# Poshmark Sold Listings Scraper (`solidcode/poshmark-scraper`) Actor \[💰 $2 / 1K] Extract Poshmark sold listings and active listings — final sold price, sold date, days-to-sell, brand, size, condition, and seller username. The sold-comps data Poshmark hides, with brand, department, price, and condition filters. - **URL**: https://apify.com/solidcode/poshmark-scraper.md - **Developed by:** [SolidCode](https://apify.com/solidcode) (community) - **Categories:** E-commerce, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 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 ```json { "searchQueries": ["Lululemon leggings"] } ```` #### Filtered — one brand, New With Tags, price band ```json { "searchQueries": ["Coach handbag"], "listingStatus": "sold", "brand": "Coach", "condition": "nwt", "minPrice": 50, "maxPrice": 300, "sortBy": "sold_recently", "maxResults": 500 } ``` #### Advanced — multi-keyword batch, full filters ```json { "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: ```json { "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. # Actor input Schema ## `searchQueries` (type: `array`): What to search for on Poshmark — a product, brand, or phrase. For example 'Nike Air Jordan 1', 'Lululemon leggings', or 'Coach handbag'. Add several keywords to run multiple searches in one go. ## `listingStatus` (type: `string`): Whether to collect items that have already sold (great for pricing research and sold comps) or items still available for sale. ## `department` (type: `string`): Limit results to one department, or leave on 'All departments' to search everything. ## `brand` (type: `string`): Only return items from this brand (e.g. 'Nike', 'Coach'). Matches the whole brand family, so 'Nike' also returns sub-labels like Nike Air Jordan. Leave empty to include every brand. ## `condition` (type: `string`): Limit to brand-new items still carrying their tags, or include items in any condition. ## `minPrice` (type: `integer`): Only return items at or above this price. Leave empty for no lower limit. ## `maxPrice` (type: `integer`): Only return items at or below this price. Leave empty for no upper limit. ## `sortBy` (type: `string`): How to order results before they are collected. ## `maxResults` (type: `integer`): Maximum number of listings to collect across all searches. Set to 0 for no limit. Tip: start with 50-100 to preview, then increase. ## Actor input object example ```json { "searchQueries": [ "Lululemon leggings" ], "listingStatus": "sold", "department": "all", "condition": "all", "sortBy": "sold_recently", "maxResults": 100 } ``` # Actor output Schema ## `overview` (type: `string`): Table of scraped Poshmark listings with key fields. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQueries": [ "Lululemon leggings" ], "listingStatus": "sold", "department": "all", "condition": "all", "sortBy": "sold_recently", "maxResults": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("solidcode/poshmark-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchQueries": ["Lululemon leggings"], "listingStatus": "sold", "department": "all", "condition": "all", "sortBy": "sold_recently", "maxResults": 100, } # Run the Actor and wait for it to finish run = client.actor("solidcode/poshmark-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchQueries": [ "Lululemon leggings" ], "listingStatus": "sold", "department": "all", "condition": "all", "sortBy": "sold_recently", "maxResults": 100 }' | apify call solidcode/poshmark-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solidcode/poshmark-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Poshmark Sold Listings Scraper", "description": "[💰 $2 / 1K] Extract Poshmark sold listings and active listings — final sold price, sold date, days-to-sell, brand, size, condition, and seller username. The sold-comps data Poshmark hides, with brand, department, price, and condition filters.", "version": "1.0", "x-build-id": "VHixyTRC0q8gSDbaI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solidcode~poshmark-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solidcode-poshmark-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solidcode~poshmark-scraper/runs": { "post": { "operationId": "runs-sync-solidcode-poshmark-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solidcode~poshmark-scraper/run-sync": { "post": { "operationId": "run-sync-solidcode-poshmark-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "searchQueries": { "title": "Search Keywords", "type": "array", "description": "What to search for on Poshmark — a product, brand, or phrase. For example 'Nike Air Jordan 1', 'Lululemon leggings', or 'Coach handbag'. Add several keywords to run multiple searches in one go.", "items": { "type": "string" } }, "listingStatus": { "title": "Listing Status", "enum": [ "sold", "available" ], "type": "string", "description": "Whether to collect items that have already sold (great for pricing research and sold comps) or items still available for sale.", "default": "sold" }, "department": { "title": "Department", "enum": [ "all", "women", "men", "kids", "home", "pets", "electronics" ], "type": "string", "description": "Limit results to one department, or leave on 'All departments' to search everything.", "default": "all" }, "brand": { "title": "Brand", "type": "string", "description": "Only return items from this brand (e.g. 'Nike', 'Coach'). Matches the whole brand family, so 'Nike' also returns sub-labels like Nike Air Jordan. Leave empty to include every brand." }, "condition": { "title": "Condition", "enum": [ "all", "nwt" ], "type": "string", "description": "Limit to brand-new items still carrying their tags, or include items in any condition.", "default": "all" }, "minPrice": { "title": "Minimum Price (USD)", "minimum": 0, "type": "integer", "description": "Only return items at or above this price. Leave empty for no lower limit." }, "maxPrice": { "title": "Maximum Price (USD)", "minimum": 0, "type": "integer", "description": "Only return items at or below this price. Leave empty for no upper limit." }, "sortBy": { "title": "Sort By", "enum": [ "sold_recently", "price_asc", "price_desc", "likes" ], "type": "string", "description": "How to order results before they are collected.", "default": "sold_recently" }, "maxResults": { "title": "Max Results", "minimum": 0, "type": "integer", "description": "Maximum number of listings to collect across all searches. Set to 0 for no limit. Tip: start with 50-100 to preview, then increase.", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```