Poshmark Scraper - Fashion & Resale Marketplace

Scrape Poshmark marketplace listings for fashion, clothing, shoes, and accessories at scale. Extract prices, brands, sizes, conditions, seller info, and engagement metrics -- perfect for resellers, fashion researchers, and price monitoring.

Features

• Search by keyword with optional filters (brand, department, price range)
• Extract listing data directly from Poshmark's server-rendered state (fast, no browser needed)
• Optional detail page scraping for full descriptions, seller stats, photos, and style tags
• Automatic pagination to collect up to 5,000 results per query
• Sort by relevance, price, newest, or just shared
• Graceful abort handling for cost control

What data can you get?

Search mode (fast, default)

• Listing ID, title, and description
• Price and original retail price
• Brand, size, and condition (New With Tags, New Without Tags, Good)
• Category, department, and subcategory
• Colors
• Cover image URL
• Seller username and display name
• Like, comment, and share counts
• Inventory status (available/sold)
• Creation and update dates
• Direct listing URL

Detail mode (scrapeDetails: true) -- additional fields

All of the above, plus:

• All photos (URLs at multiple resolutions)
• Size inventory breakdown (quantity available/sold per size)
• Style tags
• Seller city and state
• Seller follower/following counts
• Seller total listings
• Seller orders shipped and average ship time
• Seller join date and profile URL

How to use

1. Enter one or more search queries (e.g., "Nike Air Max", "Lululemon leggings", "Coach bag")
2. Optionally filter by department, brand, or price range
3. Choose a sort order if needed
4. Toggle Scrape Full Details for complete listing data (slower but richer)
5. Run the scraper and download results as JSON, CSV, or Excel

Example output

{
    "listingId": "66c236d79ceaf7c22ae066dc",
    "title": "NWT Nike Blazer Shoes",
    "price": 70,
    "originalPrice": 100,
    "currency": "USD",
    "brand": "Nike",
    "size": "10",
    "condition": "New With Tags",
    "category": "Shoes",
    "department": "Women",
    "subcategory": "Sneakers",
    "colors": ["White", "Black"],
    "description": "Brand New & Never Worn\nWomen's Nike Blazer Shoes\nSize:10\nColor: Black & White",
    "imageUrl": "https://di2ponv0v5otw.cloudfront.net/posts/2024/08/18/.../m_abc123.jpg",
    "sellerUsername": "fashionista99",
    "sellerDisplayName": "Jane Doe",
    "likeCount": 74,
    "commentCount": 2,
    "shareCount": 2675,
    "status": "available",
    "url": "https://poshmark.com/listing/66c236d79ceaf7c22ae066dc",
    "searchQuery": "nike shoes",
    "scrapedAt": "2026-03-17T12:00:00.000Z"
}

Input options

Parameter	Type	Default	Description
searchQueries	string[]	["nike shoes"]	Search terms to scrape (required)
category	string	--	Department filter (e.g., "Women", "Men", "Kids")
brand	string	--	Brand filter (e.g., "Nike", "Lululemon")
minPrice	integer	--	Minimum price filter ($)
maxPrice	integer	--	Maximum price filter ($)
sortBy	string	relevance	Sort: price_asc, price_desc, added_desc, just_shared
maxListings	integer	100	Max listings per query (0 = unlimited)
scrapeDetails	boolean	false	Visit each listing page for full data
proxyConfiguration	object	no proxy	Proxy settings for Apify platform

Use cases

• Resellers: Find underpriced fashion items to flip
• Price monitoring: Track used clothing prices by brand, size, and condition
• Market research: Analyze pricing trends for specific brands or categories
• Inventory sourcing: Find bulk inventory for your Poshmark, eBay, or Mercari store
• Competitor analysis: Monitor pricing strategies of other sellers
• Data analysis: Export to CSV/Excel for spreadsheet analysis

How it works

1. Search pages: The scraper fetches Poshmark search result pages and extracts listing data from the window.__INITIAL_STATE__ JavaScript object embedded in the server-rendered HTML. This contains rich structured data for all ~48 listings per page.

2. Pagination: Poshmark uses cursor-based pagination via a max_id parameter. The scraper automatically follows pagination until the requested number of listings is reached.

3. Detail pages (optional): When scrapeDetails is enabled, the scraper visits each listing's individual page to extract additional data including all photos, seller statistics, and style tags.

4. Fallback: If __INITIAL_STATE__ parsing fails, the scraper falls back to JSON-LD structured data embedded in the page.

Performance tips

• Search mode (scrapeDetails: false) is significantly faster since it extracts all data from search pages without visiting individual listings. Each search page contains ~48 listings, so 100 listings requires only 3 HTTP requests.
• Detail mode (scrapeDetails: true) makes one additional request per listing but provides photos, seller stats, and style tags.
• Use maxListings to control costs. Poshmark returns up to 5,000 results per search query.
• Use Apify Schedules to run daily for automated price tracking.
• Combine with Apify integrations (Google Sheets, Slack, Zapier) for automated workflows.

Quick start

# Install dependencies
npm install

# Run locally
apify run --purge

Deploy to Apify

apify login
apify push

Limitations

• Only scrapes publicly available listing data
• Maximum ~5,000 results per search query (Poshmark platform limit)
• Seller contact info is not available through public pages
• Seller stats (followers, ship time) only available in detail mode

Technology

• Apify SDK - Actor platform toolkit
• Crawlee - CheerioCrawler for fast HTTP-based scraping
• Cheerio - HTML parsing and traversal

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