Adyen and Affirm have partnered to offer merchants the option of allowing customers to pay over time — either online or in-store.
The collaboration comes as shoppers increasingly vie for alternative payment options such as paying in automated installments. Buy now, pay later is particularly favored by credit card wary Millennials, but is also gaining momentum with other demographics of consumers.
Adyen described Affirm’s solution as “a payment method that provides consumers a transparent way to pay over time online and in-store” and noted that through a single integration, the company’s “merchants can now add Affirm as a payment option with a few clicks.”
“By offering Affirm at checkout, both online and in-store via QR code, merchants can give their customers the option to split the cost of their purchase into installments and pay monthly or every other week, choosing a schedule that best fits their budget, without hidden or late fees,” Adyen said in a statement.
Brian Dammeir, president of North America at Adyen, said the deal with Affirm “makes sense as the demand for pay-over-time payment solutions has only grown in recent years in the U.S., especially gaining traction as more people have been staying home.” Dammeir said its retail partners are seeing demand for these payment options directly from their customers.
Silvija Martincevic, Affirm’s chief commercial officer, said shoppers are “increasingly looking for flexible and transparent ways to pay, and merchants who enable these types of payment options can rapidly accelerate their own sales.”
Affirm’s has 6,000 merchant partners, and the brands include Adidas, Bonobos, Casper, Dyson, Oscar de la Renta, Peloton and Walmart, among others. The retail brands using the payment solution “see an increase in average order value and overall sales,” the company said, adding that last year, “merchants using Affirm reported 85 percent higher AOVs [average order volume] when compared to other payment methods, and in the first half of 2020 nearly 70 percent of Affirm purchases were from repeat users.”
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