Poshmark Sold Listings Scraper

Pull real sold-comp data from Poshmark at scale — final sold prices, exact sold dates, and days-to-sell that Poshmark never shows you, plus brand, size, condition, colors, and seller handle on every row. Search many keywords in one run and get one clean row per listing, ready for a spreadsheet or your pricing model. Built for resellers, sourcing pros, and brand analysts who need accurate Poshmark sold comps without manually scrolling through closed listings one page at a time.

Why This Scraper?

• Real sold comps Poshmark hides — every sold row carries the final sold price, the exact sold date, and a computed days-to-sell, the three numbers Poshmark removes from its public UI the moment an item sells.
• Sold or active in one toggle — flip listingStatus between sold comps (what items actually fetched) and live listings (what the current market is asking), instead of being locked to sold-only.
• Multi-keyword batch search — feed a whole product list into searchQueries and run every search in a single job; no one-keyword-per-run limit.
• 7 departments — scope to Women, Men, Kids, Home, Pets, Electronics, or leave on All departments.
• 4 sort modes — order by Most recently sold, Price: low to high, Price: high to low, or Most liked before results are collected.
• Brand-family filtering — pass a single brand name (e.g. Nike, Coach) to scope results to that brand and its sub-labels, so "Nike" also pulls in Nike Air Jordan listings.
• New-With-Tags-only filter — narrow to brand-new, tagged inventory for deadstock and retail-arbitrage research.
• Price-band filtering in USD — set a minPrice, a maxPrice, or both to focus on a single price tier.
• Full listing detail on every row, no extra step — each result already carries the complete seller description, every listed color, style tags, Poshmark category, and the like, comment, and share counts, plus original retail price for sell-through math — no second lookup needed.

Use Cases

Reseller Pricing & Sourcing

• Build a fresh sold-comp set for any item before you list, so you price to what actually sells.
• Measure days-to-sell across brands and price bands to find the fastest-moving inventory.
• Spot underpriced active listings to flip by comparing live asks against recent sold prices.

Brand & Market Research

• Track real resale values for a single brand across departments over time.
• Compare New-With-Tags sell-through against used-condition listings for the same product.
• Benchmark a brand's secondary-market pricing against its retail price using the original-price field.

Inventory Valuation

• Value a closet or consignment lot by pulling sold comps for each item and summing realistic exit prices.
• Audit which size and color combinations command a premium within a brand.

Trend Analysis

• Watch which styles, colors, and tags are selling fastest in a category.
• Quantify demand by sorting on Most liked and cross-referencing likes against sold dates.

Getting Started

Simple — one keyword, sold comps

{
  "searchQueries": ["Lululemon leggings"]
}

Filtered — one brand, New With Tags, price band

{
  "searchQueries": ["Coach handbag"],
  "listingStatus": "sold",
  "brand": "Coach",
  "condition": "nwt",
  "minPrice": 50,
  "maxPrice": 300,
  "sortBy": "sold_recently",
  "maxResults": 500
}

Advanced — multi-keyword batch, full filters

{
  "searchQueries": ["Nike Air Jordan 1", "Adidas Samba", "New Balance 990"],
  "listingStatus": "sold",
  "department": "men",
  "condition": "all",
  "minPrice": 80,
  "maxPrice": 600,
  "sortBy": "price_desc",
  "maxResults": 2000
}

Input Reference

What to Search

Parameter	Type	Default	Description
searchQueries	array of strings	["Lululemon leggings"]	Keywords, brands, or phrases to look for. Add several entries to run multiple searches in one job.
listingStatus	string (select)	sold	sold for items that already sold (sold comps) or available for items still for sale.

Filters

Parameter	Type	Default	Description
department	string (select)	all	One of All departments, Women, Men, Kids, Home, Pets, Electronics.
brand	string	(empty)	Return only items from this brand and its sub-labels (e.g. "Nike" also returns Nike Air Jordan). Leave empty to include every brand.
condition	string (select)	all	all for any condition or nwt for New With Tags only.
minPrice	integer	(none)	Only return items at or above this price in USD.
maxPrice	integer	(none)	Only return items at or below this price in USD.
sortBy	string (select)	sold_recently	Most recently sold / added, Price: low to high, Price: high to low, or Most liked.

Options

Parameter	Type	Default	Description
maxResults	integer	100	Maximum listings to collect across all searches. Set to 0 for no limit.

Output

Each listing is one flat row. Example sold-comp result:

{
  "listingId": "65f1a2b3c4d5e6f7a8b9c0d1",
  "title": "Lululemon Align High-Rise Leggings 25\" Black Size 6",
  "brand": "lululemon athletica",
  "size": "6",
  "department": "Women",
  "category": "Pants & Jumpsuits",
  "colors": ["Black"],
  "description": "Excellent used condition, no pilling. Inseam 25\".",
  "condition": "not_nwt",
  "nwt": false,
  "soldPrice": 58.0,
  "originalPrice": 98.0,
  "status": "sold",
  "soldAt": "2026-05-28T14:21:09Z",
  "listedAt": "2026-05-10T09:03:44Z",
  "daysToSell": 18,
  "styleTags": ["align", "leggings"],
  "likesCount": 42,
  "commentsCount": 3,
  "shareCount": 7,
  "sellerUsername": "closetdeals22",
  "sellerName": "Jamie R.",
  "thumbnailUrl": "https://di2ponv0v5otw.cloudfront.net/posts/.../thumbnail.jpg",
  "imageUrls": [
    "https://di2ponv0v5otw.cloudfront.net/posts/.../thumbnail.jpg",
    "https://di2ponv0v5otw.cloudfront.net/posts/.../large.jpg"
  ],
  "url": "https://poshmark.com/listing/65f1a2b3c4d5e6f7a8b9c0d1",
  "scrapedAt": "2026-06-02T17:45:00Z"
}

Core Fields

Field	Type	Description
listingId	string	Poshmark listing identifier.
title	string	Listing title.
brand	string	Brand name as listed.
size	string	Item size with its size system.
department	string	Department the item is listed in.
category	string	Poshmark category for the item.
colors	array of strings	Colors listed on the item.
description	string	Full listing description.
condition	string	Raw condition token (e.g. nwt, not_nwt, ret).
nwt	boolean	Whether the item is New With Tags.
styleTags	array of strings	Style tags applied by the seller.
url	string	Full listing URL.
scrapedAt	string (ISO 8601)	When the row was collected.

Pricing & Status

Field	Type	Description
soldPrice	number	Final sold price for sold items, or current price for active listings.
originalPrice	number	Original retail price, or null when the seller did not enter one.
status	string	sold or available.

Dates & Velocity

Field	Type	Description
soldAt	string (ISO 8601)	Date the item sold (sold listings only).
listedAt	string (ISO 8601)	Date the item was first listed.
daysToSell	integer	Days between listed and sold.

Seller & Engagement

Field	Type	Description
sellerUsername	string	Seller handle.
sellerName	string	Seller display name.
likesCount	integer	Number of likes on the listing.
commentsCount	integer	Number of comments.
shareCount	integer	Number of shares.

Media

Field	Type	Description
thumbnailUrl	string	Cover image URL.
imageUrls	array of strings	Cover image in thumbnail and large sizes.

Tips for Best Results

• For pricing research, combine listingStatus: sold with sortBy: sold_recently to build the freshest possible comp set — recent sales reflect current demand far better than old ones.
• Sold results top out at 5,000 per keyword. To dig deeper into a popular product, split the keyword by a brand or a tight minPrice/maxPrice band and run several focused searches instead of one broad one.
• Every row already carries the full description, colors, style tags, category, and like/comment/share counts — no extra step or setting is needed to get the complete listing detail.
• Compare originalPrice against soldPrice to measure how much of retail value a brand holds on the secondary market.
• Sort on daysToSell after a run to find which styles, sizes, and colors sell fastest, then prioritize sourcing those.
• Start with a maxResults of 50–100 to preview the shape of the data, then raise it once you are happy with your filters.
• Set listingStatus: available to size up the live market — how many comparable items are currently listed and at what asking prices — before deciding what to buy.

Pricing

From $2.00 per 1,000 results — flat per-result pricing, undercutting comparable Poshmark tools. No compute or time-based charges — you pay per result, plus a small fixed per-run start fee. Bronze, Silver, and Gold subscribers pay progressively less; the table below shows total cost at each discount tier.

Results	No discount	Bronze	Silver	Gold
100	$0.24	$0.23	$0.21	$0.20
1,000	$2.40	$2.25	$2.10	$2.00
10,000	$24.00	$22.50	$21.00	$20.00
100,000	$240.00	$225.00	$210.00	$200.00

A "result" is one listing row in your dataset. Apify platform usage fees are billed separately.

Integrations

Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps via:

• Zapier / Make / n8n — Workflow automation
• Google Sheets — Direct spreadsheet export
• Slack / Email — Notifications on new results
• Webhooks — Trigger custom APIs on run completion
• Apify API — Full programmatic access

Legal & Ethical Use

This scraper collects publicly available listing data for legitimate research, pricing, and analytics purposes. You are responsible for using the collected data in compliance with Poshmark's terms of service, applicable laws, and any relevant data-protection regulations. Do not use the data to harass sellers, infringe intellectual property, or process personal data unlawfully. Always review the target site's terms before running large jobs.