AI Poised to Even the Returns Playing Field for Retailers
A couple years ago retailers set a series of events in motion that inadvertently created one of the industry’s biggest challenges: how to manage the exponential rise in product returns while also meeting customers' high expectations. As it stands, artificial intelligence (AI) may be the only solution.
How it Happened
It all started with pure intentions. Retailers wanted to make returns easier for customers to inspire greater brand loyalty. This was especially true for e-commerce companies, like Amazon.com, which wanted to incentivize shoppers to buy more products online. As a result, several companies started changing their return policies. Stores began making returns free, extending policy time limits, allowing customers to shop online and return in-store, and even stopped requiring IDs and receipts in certain cases.
Unsurprisingly, retailers saw an explosion in online shopping and repeat business as a result of their efforts. But in a classic case of be careful what you wish for, retailers also saw an explosion in the rate of returns. Brick-and-mortar returns are now 10 percent of sales, and e-commerce returns grew to about a third of all purchases!
That's a nearly $550 billion problem for the industry. And companies that can’t afford to absorb the costs are struggling the most. As a result, many smaller retailers have pulled back on customer-centric returns policies. But the genie is out of the bottle, and nearly 50 percent of retailers are offering free return shipping today.
As a result of such lenient policies, customers’ expectations have permanently shifted. According to data by Invescpcro, 92 percent of customers will buy from a store again if returns are easy, and 79 percent expect free shipping. Moreover, 67 percent of shoppers check the returns policy page before purchasing a product to make sure it meets their standards.
Lenient policies are no longer a nice-to-have. They're a requirement for retailers that want to compete in an increasingly competitive marketplace dominated by a few major players. Luckily, emerging AI-based technology promises to make returns profitable and manageable for companies of all sizes.
Emerging AI Technology: Disposition Engines
Large retailers with the most capital and incentive, such as Target, Walmart, Amazon, and Lowe’s, are already investing in private tech companies that promise to deliver AI for smarter returns. The goal of these systems, known as disposition engines, is to reduce the inefficiencies at every step of the returns process, reduce transportation miles, and increase the recovery of every item by eliminating human bias and diminishing costly touchpoints.
How Disposition Engines Work
For example, in most retail environments, store clerks receive returns and inspect them to determine the condition of the product. If the item seems damaged, the clerk generally has to choose between returning-to-vendor, returning to a processing center, or earmarking for disposal.
The choices seem simple, yet store clerks don’t have the time or resources to determine the financial implications of their decisions. With disposition engines, employees can scan an item and follow real-time instructions to determine the most profitable path of the item. Not only does this make a better business decision, it also reduces time and overhead investment. The story doesn't end there, however.
Disposition engines continue to support retailers throughout the entire lifecycle of a returned product through deep data and learning algorithms. In fact, DEs intelligently determine the value of returned and used items by weighing the cost to refurbish them against the potential resale value of each item. And in cases when the engine is presented with a unique SKU that it has never analyzed before, DEs will adjust to compare similar items in the marketplace.
Once the system determines that a returned item is valuable enough to resell, it then decides how, where and when to sell it to beat the competition and recover the highest profits. This marks a huge contrast from the manual method many retailers employ today, where teams of business analysts analyze marketplace data to determine consumer demand and price point. However, if retailers' sole strategy is competing with the lowest possible Amazon price, they'll struggle to make a profit. Instead, retailers must use DEs to carve their own market share.
Disposition Engines: The Great Equalizer for Retail Returns
Disposition engines promise to revolutionize retail returns and fortify customer-centric returns policies across the industry. But right now, the technology is scarce and cost prohibitive for small and midsize retailers because it's new and continuing to develop.
The good news? Industry experts predict that DEs will be available for any company to use, no matter their size, in the next two years or less. Similar to the way Shopify and WordPress made it accessible for companies with small budgets to produce impeccable websites, disposition engines will allow small businesses to compete with big businesses’ customer-centric — and costly — returns policies.
With affordable technology to make returns profitable, smaller retailers will be able to process a higher volume of items without suffering major losses. That means they’ll be able to drive customer loyalty and increase market share.
Thanks to AI, customers can expect more lenient returns policies from more of their favorite brands. And reputable retailers with must-have products will be able scale their businesses to new levels — mega budgets not required.
Daniel Ray is vice president of product development at goTRG, a global technology company that offers the first fully managed reverse logistics solution for enterprise retail clients.
