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Sameet Gupte is senior vice president and managing director Europe for Virtusa Corporation

Loyalty is key to business success – and banks that can bring data and technology to bear to achieve it stand to gain the most, writes Sameet Gupte, senior vice president and managing director for Europe at IT consulting and outsourcing company Virtusa Corporation.

The pride and joy of every business is a loyal customer; one that believes in you, and trusts that they will get the best possible value every time they use your services. Trust is a very strong and intangible emotion, which translates to long term loyalty; therefore every business has a responsibility to proactively look after and continuously improve in order to help build and maintain this trust. In terms of business metrics, selling to a loyal and existing customer costs lower than acquiring a new one.

Today, this experience of loyalty is being constantly tested: the ease of transferring accounts, commoditisation of products and services, and transparency through regulatory requirements, has translated into a volatile customer base. However, there are a few banks that have tapped into customer behaviour and gained the sought after status of an “Advisor”.

Over the past 18 months, some of these banks have demonstrated double digit growth in retail customer numbers in some markets, while at the same time also successfully growing their private banking portfolios.

So what is the secret to their success? Very simply, they are adapting and listening to their customers through the available data, and adopting new technologies to create a richer customer experience.

Mobility: Be there for your customer – anytime and anywhere 

Statistics show that 60% of people in the UK have a smartphone and more than 80% of individuals in the age group of 18-24.  These devices not only enable phone and internet, but the GPS feature provides the ability to locate the device accurately. The “trusted” banks have leveraged this feature to create ‘Geospatial’ banking apps, which the customer can download on their smartphones.

Imagine sitting in your favorite restaurant, enjoying your food, when suddenly you get a ping on your smartphone screen: “Hi John, we see you are dining at ABCD restaurant. As a valued and loyal customer of our bank we would like to offer you a discount of 10% on your bill today. Please swipe “ACCEPT” to redeem the discount.”

A QR code is generated on your screen (very similar to the ones generated for the boarding passes), which can be scanned by the restaurant and the discount is applied against your bill. You just saved 10%.

This application not only creates a unique customer experience, but it also allows the bank to store the location and transaction data. As such, the next time you are in the vicinity of the same restaurant, the app can prompt you with a discount and also make available the details of similar restaurants around your location where it can offer similar discounts.

Another example of this is the “In Store- Retail” experience, which some banks have tapped into. Imagine you enter a Sainsbury /Boots/M&S, or any other retail store. As soon as you step into the shop, the bank’s geospatial app quickly highlights all the various discounts and sales that you are entitled to in that shop.  As you buy your groceries or other items, you just tap the item on your phone.  At the end of the shopping you swipe a finger to generate a QR code which gets scanned at the Point of Sale machine and the cumulative discount is applied. The payment is then made through the mobile wallet. Making the entire shopping experience personal, economical and within the security of your bank’s app.

At the backend, banks are tying up with these popular restaurants and retailers to get volume discounts, which they can pass directly to their customers: thus creating a new business model for the banks and retailers.

Everyone wins: the customer saves money; the bank gets the transaction and the loyalty; and the restaurant/retailer gets a volume commit business from the bank.

Data Analytics: Know your customer’s habits and preferences

The data acquired through the multiple mobile transactions and geospatial apps are a gold mine of customer behaviour.  A few banks are using this data to analyse spending patterns based on locations and pro-actively engaging with the customers.

For example: Dave lives in London and every week shops for his regular groceries from the retailer round the corner from his residence. The geospatial app has been helping Dave save money every time he goes to this shop. The data gathered over the past few months enables the app to analyze:  shopping frequency, amount spent, typical time of the week/month, travel route to the shop, etc.

Last week Dave threw a party and paid everything by his credit card. He wakes up in the morning and starts walking towards the grocery store for his regular shopping trip, he gets a ping. “Good morning Dave. You currently have a balance of £1800 on your card and your limit is £1850. Your average grocery bill over the past 3 months has been £75 with all discounts applied. Would you like to pay part of your balance?”

The app just saved Dave an embarrassing trip to the store by analysing all his trips down this route, the frequency of those trips and the typical costs involved during those trips.

Knowing the spend pattern and the location, the bank’s app can use the data to validate whether the customer has enough credit limit on the card, and if not, can send a ping to let the customer know that he needs to pay the credit card bill.

There are many examples of this nature, where the app analyses the data of the various journeys undertaken by a customer for business on the tube/National Rail. If the customer was to travel a particular route every day/week, the app would use this data to analyse the best possible cost options: a weekly pass, monthly pass, or a pay as you go Oyster. The bank’s app would then send a ping offering the best possible option which could be purchased through the mobile wallet. Alternatively, it could offer a possible discount on long distance train journeys. In this instance, the bank would have tied up with the rail service provider, just like with the retailers.

There is no magic formula to loyalty – It will always be trust and advice.

But what these banks have been able to tap into is the use of mobility and data analytics through geospatial applications and innovative partnership models. Through using technology to create these innovative pay-backs to customers, banks can build all-important trust by highlighting the best economic value, and saving the customer money, or providing wise advice by knowing and understanding their behaviour.

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