Payments Innovation

Why Payments Personalization Is Key To Enhancing User Experience For Digital Content Platforms

Getting consumers to subscribe to digital content is mostly an all or nothing endeavor: pay up via a standardized subscription paywall or go without accessing the content, says Trevor Kaufman, CEO of SaaS firm Piano.io. In this month’s Payments Orchestration Playbook, Kaufman discusses the importance of moving past this one-size-fits all approach to one that gauges consumer interest to determine whether paying per month, per piece or something else will maximize conversion.

Consumers have come to expect personalization in their shopping experiences, whether using online marketplaces such as Amazon and Etsy or mobile apps such as Gilt or Poshmark.

Product recommendations, informed by purchase histories and preferred payment methods, are becoming a standard aspect of digital checkout experiences.

Online content subscription purchasing experiences are far different from that ideal in practice, however. Magazines, newspapers, television networks and other content providers typically offer more uniform interfaces that may not consider their customers’ geographies, content or payment preferences.

The standard approach to conversion that has been representative of the digital content ecosystem — the paywall — could be on its way to becoming a thing of the past, according to Trevor Kaufman, CEO of New York City-headquartered Software-as-a-Service firm Piano.io, which offers an assortment of artificial intelligence (AI)- and machine learning (ML)-enabled content management products. Kaufman explained in an interview with PYMNTS how payment and content customization can impact consumers’ digital user experiences.

Businesses generally prioritize getting customers on eCommerce sites or digital content platforms to make purchases above all else, and digital content platforms have leaned on paywall strategies to increase conversion. Consumers are eventually restricted from viewing site content until they subscribe or pay for additional access.

The trouble with deploying a paywall as a one-size-fits-all approach is that not all consumers are willing or able to commit to a subscription to begin with. Content platforms can thus lose potential customers who might not have wanted to pay for subscriptions but who may have considered paying piecemeal for access to specific articles, videos or other media. Kaufman said he believes that a more customized approach to content monetization can help viewers have a better user experience by providing payments options that meet consumers when, where and how they want so as to ultimately help convert them into full-fledged buyers.

A Data-Driven Approach To Enhancing The Payments Experience

Content platforms can enhance their customers’ experiences by providing payment methods that match clients’ specific preferences, according to Kaufman. This means leveraging data analysis to match consumers with the payment methods they are most likely to use, and then providing them with both those payment options and interesting content.

“Certainly, if Ashley pays with an American Express Platinum Card, and I pay with a prepaid Visa debit card, I’m probably a bit more liquid and [likely to cancel my subscription] than she is — I might have different content preferences,” Kaufman explained.

Knowing what payment method consumers like Ashley prefer in this scenario is one of the key pieces of information that can be fed into AI-powered predictive systems to help platforms extrapolate not only whether individuals might be interested in certain content but also the likelihood that they will ultimately purchase or subscribe if offered certain payment options.

Offering local payment methods is part of the drive to provide customers with the payment methods they prefer. The same data analysis tools that are used to detect customers’ preferences for debit over credit cards can be used to pinpoint their geographic locations and identify the payment options that are popular in each. Tools that use AI and ML can help secure and automate the functions needed to make cross-border transactions compliant with local regulations once options are in place, and they can also help merchants determine which payment gateways might be able to ensure the highest transaction success rates. These systems can also be used to selectively show content that users are most likely to find engaging or worth purchasing.

AI and ML can also help offer payment options that subscribers might be unaware of but could prefer. One example: giving consumers the option of making purchases using a mobile wallet without having to open their own accounts.

“If you have Apple Pay configured on your phone, rather than show you a paywall where you’d have to log in [to access] really unlimited content [such as by becoming a subscriber], we will say, ‘You can buy right now, you know, [with] Face ID [or] Touch ID,’ and you are doing no new logging in [or] creating an account,” Kaufman explained.

The added time and effort users might save by using a mobile wallet they already use often entices them to subscribe because the sign-up process is faster and easier. It therefore converts consumers who might not have been willing to commit to a full subscription if doing so required spending a great deal of time and effort entering their personal information.

Custom Content For A Personalized Internet

The implications of using this type of data-driven model go far beyond the payments experience, too. AI and ML tools can also be used to customize the type of content different users encounter to begin with. Kaufman likens the personalization of digital content to the customized shopping experiences on eCommerce retail sites. The difference is that consumers browsing the sites of their favorite magazines and newspapers might receive recommended articles and videos rather than suggested articles of clothing or other products.

“[Women] are going to get certain recommendations for clothes that are for women, and I’ll get recommendations for clothes that are for men, and that’s the kind of simplest way of thinking about it,” Kaufman said.

Readers are therefore exposed to more personalized content and less irrelevant content.

Kaufman explained that using AI and ML systems can also mean two different users could potentially never see the same content, even if they were browsing the same site at the same time.

“If you were to go to Marketwatch.com, you would see a different Marketwatch.com than I would, because we are dynamically reconfiguring that webpage for Dow Jones to show content that is more likely to make you click,” he explained.

User A might therefore enter the site and see homepage A, while user B would enter the site to see homepage B. User A might then click on one of the articles on homepage A and encounter a paywall, while user B could click on the same article and encounter no paywall on the same page — and perhaps never encounter a paywall at all.

Algorithmic tools like these that harness data and predictive analytics can therefore help companies drive conversion in a time when consumers have access to countless digital content options. The space continues to grow more competitive, and digital content platforms’ success will hinge on their ability to tailor their products, content, services and payments to meet the preferences of current and potential customers.

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NEW PYMNTS DATA: HOW WE SHOP – SEPTEMBER 2020 

The How We Shop Report, a PYMNTS collaboration with PayPal, aims to understand how consumers of all ages and incomes are shifting to shopping and paying online in the midst of the COVID-19 pandemic. Our research builds on a series of studies conducted since March, surveying more than 16,000 consumers on how their shopping habits and payments preferences are changing as the crisis continues. This report focuses on our latest survey of 2,163 respondents and examines how their increased appetite for online commerce and digital touchless methods, such as QR codes, contactless cards and digital wallets, is poised to shape the post-pandemic economy.

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