Etsy, the eCommerce retailer known for handmade and vintage goods, is doubling down on a hybrid approach to artificial intelligence that keeps humans in the loop and ensures shoppers find what they want.
“As a marketplace of over 130 million creative items that are made, designed and handpicked by individual sellers, surfacing the right item to the right buyer at the right time is a unique challenge,” Etsy Chief Product Officer Nick Daniel told PYMNTS in an interview.
The company is pursuing a strategy it calls “algotorial curation,” which blends recommendations by Etsy’s staff with advanced machine learning algorithms to scale curation across its inventory, he said.
The process starts with human experts identifying trends and selecting listings that are examples of these trends.
“After a collection is identified, our engineers use machine learning to expand it from roughly 50 human-curated listings to about 1,000,” Daniel said. “Finally, we use [large language models (LLMs)] to make sure the full collection is aesthetically cohesive, represents a variety of products and meets our standards for quality.”
The company uses Google’s Gemini multimodal model to power these experiences. Despite advances in generative AI, Etsy isn’t looking to eliminate humans from the equation. Instead, the company sees AI as a way to enhance human insight at scale, Daniel said.
“Rather than removing human expertise from our merchandising work as AI becomes more powerful, we’re leveraging these tools to amplify the expertise of our team and create a more personalized experience,” he said. “We’re putting human touch — from our buyers to our teams of employees to our sellers — at the center of shopping on Etsy.”
Consumers want AI to help them shop, whether there is a human in the loop or not. The PYMNTS Intelligence report “Getting to Know You: How AI Is Shaping the Future of Shopping” found that 51% of consumers want at least one kind of AI-assisted shopping feature. Moreover, these consumers are among merchants’ highest-value customers.
Read also: Etsy CEO Advocates for Small Sellers Amid Trade Policy Concerns
AI is also well-equipped to handle Etsy’s atypical inventory structure — comprised of millions of single and custom items — which poses challenges that traditional eCommerce technology is not optimized to handle.
“Because each item on Etsy is listed individually by a real seller, the data we have isn’t uniform — we’re not like a traditional eCommerce marketplace with a catalog or SKUs,” Daniel said. “AI can help us bridge this gap.”
Etsy is also using AI beyond curation.
“We’re leveraging LLMs to extract key product details, like size and color, from listings, which improves search and helps connect the right items to the right buyers,” Daniel said.
This strategy has yielded measurable results, boosting visibility and sales.
“We used LLMs to generate alt text for listings that didn’t already have it and saw a nearly 5% increase in SEO visits and a nearly 3% increase in conversions to sales attributed to those visits,” he said.
Looking ahead, Etsy is focused on building a more personalized shopping experience based on higher consumer engagement.
“As more buyers engage with the new product experience, we’ll have stronger data to build machine learning models that can better predict a buyer’s preferences,” Daniel said. “More engagement will fuel a more curated, personalized experience and vice versa. We’re laying the groundwork to make Etsy the starting point for special.”
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