Poshmark Listings Scraper

Pull structured product data from Poshmark — the largest social-commerce resale platform in the US — for pricing intelligence, fashion trend analysis, and inventory sourcing. No Poshmark account required.

Why scraping resale data matters (and why it's hard)

Resale fashion is a ~$200B market and Poshmark sits at the center of it. The price a Lululemon legging or a pair of Nike Dunks is actually selling for this week is buried inside Poshmark's search results — not in any dataset you can download.

Doing this yourself is more work than it sounds:

• Poshmark's mobile-first frontend is heavily JavaScript-rendered.
• Listings paginate through infinite scroll.
• Anti-automation defenses make naive HTTP scraping brittle.
• Brand, size, and condition fields aren't always in predictable HTML positions.
• A tiny site change quietly breaks any in-house scraper for weeks before you notice.

This actor takes care of all of it — you give it a search query, you get clean JSON back.

Features

• Search any keyword — Nike sneakers, Lululemon leggings, vintage Levi's.
• Filter by department — Women, Men, Kids, Home.
• Rich product fields — brand, size, condition, original price, current price, likes, photos.
• Seller info — for sourcing or competitive analysis.
• Pay-per-result pricing — only pay for listings actually returned.

Input

{
  "query": "Nike sneakers",
  "department": "Men",
  "maxResults": 20
}

Field	Type	Description
query	string	Search keywords (e.g. Nike sneakers, Lululemon leggings). Required.
department	string	Optional department: Women, Men, Kids, Home, or empty for any.
maxResults	integer	Max listings to return (1–100). Free Apify plans are capped at 5.

Output

Each item in the dataset:

{
  "title": "Nike Air Max 90 - Size 10",
  "brand": "Nike",
  "size": "10",
  "price": 65.00,
  "originalPrice": 130.00,
  "condition": "Like New",
  "seller": "@sneakerseller",
  "likes": 14,
  "description": "Worn twice, no flaws...",
  "imageUrl": "https://di2ponv0v5otw.cloudfront.net/...",
  "itemUrl": "https://poshmark.com/listing/..."
}

Use cases

• Resale pricing intelligence — know what items actually clear at, not just MSRP.
• Sourcing for resellers — find underpriced inventory in real time.
• Fashion trend analysis — track which brands and styles are gaining traction.
• Brand monitoring — see how your products move on the secondary market.
• Competitive analysis — benchmark seller activity and pricing.

Get started

1. Click Run with the default input — Nike sneakers, 20 results.
2. Swap query and department for your own niche.
3. Export to CSV/JSON or call from code via the Apify API.
4. Schedule daily runs to track price movement over time.

Data is collected from publicly viewable Poshmark listing pages. Use responsibly and respect Poshmark's terms when building products on top of this data.