London, March 12: The resale fashion market is evolving rapidly, moving beyond traditional thrift shopping into a booming industry. Platforms like eBay have seen a 400 per cent surge in searches for “pre-loved fashion” since mid-2024, with 71 per cent of Gen Z embracing resale culture.
Despite its growth, resale platforms struggle with hidden costs that hinder profitability.
While Vinted has turned a profit, companies like ThredUp and The RealReal face challenges balancing sustainability with financial success.
A key issue is the labor-intensive process of merchandising second-hand clothing.
Each unique item requires quality checks, photography, and detailed listings—costly and inefficient without automation.
Reverse SKU logistics also add complexity, making large-scale resale operations difficult to manage.
Shoppers, too, encounter frustrations.
While some enjoy the hunt for vintage pieces, many find the process overwhelming due to disorganised listings. Resale platforms must streamline searches without removing the excitement of discovery.
Messina Hembry, a pre-loved fashion reseller, is addressing these challenges through AI.
The company, founded by two brothers in university, uploads over 7,000 new pieces weekly.
To enhance efficiency, it partnered with Aistetic, a University of Oxford spinout specializing in AI-driven fashion technology.
Aistetic’s computer vision solution automates tagging, labeling, and item descriptions from images. This eliminates manual cataloging, significantly reducing costs and time.
“Using Aistetic’s AI Listing solution has revolutionized our workflow,” said Zac Hembry, CEO of Messina Hembry.
The company has increased listing capacity threefold, reduced workflow time by 70 per cent, and improved conversions.
Duncan McKay, CEO of Aistetic, emphasized AI’s potential to help resale platforms scale profitably while driving sustainability.
“Through this partnership with Messina Hembry, we’re helping them unlock more capacity, enhance the shopping experience, and contribute to the circular economy.”
This collaboration demonstrates how AI is reshaping resale fashion, making operations more efficient and enhancing the customer experience.
By automating listings and improving accuracy, AI enables resale platforms to grow profitably while minimising shopper frustration.
As the resale market expands, AI integration will be crucial in ensuring its sustainability and scalability. AI-powered solutions are not only improving backend operations but also creating a smarter, more personalized shopping experience.
With technology driving the resale revolution, the industry is poised for significant transformation, redefining how people shop, sell, and engage with fashion.
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