Vinted resale data API

ShopAPIS returns structured Vinted listing data — asking price, currency, brand, category, size, condition grade, seller rating, favorites count, photos and sold/active status — as normalized JSON. Vinted is Europe’s dominant C2C resale marketplace, and its listings are the richest second-hand pricing signal on the continent: what real sellers ask, and what actually sells, for used fashion across 25+ markets.

Why Vinted data is hard to get

Vinted is app-first with no official public API, and its value is in resale-specific fields. Listings are created by individuals, so the data is messy by nature — free-text titles, seller-declared condition, per-item photos — and the endpoints that serve the app are unofficial and undocumented. Anti-bot difficulty is medium-high, and because Vinted is app-first the public web view exposes only a fraction of activity, which is why standard web-traffic estimates understate it so badly. The analytical payoff is the resale-pricing signal: brand, condition grade (e.g. New with tags, Very good, Good), original-vs-asking price, size and crucially whether a comparable item has sold versus sits active. Aggregating that across many listings of the same brand and model is what turns noisy individual postings into a reliable second-hand price curve. ShopAPIS normalizes these messy fields into a structured, consistent record so you can build genuine resale price curves and track how used demand shifts over time.

Data fields returned

• Pricing — asking price, currency, original/retail price where stated, price including buyer protection.
• Condition — seller-declared condition grade (New with tags, New without tags, Very good, Good, Satisfactory).
• Status — active, reserved or sold; sold date where available.
• Catalog — title, brand, category, size, color, material.
• Seller — username, rating, number of reviews, item count, location/country.
• Engagement — favorites/likes count, views where exposed.
• Identifiers — Vinted item ID, listing URL.
• Images — seller photo URLs.

Sample response

{
  "marketplace": "vinted",
  "domain": "vinted.de",
  "country": "DE",
  "item_id": "4827193055",
  "title": "Nike Air Force 1 weiß Gr. 42",
  "brand": "Nike",
  "category": ["Damen", "Schuhe", "Sneaker"],
  "size": "42",
  "color": "Weiß",
  "condition": "Very good",
  "status": "active",
  "price": { "asking": 45.00, "currency": "EUR", "with_buyer_protection": 51.65 },
  "seller": { "username": "second_style_de", "rating": 4.9, "reviews": 418, "country": "DE" },
  "engagement": { "favorites": 27 },
  "images": ["https://images1.vinted.net/t/0123/f800/item.jpeg"],
  "url": "https://www.vinted.de/items/4827193055",
  "fetched_at": "2026-06-05T12:05:44Z"
}

Markets and domains covered

Use cases

• Resale price benchmarking — build asking-vs-sold price curves by brand, size and condition.
• Brand resale intelligence — see how a brand’s used value holds against its new price.
• Review and sentiment analytics — mine seller ratings and demand signals. See review analytics.
• Competitive intelligence — track second-hand supply and pricing for fashion categories. See competitive intelligence.

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