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Expert opinion

The smart use of data analytics for personalisation of payment methods

Thursday 11 July 2019 | 09:39 AM CET

Ramya Alagappan, Senior Consultant: Drawing the line in the right place is paramount in the usage of data analytics for a personalised experience

The last two years have seen an explosion in digitisation of payments and there is a plethora of options available for customers these days. This leaves the merchants or their payment service providers with the challenge of offering the right payment methods. Not having enough payment options accounts to 7% shopping cart abandonment according to an infographic from Invesp.

The industry is currently dominated by the following payment methods, with several offerings for each one:

  • cards (Visa, Mastercard, American Express, Discover, Diners Club, etc);

  • cash;

  • bank transfers (SEPA, ACH, Giro, BECS);

  • e-wallets (Google Pay, Apple Pay, PayPal, Alipay, etc);

  • prepaid store wallets;

  • digital currency;

  • gift vouchers.

Most merchants these days do provide one or more options from each of these methods. But the challenge is choosing the right mix, to ensure that all relevant options within each method are offered for the particular sale. The solution should also ensure that the checkout page is not cluttered and the cost of maintaining various payment options is justified.

Obviously, there is no ‘one size fits all’ solution here. Human beings are always delighted by an exclusive experience and in the bygone days all services were personalised and served by the local network. This was flipped by the industrial revolution, which focused on mass production. But the era of personalisation has been brought back now, with the advent of big data and the various analytical methods that are available to process data and offer a personalised experience.

Retail has always made use of data, to understand customer behaviour and target them with relevant products, ad campaigns, offers, etc, both in the brick-and-mortar and the virtual world. Personalisation in the payment methods offered to customers is something that is picking up, and it is expected to see more traction in the coming years. One early and simple example of this was the issuance of personalised cards, where the user can choose the graphics of the card, thereby providing them a customised experience. From physical cards, the payments world has moved on to mobile wallets, wearables, and now towards invisible payments, with mobile voice assistants like Siri or Google Assistant, and chat bots like Alexa used to make a payment.

It is clear from the inset data that the payment method preference varies based on geography. It is also influenced by factors like age and affluence. The pattern differs within each payment method too. For instance, within e-wallets, though PayPal, Google Pay, and Amazon Pay are popular in most European countries and the US, China uses WeChat Pay. Even within Europe, Turkey predominantly prefers BKM (Interbank Card Center of Turkey) over PayPal.

There is a lot of transactional data that is collected today aided by various big data technologies and cloud solutions that ease the storage problem. This data can be used to arrive at and to display personalised payment options to customers, based on their payment history and other demographic details. Some existing implementations in this space are:

  • Most online retailers store the customers’ preferred payment method and the payment instrument details (like a credit card) where permissible. This enables quick payments via mobile apps and ecommerce websites.

  • PayPal has introduced Smart Payment Buttons, which – based on the location, cookies, and specific options that can be set up by the integrating merchants – dynamically present payment options that are more relevant to the customer. This means that the merchant can do away with a huge list of all possible payment methods, which brings down the checkout experience. This comes along with PayPal’s One Touch (single click payment system) and Shopper Insights tool, providing aggregated and anonymous data about PayPal customers’ shopping trends, which can help merchants devise a personalisation strategy.

  • Small to mid-sized ecommerce businesses use Google Analytics on their sites to track customer trends, including payment transactions. It offers options to track payment methods, and this data can be used by merchants to provide better payment options for their targeted consumers.

There clearly is scope for products that use a customer’s historic payment data with artificial intelligence and machine learning to deliver better personalised options for each shopper. The payment options provided can also be linked with various offers and loyalties available on the product that is being purchased, and the order of display can be driven by that. This will be a luring factor for the customer and will lead to an increase in conversion rate.

In summary, there is a lot of opportunity in personalising payment methods and several payment service providers are already exploring this space. The industry will also have to keep in mind that drawing the line in the right place is paramount in the usage of data analytics for a personalised experience to ensure that the customer does not find it intrusive or less secure. This is all the more important with payment information in addition to complying with the regulatory bodies. Achieving this balance is something that all innovators in this space should watch out for.

References

1. https://economictimes.indiatimes.com
2. https://www.billpro.com/increasing-global-sales-with-alternative-payment-methods/
3. https://www.paypal.com/
4. https://www.ppro.com/reports/

About Ramya Alagappan

Ramya Alagappan is a Senior Consultant within a prominent consulting company. She specialises in the field of cards and payments, and she has been involved in various projects that deliver IT solutions for banks across the globe.

 

 

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