How to Scrape Etsy in 2026: Product Listings, Seller Data, and Prices

Etsy is one of the largest marketplaces for handmade, vintage, and craft goods — with over 90 million active buyers and 7+ million sellers. For market researchers, dropshippers, and e-commerce analysts, Etsy data is incredibly valuable: product trends, pricing strategies, seller performance, and buyer sentiment are all embedded in those listing pages. In this guide, I'll walk through scraping Etsy product listings, seller profiles, and reviews using Python. I'll cover the technical challenges (spoiler: JavaScript rendering is the big one) and show practical code you can adapt. What Data Can You Extract from Etsy? Here's what's publicly available on Etsy pages: Product listings — title, description, price, images, tags, materials, shipping info Seller profiles — shop name, location, sales count, star rating, member since Reviews — star rating, review text, buyer photos, date, item purchased Search results — products ranked by relevance/price/recency for any keyword Category data — trend