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How Depop’s AI image-recognition tool speeds up selling for 180,000 daily listings

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How Depop’s AI image-recognition tool speeds up selling for 180,000 daily listings

  • Depop’s new gen-AI feature creates item descriptions based on photos that users upload.
  • The tool has boosted the number of listings on the company’s website and saves sellers time.
  • This article is part of “CXO AI Playbook” — straight talk from business leaders on how they’re testing and using AI.

Depop is an online fashion marketplace where users can buy and sell secondhand clothing, accessories, and other products. Founded in 2011, the company is headquartered in London and has 35 million registered users. It was acquired by Etsy, an online marketplace, in 2021.

Situation analysis: What problem was the company trying to solve?

Depop’s business model encourages consumers to “participate in the circular economy rather than buying new,” Rafe Colburn, its chief product and technology officer, told Business Insider. However, listing items to sell on the website and finding products to buy take time and effort, which he said can be a barrier to using Depop.

“By reducing that effort, we can make resale more accessible to busy people,” he said.

To improve user experience, Depop has unveiled several features powered by artificial intelligence and machine learning, including pricing guidance to help sellers list items more quickly and personalized algorithms to help buyers identify trends and receive product recommendations.

In September, Depop launched a description-generation feature using image recognition and generative AI. The tool automatically creates a description for an item once sellers upload a product image to the platform.

“What we’ve tried to do is make it so that once people have photographed and uploaded their items, very little effort is required to complete their listing,” Colburn said. He added that the AI description generator is especially useful for new sellers who aren’t as familiar with listing on Depop.


Headshot of Rafe Colburn

Rafe Colburn is the chief product and technology officer of Depop.

Courtesy of Depop



Key staff and stakeholders

The AI description-generation feature was developed in-house by Depop’s data science team, which trained large language models to create it. The team worked closely with product managers.

Colburn said that in 2022, the company moved its data science team from the engineering group to the product side of the business, which has enabled Depop to release features more quickly.

AI in action

To use the description generator, sellers upload an image of the item they want to list to the Depop platform and click a “generate description” button. Using image recognition and gen AI, the system generates a product description and populates item-attribute fields on the listing page, including category, subcategory, color, and brand.

The technology incorporates relevant hashtags and colloquial language to appeal to buyers, Colburn said. “We’ve done a lot of prompt engineering and fine-tuning to make sure that the tone and style of the descriptions that are generated really fit the norms of Depop,” he added.

Sellers can use the generated description as is or adjust it. Even if they modify descriptions, sellers still save time compared to starting with “an empty box to work with,” Colburn said.

Did it work, and how did leaders know?

Depop has about 180,000 new listings every day. Since rolling out the AI-powered description generation in September, the company has seen “a real uplift in listings created, listing time, and completeness of listings,” Colburn said. However, as the tool was launched recently, a company spokesperson said that specific data was not yet available.

“Aside from the direct user benefits in terms of efficiency and listing quality, we have also really demonstrated to ourselves that users value features that use generative AI to reduce effort on their end,” Colburn said.

Ultimately, Depop wants sellers to list more items, and the company’s goal is to make it easier to do so, he added. Automating the process with AI means sellers can list items quicker, which Colburn said would create a more robust inventory on the platform, lead to more sales, and boost the secondhand market.

What’s next?

Colburn said Depop continues to look for ways to apply AI to address users’ needs.

For example, taking high-quality photos of items is another challenge for sellers. It’s labor-intensive but important, as listings with multiple high-quality photos of garments are more likely to sell. He said Depop was exploring ways to make this easier and enhance image quality with AI.

A challenge for buyers is sometimes finding items that fit. Depop is also looking into how AI can help shoppers feel more confident that the clothing they purchase will fit so that their overall satisfaction with the platform will be enhanced, Colburn said.

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