In recent years, more and more banks have grown curious about data-driven customer experiences and how to tap into their potential. Over the past few weeks, however, it has become clear that their ability to connect and cater to customers digitally will not just boost their bottom lines. It will make or break them in the (very near) future. The market turmoil sparked by the coronavirus outbreak will hopefully make them realise one other thing. That is, they’re sitting on a goldmine of consumer data that can help them get closer to their customers than ever before – and drive growth even in an increasingly volatile world. 

Probably the most valuable information banks have on their customers is transaction data. Not only because financial transactions show how people bank, mind you. But rather because they show how people live. In other words, the way people spend (or don’t spend) their hard-earned money tells a lot about their lifestyles, habits, preferences and how these change over time. Meanwhile, transaction data offers banks invaluable insights into customers’ needs and how to satisfy them. So let’s see some examples of how banks can turn it into more engaged customers and bigger sales. 

In W.UP’s case, customers are profiled based on variables related to their everyday lives. Their housing profile shows if they own or rent a flat and, based on utility bills, how big that flat might be. A customer’s car profile shows their preferred way of transport, the sports profile the type of workout they’re into, while their entertainment and dining profiles classify them as fast food lovers, fine dining enthusiasts, cinema-goers, festival fans and so on. Finally, people fall into different banking and income profiles, too, based on what banking products they have, what banking channels they use and what type of income they have coming in. 

In the simplest sense, profile building is putting customers somewhere on a scale between two extremes. Which will result in loads of variables and, eventually, new ways to laser-target customers.

Let’s take grocery shopping as an example. A customer’s grocery shopping profile includes how much they spend on groceries each month, how much they spend on average, when and how often they typically do their grocery shopping and which stores they usually shop at. Now, let’s say that their bank has just partnered with Supermarket A for a joint loyalty programme. Using the relevant profile variables, the bank can easily select customers who, based on their spending history, prefer shopping at Supermarket B and offer them 3% cashback if they do their grocery shopping at Supermarket A and use their credit card. 

But that’s not nearly all. The real value of customer profiles lies in the fact that they’re constantly changing, one transaction at a time. Being able to spot these changes and respond to them with just the right offer or advice can mean a huge competitive edge for financial service providers. 

If a customer suddenly starts travelling a lot, their bank can approach them with an offer for a travel credit card, foreign currency account or travel insurance, depending on its business and sales strategy. If someone has recently become a homeowner, they might be interested in taking out a home improvement loan or home insurance. A customer has a bigger salary coming in than usual? Why not give them advice on what product they should invest their extra income in and how much their investment would yield? 

Customer profiles, of course, not only help banks follow through with their business goals but also serve as the input for setting them. Knowing how many of a bank’s customers are frequent travellers, love fine dining restaurants or have a passion for cycling can offer deep, actionable insights for product development, sales and marketing.



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