Merchandising a Marketplace: The Magician Behind Etsy’s Curatorial Magic
Retail Remix
· with Mary Andrews
· March 30, 2026
· 23 min
Summary
Etsy’s Head of Global Merchandising, Mary Andrews, reveals how the marketplace masterfully blends AI and human curation to create a personalized and culturally relevant shopping experience for its millions of users. This episode is a must-listen for ecommerce operators looking to understand how to leverage AI to identify trends, scale insights, and amplify niche interests while redefining the critical role of human merchandisers in an AI-driven retail landscape.
Key takeaways
AI will not replace human merchandisers but elevate their role to focus on higher-level strategic work like shaping taste and influencing culture.
Etsy uses a combination of AI and human curation to translate cultural trends and buyer signals into an ever-changing slate of collections and experiences.
AI answer engines like ChatGPT and Gemini can expand product discovery by helping buyers find niche products they might not have otherwise discovered.
AI personalization can amplify niche interests and diverse tastes, countering the homogenization often associated with online experiences.
Learning from niche communities, like Depop’s merchandisers specializing in Gen Z trends, is crucial for understanding specific demographics and their unique preferences.
Themes
ai & machine learningconsumer trendsmarketplace strategymerchandising & curation
With more than 120 million listings and millions of active sellers, Etsy operates one of the most unique marketplaces in retail. But surfacing the right products for the right buyers requires more than algorithms alone.In this episode of Retail Remix, host Nicole Silberstein speaks with Mary Andrews, Head of Global Merchandising at Etsy, about how the company balances human insight and instinct with AI-driven discovery to curate a shopping experience that feels both personalized and culturally relevant.Mary shares how her team identifies emerging trends, translates cultural moments into shopping occasions and uses AI to scale those insights across Etsy’s massive inventory. Key TakeawaysHow Etsy uses a combination of AI and human curation to translate cultural trends and buyer signals into an ever-changing slate of collections and experiences; Why AI will actually make human merchandisers even more valuable; Insight from Etsy’s early experiments using AI answer engines like ChatGPT and Gemini to expand product discovery; Lessons learned from working alongside Depop’s team of merchandisers, who have their finger on the pulse of Gen Z; How AI personalization is helping to amplify niche interests rather than homogenize the internet; and Why the future merchandiser will spend less time programming products and more time shaping taste and culture. Related LinksExplore Etsy and discover one-of-a-kind products from independent sellersRelated reading: Etsy, Shopify Among Early Partners for Microsoft’s Copilot CheckoutRelated reading: <a href="https://www.retailtouchpoints.com/topi
What does this episode say about ai & machine learning?
AI will not replace human merchandisers but elevate their role to focus on higher-level strategic work like shaping taste and influencing culture.
What does this episode say about consumer trends?
Etsy uses a combination of AI and human curation to translate cultural trends and buyer signals into an ever-changing slate of collections and experiences.
What does this episode say about marketplace strategy?
AI answer engines like ChatGPT and Gemini can expand product discovery by helping buyers find niche products they might not have otherwise discovered.
What does this episode say about merchandising & curation?
AI personalization can amplify niche interests and diverse tastes, countering the homogenization often associated with online experiences.
What does this episode say about ai & machine learning?
Learning from niche communities, like Depop’s merchandisers specializing in Gen Z trends, is crucial for understanding specific demographics and their unique preferences.
