When it comes to online returns, the stats aren’t pretty. Consumers return 30% of ecommerce purchases and a study from Shopify reveals that 40% of consumers buy variations of a product online intending to send back most of the order.
In many cases, returned items cannot be put back on shelves due to product obsolescence (this is especially true with fast fashion and technology items) or slight wear and tear. This ever-increasing number of online returns is causing profits to take a massive hit.
While 2019 saw a rise in retailers cracking down on serial returners and implementing a more efficient and sustainable approach to the handling of returned and excess stock, the issue isn’t being solved at a fast-enough rate. Retailers need to look closely at how they manage returns, the value of which could reach $400 billion this year—not including inventory losses or restocking expenses. Artificial intelligence (AI) and augmented reality (AR) being among the latest kinds of technology retailers can use to meet the challenge.
According to Global Market Insights, investments in AI within the retail sector will exceed $8 billion by 2024. As more applications for machine learning (ML), predictive analytics and deep-learning technologies are emerging, digital disruption in the retail sector should increase at a rapid pace.
AI can serve as a competitive advantage for retailers when it comes to gathering customer data. These intelligent systems learn from the behavior and habits of every customer. As the technology evolves and the capabilities mature, retailers will realize additional benefits beyond their original expectations—with offerings such as greater operational agility and the ability to make faster, smarter decisions while improving customer experience.
When it comes to using automated analytics and AI to deal with returns, some retailers turn to SaaS inventory management software to determine the best channel for an item once it returns to the warehouse. Whether it’s to re-shelve, refurbish, liquidate or scrap the item, an automated process allows retailers to process, reroute and track merchandise, boosting efficiency quickly. Some retailers are even leveraging AI to provide data-driven disposition decisions at the point of return (at the actual return counter).
Automated apps that specialize in helping retailers manage online returns are also hitting the market. For example, Returnly is an app that facilitates product returns and provides an instant return to the customer.
It’s not only AI that is playing a key role in combating retail returns. Retailers are investing heavily in AR so customers can accurately see what the item would look like in their environment before they order it. It started in the beauty industry with mirrors that allowed customers to see what they would look like in a particular shade of lipstick or blush.
This concept is expanding into the broader retail industry as retailers realize the benefits AR could bring—with the hope of driving engagement, increasing sales and reducing returns. IKEA’s AR application, IKEA Place, is a good example. The app allows customers to drop virtual furniture into their own homes and view it through their smartphone camera.
In other cases, shoppers can trigger animations showing how products work, so they are familiar with the product before they even buy it. For example, Nespresso uses AR technology to enable customers to explore its range of products, and customize them specifically for their homes, helping customers to make well-informed purchasing decisions by allowing them to try before they buy.
When people have a clearer idea of size, color, and style, it reduces the likelihood of buyer’s remorse and, ultimately, their chance of returning.
While AI and AR will continue to be an integral part of the retail landscape, they will never address all aspects of the returns process. For returns slated for liquidation into the secondary market, retailers should think about using technology. For example, some of today’s largest retailers are using their own B2B online auction marketplaces to sell returned and excess merchandise directly to business buyers around the country. Using this kind of online auction channel sets up a dynamic where many buyers are competing for the inventory; this pushes up the prices and allows for a faster sales cycle. It also produces real data on secondary market pricing.
The current behavior associated with returns will continue and retailers need to take their returns-management processes seriously. The best plans will include both pre- and post-returns strategies, incorporating AI and AR, as well as a viable solution to offset the maximum amount of loss for the inventory that can’t go back on shelves.
B-Stock Solutions Inc. runs auction sites for the inventory retailers want to off-load.