Payment data delivers loyalty

Loyalty as a business advantage cannot be overstated. Just a 5 per cent increase in the number of loyal customers can improve turnover by as much as 90 per cent, according to the Harvard Business Review.

Electronic payment systems have a basis of data that can be acted upon, but it’s the ability to tailor a customer relationship that offers the most power.

As Philip McHugh, chief executive of Barclaycard Business Solutions, says: “Data drives relevancy, which then drives consumer purchase. Electronic payments can provide valuable insight and data analytics, which can help provide improved personalisation, relevancy and timeliness of products and services offered to consumers.”

PayPal is a good example, as the mobile app also contains GPS (global positioning system) information that allows businesses to push local services to the customer where they can pay with PayPal. DBS Bank in Singapore does just this using data analytics that can match customer locations to make personalised offers. This geospatial insight into consumer behaviour is transforming how businesses communicate and understand their customers.

The gold standard is the Tesco Clubcard that has been leveraged by the company to massive success. The level of insight that the card offers is massive and allows Tesco to see buying patterns that influence every aspect of its business. Electronic payment systems are set to eclipse this success, as they reach further and offer more depth with consumer profiling.

Electronic payments can provide valuable insight and data analytics, which can help provide improved personalisation, relevancy and timeliness of products and services offered to consumers

The granular view of consumer spending that electronic systems presents is unprecedented. Big data principles can be applied by any business to gain a 360-degree view of their customers that, on a practical level, produces rich data that can be acted upon. This data enables enterprises to see customer preferences, why they switch brands, what they will buy next and why they recommend one product or service over another.

“The big data era brings the analytics of the now,” says Karthik Krishnamurthy, vice president, enterprise information management, at Cognizant. “Real-time insights about each customer are based on advanced statistical analysis and machine-learning techniques on very large datasets of granular payment data.

“The granular data lays the foundation for mass-personalisation in lieu of the old segmentation methods. As each customer’s response is processed, it is analysed to provide inputs about campaign effectiveness, brand loyalty, changing spending habits and profit or loss.”

Shane Fitzpatrick, president and managing director of Chase Paymentech Europe, adds: “Data mining requires a combination of business acumen, analytical creativity and technical expertise. By developing the right processes and culture, businesses can identify where the real value lies within its data.”

This is being demonstrated by Uber that has developed an app, which not only allows users to manage their travel, but also make payments seamlessly. This level of integration is evolving for the entire retail sector which will eventually be able to integrate point-of-sale, mobile and online sales data, plus a raft of other consumer profile information from social media, for instance, to gain commercial insights into how, why and where customers shop.

Starbucks, for example, claim that 10 per cent of in-store sales are driven by its mobile wallet app. The insight that these transactions gives the company is a goldmine of information that can inform every new communication the business has with individual customers.

Current electronic payment systems may offer a somewhat brute-force approach to data analysis. They are able to show consumer purchasing history, but few can analyse in depth why a consumer bought an item from a particular retailer. This is where big data can make a huge difference, as it takes several data sources and combines them with payment information to give insight into consumer behaviour that has not been possible for retailers in the past.

Understanding payment behaviour and how this can be used as the basis for adding value to services is at the core of what electronic payment data can offer. The merging of key data sets, including geospatial and geo-demographic data, is creating an environment which, when payment information is also included, results in customer profiling that can direct real-world promotions and campaigns.

Payments and data analytics are now rapidly evolving to profile individual shoppers to a level where intimate purchasing habits can be identified, but more importantly, predicted.