The Ideal Purchase: Payment Systems and Plans, Fraud, Returns and More

What makes the perfect shopping experience for your customers now? As online shoppers get used to better and better ecommerce experiences, it’s no longer enough to have one or two standout elements along the path to purchase. Now, retailers need to review every step along the way to ensure a journey that’s perfectly convenient and reassuringly secure. That’s especially true in the areas of payment, fraud prevention, and returns—as reflected in the results of the most recent international ClearSale survey on ecommerce consumer attitudes.

Your Customers’ Ideal Payment Methods

Ease of payment can make the difference between a successful shopping visit and a visit that ends with an abandoned cart. Thirty-five percent of shoppers in the survey said they have abandoned online purchases because checkout was too complicated or took too long.

One way to streamline checkout for customers is to provide digital wallet options for payment. Seventy-one percent of survey participants said they sometimes or always use digital wallets to pay for online purchases rather than enter credit card information directly into the website.

With a digital wallet such as GPay, PayPal, or Apple Pay, customers only have to tap the digital wallet button and authenticate their identity to complete their transaction. The digital wallet can also autofill the customer’s billing and shipping information, to save even more time and avoid data entry errors that can raise fraud flags and lead to false declines.

Because digital wallets don't share customers’ payment account data with the merchant, they are also ideal for the 34 percent of online shoppers who say that concerns about where their data is stored limit their online shopping activity.

Frictionless Fraud Prevention for an Ideal Order Experience

Hitting the “Pay Now” button is one milestone in the ideal order experience. The next step happens on the back end, as the retailer’s fraud prevention tools analyze the order in milliseconds to determine the risk of fraud. Thorough and accurate fraud screening is critical, because card-not-present (CNP) fraud is rampant. That’s not surprising since the Merchant Risk Council reports that “fraudsters already have the information they need to make a purchase from more than 80 percent of the credit cards in existence.” Account takeover fraud is a growing threat to merchants and consumers as well.

If an order’s risk factors exceed the retailer’s threshold, what happens next can make or break the customer experience. If the order is automatically declined, the retailer loses the profit from the order and avoids a potential chargeback, but they may lose much more overall. That’s because false declines are much more common than fraud, and they drive customer churn. Aite Group research projected that false declines would cost nearly 70x more than fraud losses in 2021, and found that 62 percent of merchants reported an increase in false decline rates.

Why do false declines cost so much? Survey data gives us some clues. Forty percent of online shoppers say they’ll never buy again from a website that declines their order, which erodes the retailer’s marketing ROI and average customer lifetime value. In addition, more than a third say they’ll post a negative comment about the website on social media after a false decline, which can damage the retailer’s brand and increase the cost to acquire new customers.

To avoid these losses and ensure that legitimate customers have an ideal purchasing experience, automated order screening should be paired with manual review of flagged orders. Experts can quickly separate good-but-unusual orders from fraud to reduce false declines without permitting fraud. Then their findings can go back into the merchants’ AI and ML fraud detection programs to refine and improve them.

Convenient, Secure Return Processes

The ideal purchase continues after order approval, when the items arrive. If the items don’t meet the customer’s needs, the retailer’s return process should be simple for the shopper and secured against fraud. Both elements are critical as the average ecommerce return rate exceeded 20 percent in 2021 and may continue to rise.

Easy returns are critical for the 61 percent of consumers who say convenience is why they shop online rather than in stores. Prepaid return shipping labels, carrier pickups, and accessible drop-off locations are key elements of a simple return program. Retailers should also make it easy for customers to start the return process, ideally without having to speak to a customer service agent. If that process is too confusing or timeconsuming, customers may opt to dispute the charge with their card issuer instead, which can lead to a chargeback and related fees.

Merchants also need to screen returns for fraud, which accounted for more than 10 percent of total retail return value in 2021. “Wardrobing” and other forms of single-use fraud can be prevented with special tags that prevent fraudsters from wearing or using the item without removing them, voiding the return policy. Artificial intelligence (AI) and machine learning (ML) can also analyze customers’ return patterns to look for patterns that could indicate fraud, such as frequent returns of high-end clothing for being the wrong size, without ever reordering the same item in the correct size. Measures like these can help weed out fraudsters without negatively impacting the customer experience.

Continuous CX Improvement with AI/ML

AI and ML have a clear role in the fraud-prevention aspects of the perfect purchase experience. They can also help retailers with ongoing improvements in personalization and CX at every touchpoint in the shopping journey. Harvard Business School and Boston Consulting Group advisers report using AI and ML for personalization initiatives that have yielded net incremental revenue increases of 40 to 100 percent. The Harvard Business Review recommends using AI to “reimagine the end-to-end experience as a seamless flow” that moves with the customer across channels and creates experiences that match the customer’s context.

When businesses unify their data, they can start to do more with AI and ML to build more convenient and relevant experiences, test the outcomes, and maintain a focus on frictionless security. That approach can bring them closer to delivering the perfect purchase experience for each customer, every time.


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