The digital equivalent of rummaging through clothing racks may soon become a relic as ThredUp rolls out artificial intelligence to transform the happily chaotic world of thrifting into a precision-targeted retail experience.
The technology promises to match millions of unique items with potential buyers by analyzing photos and descriptions, highlighting a growing tension between the efficiency-focused world of eCommerce and the treasure-hunt ethos that has long defined thrift shopping.
“I believe that AI will help match consumers with the items they are looking for and, because of this, can help small business owners compete in an increasingly competitive resale marketplace,” Aaliyah Kissick, owner of thrift shop AK Boutique, told PYMNTS. “At the same time, AI can facilitate a form of novelty online by learning consumer behavior and giving intermittent reinforcement, much in the same way social media algorithms do.”
AI could reshape a booming market for old stuff. Ninety-three percent of Americans now hunt for secondhand treasures online, helping drive the U.S. secondhand market to $53 billion in revenue in 2023, according to research from CapitalOne. While saving money is the top motivator for thrift shoppers at 85%, consumers also score environmental wins. Each secondhand clothing purchase saves 8.41 pounds of carbon emissions compared to buying new.
ThredUp is an online marketplace dedicated to secondhand clothing. Users can buy and sell gently used apparel from various brands. Positioned within the rising resale market, it serves as a digital consignment shop, catering to consumers interested in affordable, pre-owned fashion.
On ThredUp’s website, vintage sneakers from every era are jumbled together in this digital rummage sale, from $14 Reeboks to surprisingly pristine $365 Golden Goose kicks. The chaotic mix mirrors an old-school thrift store shelf, where pristine Nikes share space with scuffed Pumas and forgotten Tretorns, although the website’s sorting features somewhat tame the randomness.
ThredUp’s integration of AI tools reflects a practical shift in the secondhand retail market. The platform aims to improve users’ navigation of a massive inventory. Its new AI-powered search allows users to upload photos of items they want, with the system scanning the database to locate similar pieces.
This feature seeks to reduce search time for shoppers overwhelmed by the site’s millions of listings. ThredUp’s chatbot, trained to understand natural language queries, enables users to ask specific questions or describe items they’re looking for, which can be particularly useful given the variability in secondhand goods. Unlike traditional resale site search functions, these tools allow for a more guided shopping experience, addressing a common pain point of browsing hundreds of unrelated listings.
AI-driven tools in secondhand shopping make it easier to find specific items, but they also create a split between tech-savvy shoppers and those who love the traditional hunt, Arunkumar Thirunagalingam, senior manager of data and technical operations at McKesson Corporation told PYMNTS. For many customers, the charm of thrifting lies in discovering unexpected finds through slow, unhurried browsing.
“But with AI streamlining the search, the experience can start to feel more like standard retail, losing that unique sense of serendipity,” he said. “Shoppers who are comfortable with AI can quickly and easily get exactly what they’re looking for, while those who cherish the randomness and magic of thrifting might feel left out. Over time, this shift could change the whole customer base for secondhand stores, appealing more to those who prioritize efficiency and leaving behind those who come for the thrill of discovery.”
Online thrifters also face the concern of AI introducing subtle biases that affect selection, Thirunagalingam said. Most algorithms promote what’s popular or are based on users’ previous searches, which could repeatedly highlight the same mainstream brands and styles.
“This emphasis risks crowding out the lesser-known, quirky pieces that often make thrifting feel so special,” he said. “Sellers, noticing which items the algorithm prefers, might start curating inventory to match this trend, making the selection feel less diverse and potentially limiting the creativity that’s usually part of secondhand shopping.”
Perhaps the biggest question, however, is whether AI’s efficiency takes away the joy and spontaneity that make thrifting a unique experience. For many shoppers, thrifting isn’t about finding the “right” item on the first try; it’s about the surprise, the journey and stumbling across treasures you didn’t even know you wanted, Thirunagalingam said.
“With AI serving up what you’re looking for right away, this sense of adventure can easily disappear, leaving a more predictable and less personal experience,” he said. “AI can be a powerful tool, but balancing convenience with the distinct, joyful messiness of thrifting will be key to keeping the spirit of secondhand shopping alive.”
Gary Firth, managing director of U.K. screen printing company Screen Textiles, told PYMNTS that he can still remember when he unexpectedly found vintage football shirts or Carhartt pieces while rummaging around thrift stores.
“The feeling of such a find is tough to beat with an online platform to begin with, let alone then introducing an aspect of AI automation into the mix,” he said.
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