Etsy’s Head of Global Merchandising on AI-Driven Curation

Etsy's merchandising team uses AI to scale human-curated collections across 120 million listings, creating 'algatorial collections' where merchandisers seed aesthetic concepts and AI matches them to relevant buyers. The platform restructured its merchandising team into three arms: vertical categories, horizontal themes, and 100% human curation programs.
This hybrid human-AI curation model could influence how Amazon and Walmart develop their own product discovery algorithms, potentially favoring sellers who optimize for both algorithmic signals and cultural relevance. Sellers should monitor if major platforms start emphasizing 'taste' and cultural moments in their ranking factors beyond traditional performance metrics.
This represents the evolution of marketplace algorithms from pure performance optimization toward cultural and aesthetic relevance, potentially changing how products get discovered across all major platforms.
Track cultural trends and seasonal moments in your niche -- platforms may increasingly weight cultural relevance in discovery algorithms alongside performance metrics.
Monitor your product discovery performance across different buyer intent levels (targeted search vs. browsing) as platforms may adjust algorithms based on shopper behavior.
Bottom Line
Etsy's human-AI merchandising blend signals broader platform shift toward cultural curation.
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Useful background context, but lower-priority than direct platform, community, or operator intelligence.
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Etsy's human-AI merchandising blend signals broader platform shift toward cultural curation.
Key Stat / Trigger
120 million listings
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Full Coverage
With more than 120 million listings and millions of active sellers, Etsy faces one of the most complex curation challenges in retail. Surfacing the right products to the right shoppers at that scale requires more than algorithms alone.
Mary Andrews, Head of Global Merchandising at Etsy Mary Andrews, Head of Global Merchandising at Etsy, sat down with Nicole Silberstein, Editor in Chief of Retail TouchPoints, on the Retail Remix podcast to discuss how her team balances human instinct with AI-driven discovery to build a shopping experience that feels both personalized and culturally relevant.
Merchandising a Marketplace at Scale Andrews describes her team’s core function as translating cultural moments and buyer demand into the categories and stories Etsy surfaces across its “front doors” — the homepage, app, email, and marketing channels. The process starts with human observation: “We start with taste, cultural instinct,” Andrews said.
Her team monitors music, film releases, emerging style trends and broader cultural shifts, then layers in behavioral data, such as searches and shifts in demand to identify where interest is building.
From there, those insights feed into algorithmic training signals: “AI scales the insight; and our merchandisers ensure it’s accurately capturing their intent and that it’s resonating,” she said. “It’s really this constant feedback loop.”
‘AI Doesn’t Replace Uniqueness,’ and it can Fuel it Etsy has built its identity around non-commodity, one-of-a-kind products. The concern that algorithms push toward sameness is a real one, but Andrews argues that Etsy’s approach works in the opposite direction. “Algorithms can promote sameness if they’re optimized for popularity alone,” she said.
“But at Etsy, AI doesn’t replace uniqueness. I think it helps surface truly personalized niche merchandising.” Rather than programming for a single audience, Andrews said Etsy can now connect specific collections to the buyers most likely to appreciate them.
Intent matters too: when a shopper has a clear goal, AI narrows quickly toward precision, but when they’re browsing, Etsy intentionally widens the aperture to encourage discovery. To illustrate, Andrews offered an example: In the past, the team might have run one single “spring dresses” feature that every visitor would see.
Now, the team seeds hundreds of spring fashion collections, each maintaining the merchandiser’s intent but scaled and personalized for a wider range of tastes, styles and occasions. ‘Algatorial’ Collections and the Human-AI Blend One of the clearest examples of the combination of human and AI is what Etsy calls “algatorial collections.”
A merchandiser seeds a collection with a specific aesthetic or point of view, and AI scales it to thousands of relevant listings while preserving the original intent.
“This has allowed us to focus on seeding a much greater variety of content across more interests and niches, while AI is taking care of matching the content to the right buyer,” Andrews explained.
Etsy also uses guided groups — combinations of keywords used to build collections around themes that rely less on visual cues, such as “seashell bridal jewelry” or “gold theme gifts for a 50th anniversary.” These collections are presented as interest modules on the homepage and expand as shoppers provide more behavioral signals.
In the past year, Etsy has restructured its merchandising team to support this model. The team now operates across three arms: vertical categories such as home and living; horizontal categories including gifts, weddings and fandoms; and a merchandising programs arm focused on 100% human curation.
That last arm covers initiatives like new arrivals, “ones to watch” sellers and co-created drops with sellers and influencers. The restructuring also introduced new roles.
Merchandisers now help train and review AI models through what Etsy calls Human Quality Review (HQE) and Visual Quality Review (VQE) — teaching systems to understand quality attributes and relevance. Andrews noted that this work has improved search accuracy around attributes like material, color, dimension and size.
AI Answer Engines and New Discovery Channels Etsy has also been an early mover in integrating with AI answer engines — including ChatGPT, Google Gemini and Microsoft Copilot — to trial selling directly on those platforms. Andrews sees these channels as an opportunity to reach shoppers who might not have thought of Etsy as a starting point.
“I’m also energized by how well these systems interpret intent, not just keywords,” she said. “When someone describes a feeling or an occasion or a vibe, I think Etsy’s positioned really well to surface something special.”
She noted that Etsy sellers are often among the first to bring emerging trends to market, and that AI answer engines may give those products immediate visibility for shoppers who don’t yet have the words to describe what they’re looking for: “You can describe what you’re looking for witho
Original Source
This briefing is based on reporting from Retail TouchPoints. Use the original post for full primary-source context.
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