is a culmination of all these three and much more.

Words like Digital, State-of-the-Art, Ubiquitous, 24*7, etc. were the buzz words of the era gone by. These are considered the bare minimum now. With such a tremendous change in customer experience and expectations, we need to up our game by putting the customer at the center of everything we do. We need to personalize content in such a manner that the customer does not go looking for a product or service elsewhere. This is where analytics comes into the picture. Data can be leveraged for figuring out the likes and dislikes of the end customer and in turn playing on their preferences to fine tune the end product to cater to their needs.

Over the past few months, every Monday morning, I receive an email which tells me how I have spent my time the previous week. It gives a detailed split into time spent over calls, communicator, meetings, etc. It also suggests behavior patterns like how I schedule my meetings with others (“always at the last minute” of course!). Initially, I did not realize what I would achieve from this, but over time, I have taught myself how I can use this data to better utilize my time. And these kind of insights do not stop here. My banking mobile app now suggests how to round off my transactions and invest that rounded off portion into a deposit account. My food delivery app notifies me whenever my favorite restaurant has good offers and so on and so forth. Data is everywhere. Tapping into this data has already begun at a tremendous pace.

Any new analytics use case design and implementation need to take care of the following:

Proper implementation of analytics in the financial industry could lead to better business outcomes for the institutions and at the same time, more satisfaction for the end customers. From the customer’s perspective, there can be many small delights in the user experience like reminding the customer to order a new cheque book when the old one is about to run out of leaves, appreciating the customer for maintaining a good credit score, or suggesting a better credit card with more benefits based on the user profile which will improve their loyalty and hence ensure continuation of business.

Similarly, from the perspective of a financial institute, suggestions to prevent approving loans to customers with certain predetermined combination factors, predicting when a customer is likely to default (and hence strengthening their collection mechanism), providing data on profitability of various products and hence aiding the decision making about products at a sunset, can help do significantly better business.