Once novel technologies, such as e-commerce platforms, mobile apps, and targeted advertising, profoundly reshaped the direct-to-consumer retail industry. Early adopters of these technologies saw exponential growth compared to other brands jumping into the fray later in the game.
Today, computer vision technology, non-fungible tokens (NFTs), blockchain solutions, and AI-driven dynamic pricing are on the verge of reshaping the retail experience yet again.
Computer Vision Technology
Advancements in computer vision and machine learning are likely to transform one of the biggest challenges facing retailers: how to identify incoming items. Currently, computer vision is leveraged as a merchandising tool to aid in the identification of similar items. Human intervention is still required though because often this technology can incorrectly categorize an item.
Greg Ferris, Trove’s Chief Product, and Engineering Officer predicts that sometime in the next year, new and compelling computer vision technology will advance beyond grouping products together for merchandising. The predicted solutions will enable brands to narrow a product down to a smaller, more specific set of items that would only require a human a few seconds to categorize.
Ferris’ believes new computer vision technology will transcend back-of-house merchandising programs. This technology will be rolled out to aid in branded recommerce solutions. Brands can leverage advanced computer vision tools with in-store kiosks and via mobile apps, to offer even more accurate and real-time information regarding an item’s trade-in value.
Several of Trove’s brand partners currently use computer vision technology, powered by Trove, to ease the sometimes-cumbersome task of categorizing apparel that is no longer carried, and thus, lacks a match to a catalog item. At lululemon, computer vision brings together the hundreds of off-catalog pre-worn tank tops they receive and helps sell them under a single SKU on their branded resale marketplace, lululemon Like New.
Beyond categorization, Trove may one day offer a computer vision solution that takes better measurements of pre-worn items, which, thanks to machine learning, is likely to grow more accurate over time. According to Ferris, much of this work is now done manually to account for normal wear and tear and tailoring. But with new computer vision technology, it will be possible to leverage a photograph of a pre-worn item to know its true inseam and waist size.
Dynamic Pricing Using AI Algorithms
Improved AI-driven dynamic pricing solutions for retailers will offer retailers new solutions to streamline their inventory control processes and pricing strategies in the near term. With dynamic pricing, premium brands will be able to adjust, on a constant basis, the price of their products based on supply and demand levels, overall market trends, and various website and customer metrics, among other factors.
While Amazon is perhaps the best-known retailer to deploy dynamic pricing, a report by digital commerce consulting firm Vaimo noted that over 20% of companies currently leverage dynamic pricing in their ecosystems, with another 15% planning to do so in the near term.
Apparel companies will also be able to leverage new dynamic pricing solutions in enticing ways to meet customer preferences. For example, if a retailer is experiencing a shortage of a particular article of clothing that is in high demand, dynamic pricing tools Trove is developing will be able to increase the trade-in value for particular sizes and colors that are missing from inventory.
In turn, Ferris noted that our partners should expect our offerings to soon provide data for setting a resale price. When deployed, dynamic pricing can help our brand partners to determine an item’s price based on inventory-related factors and other data points, such as website traffic associated with certain styles.
NFTs & Blockchain Technology for Apparel
Exciting new retail applications of blockchain technology and non-fungible tokens are also on the horizon. In fact, several leading retailers have already shown the power of these technologies to create value for their brands.
A collaboration between celebrated fashion powerhouse Balmain and Mattel’s beloved Barbie brand not only offered ready-to-wear apparel, it also included three NFT avatars featuring Ken and Barbie. The success of these and similar NFT experiments will create new value streams for fashion brands and retailers, as they’ll be able to extend offerings into the metaverse. In particular, brands could leverage NFTs to provide exclusive access to deals or pre-sale events, which helps to increase brand loyalty in the metaverse and the physical world.
Nike has already experienced success by creating products solely for the metaverse. The shoe company developed and sold NFT sneakers, known as CryptoKicks, exclusively for sale on a metaverse platform. Some of the collection’s sneakers fetched over $100,000 on OpenSean, an online marketplace, CBS News reported. According to Ferris, Nike’s experiment demonstrates that brands can leverage NFTs to build and enhance brand loyalty in distinct digital communities.
These nascent uses of NFT by leading apparel brands underscore the potential for blockchain technologies to revolutionize branded resale. As Ferris reasoned, that is because NFTs, which run on blockchain technology, are akin to a CARFAX. Thus, when embedded into products, NFTs can enhance trust in a brand’s recommerce channel as customers will be able to authenticate an item’s origin and ownership history. These NFTs essentially form a new kind of digital receipt, which may prove especially enticing to retailers selling luxury brands that are eager to show that they are offering authentic products.
Customer Demand & Adoption
While these new technologies will enhance the branded recommerce ecosystem over the long term, customers may need time to adjust to some of the changes brought about by these innovations, especially in regard to embedding NFTs into apparel.
With broader adoption of blockchain and NFT technology by brands and retailers, customers are likely to grow more accustomed to demanding detailed digital ownership records and will come to expect them within the next five years.
In fact, despite its growing dominance today, the early e-commerce experience may provide lessons for retailers about what to expect regarding NFTs and other emerging technologies. Initial skepticism about the value of e-commerce eventually dissipated as more customers grew accustomed to transacting online and via mobile apps.
We believe that we are about to arrive at an adoption tipping point for these technologies, especially as retailers and customers alike increasingly find value in them.
On the retailer side, our brand partners will come to rely on blockchain and NFT technologies to verify items upon trade-in rather than cumbersome manual inspections to guarantee authenticity.
We also expect retailers to garner savings through computer vision and dynamic pricing, as these technologies will streamline the inspection and inventory processes. Not only will retailers find these technologies useful, but customers will also enjoy the added convenience provided by computer vision’s ability to offer better sizing information and the ability to sell pre-worn items at a high level if demand is sufficiently high.
Perhaps most importantly, all the technologies enable a wider swath of stakeholders to embrace a circular economy ethos and support other societal values customers increasingly demand.
Technology is the Future of Resale
We believe these leading-edge technologies, with their ability to create value and streamline operations, will drive the widespread adoption of branded resale, especially in the luxury, sneaker, and rare-item categories. Trove, already a leader in scaling resale, is excited to continue investing in and offering these technologies to create an unparalleled Recommerce Operating System for brands looking to create their own resale space.
Curious about opening your own branded resale marketplace? Speak to a Trove representative today to book your free demo.