# Poshmark Sold Comps Scraper - Resale Prices & Pricing Stats (`webdata_labs/poshmark-sold-comps-scraper`) Actor Pull Poshmark sold comps and pricing stats so resellers know what items actually sell for. Returns sold listings plus median/average/min/max sold price, an optional active-vs-sold spread, and a suggested max buy price — exported as CSV/JSON. - **URL**: https://apify.com/webdata\_labs/poshmark-sold-comps-scraper.md - **Developed by:** [Open Web Team](https://apify.com/webdata_labs) (community) - **Categories:** E-commerce, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $2.00 / 1,000 comp rows This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Comps Scraper - Resale Prices & Pricing Stats Know what items actually **sell** for on Poshmark before you buy or relist. This Actor searches Poshmark **sold** listings for a keyword or brand, extracts each sold comp (title, sold price, original price, discount, size, image, URL), and rolls them up into reseller pricing intelligence: median / average / min / max sold price, an optional active-vs-sold spread, and a suggested max buy price - exported as CSV or JSON. It is built for **resellers and flippers**, not just "give me raw listings." Sold comps tell you the truth; active asking prices do not. ### Why Use This Actor - Get **real sold prices**, not optimistic active asking prices. - See median, average, min, and max sold price for any query in one row. - Optionally compare sold vs active to spot over- or under-priced inventory. - Get a **suggested max buy price** so you protect your margin at the source. - Export CSV-ready comps for sourcing spreadsheets, Whatnot prep, or accounting. - No login required for public sold-listing data. ### Common Use Cases - Decide what to pay at a thrift store, estate sale, or wholesale lot. - Price your own listings against what comparable items actually sold for. - Spot brands/sizes with a wide active-vs-sold spread (slow movers vs fast flips). - Build a sourcing cheat sheet of median resale values by keyword. ### Quick Preview | Input | Output | |---|---| | `nike air max women`, availability `sold` | median **$40**, range **$19-$72**, 10+ sold comps with size and discount | | add `includeActiveComparison: true` | active median, **active-vs-sold spread**, suggested max buy price | ### Input Example ```json { "query": "nike air max women", "availability": "sold", "maxItems": 50, "includeActiveComparison": true, "targetMarginPercent": 50 } ```` You can also pass a `brand` (e.g. `Nike`) or a full `startUrl`. If no input is provided, the Actor runs the sample query above so you can see the output immediately. ### Output The Actor writes one **summary** row plus one row per **listing** to the default dataset. #### Summary row ```json { "recordType": "summary", "query": "nike air max women", "availability": "sold", "soldCount": 50, "medianSoldPrice": 40, "averageSoldPrice": 41.1, "minSoldPrice": 19, "maxSoldPrice": 72, "activeCount": 50, "activeMedianPrice": 65, "activeVsSoldSpread": 25, "targetMarginPercent": 50, "suggestedMaxBuyPrice": 20 } ``` #### Listing row ```json { "recordType": "listing", "status": "sold", "rank": 1, "title": "Nike Air Max size 9 women's", "price": "$30", "priceValue": 30, "originalPrice": "$125", "originalPriceValue": 125, "discountPercent": 76, "size": "US 9", "listingUrl": "https://poshmark.com/listing/...", "imageUrl": "https://di2ponv0v5otw.cloudfront.net/...", "scrapedAt": "2026-06-21T20:28:00.102Z" } ``` ### Dataset Views | View | Best for | |---|---| | `Sold comps` | Individual listings with price, discount, and size | | `Pricing summary` | One-row pricing intelligence for the query | ### Input Reference | Field | Meaning | |---|---| | `query` | Keyword to search on Poshmark | | `brand` | Optional brand page instead of search | | `availability` | `sold` (sold comps), `available` (active), or `all` | | `maxItems` | Max listings to extract (1-200; page is scrolled to load more) | | `includeActiveComparison` | Also scrape active listings and compute the spread | | `targetMarginPercent` | Margin used to compute `suggestedMaxBuyPrice` | | `proxyEnabled` / `proxyConfiguration` | Route through Apify Proxy (residential recommended if blocked) | | `startUrl` | Full Poshmark URL; overrides the above | ### Output Fields | Field | Meaning | |---|---| | `status` | `sold` or `active` (detected from the Poshmark badge) | | `price` / `priceValue` | Listing price as text and number | | `originalPrice` / `originalPriceValue` | Original retail price when shown | | `discountPercent` | Discount off original price (0-100) | | `size` | Parsed size token | | `medianSoldPrice` / `averageSoldPrice` | Central sold price for the query | | `activeVsSoldSpread` | Active median minus sold median | | `suggestedMaxBuyPrice` | Naive max buy price for your target margin | ### Limits and Caveats - **Sold comps reflect listed sold prices, not after-fee proceeds.** Poshmark does not publicly expose final sale dates or days-to-sell, so this Actor does not promise those fields. - `suggestedMaxBuyPrice` is a simple rule of thumb (`sold median x (1 - targetMargin)`). It ignores marketplace fees, shipping, and condition. Treat it as a starting point, not advice. - Pricing stats are most reliable with `maxItems` of 50-200; very narrow queries return fewer comps. - Poshmark renders with JavaScript and lazy-loads on scroll; the Actor uses a headless browser. Enable residential proxy if you hit blocks on repeated runs. - This Actor reads public listing data only; it does not log in or scrape private account data. ### Pricing Designed for **pay-per-result** pricing plus Apify platform usage. Because it launches a headless browser (and a second pass when active comparison is on), enable proxy only when needed to keep runs inexpensive. # Actor input Schema ## `query` (type: `string`): Keyword to search on Poshmark, e.g. 'nike air max women' or 'lululemon align leggings'. ## `brand` (type: `string`): Optional Poshmark brand name/slug. If set, the Actor starts from the brand page instead of search. ## `availability` (type: `string`): Which listings to pull. 'Sold' gives true sold comps - what items actually sold for. ## `maxItems` (type: `integer`): Maximum listing cards to extract (the page is scrolled to lazy-load more). 50-200 gives stable pricing stats. ## `includeActiveComparison` (type: `boolean`): When scraping sold items, also scrape current active listings for the same query and compute the active-vs-sold price spread. Doubles the run cost. ## `targetMarginPercent` (type: `integer`): Share of the median sold price you want to keep as margin. Used only to compute 'suggestedMaxBuyPrice' (a naive rule of thumb that ignores marketplace fees and shipping). ## `proxyEnabled` (type: `boolean`): Route the browser through Apify Proxy. Recommended (residential) if Poshmark starts blocking requests on repeated runs. ## `proxyConfiguration` (type: `object`): Apify Proxy settings used when 'Use Apify Proxy' is enabled. Residential is recommended for Poshmark. ## `startUrl` (type: `string`): Optional full Poshmark search/brand URL. Overrides query, brand, and availability. ## Actor input object example ```json { "query": "nike air max women", "brand": "", "availability": "sold", "maxItems": 50, "includeActiveComparison": false, "targetMarginPercent": 50, "proxyEnabled": false, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] }, "startUrl": "" } ``` # Actor output Schema ## `results` (type: `string`): No description ## `comps` (type: `string`): No description ## `summary` (type: `string`): No description # 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 = { "query": "nike air max women" }; // Run the Actor and wait for it to finish const run = await client.actor("webdata_labs/poshmark-sold-comps-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 = { "query": "nike air max women" } # Run the Actor and wait for it to finish run = client.actor("webdata_labs/poshmark-sold-comps-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 '{ "query": "nike air max women" }' | apify call webdata_labs/poshmark-sold-comps-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=webdata_labs/poshmark-sold-comps-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Poshmark Sold Comps Scraper - Resale Prices & Pricing Stats", "description": "Pull Poshmark sold comps and pricing stats so resellers know what items actually sell for. Returns sold listings plus median/average/min/max sold price, an optional active-vs-sold spread, and a suggested max buy price — exported as CSV/JSON.", "version": "0.1", "x-build-id": "7TK9dX6eqXJ0MrhHa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/webdata_labs~poshmark-sold-comps-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-webdata_labs-poshmark-sold-comps-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/webdata_labs~poshmark-sold-comps-scraper/runs": { "post": { "operationId": "runs-sync-webdata_labs-poshmark-sold-comps-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/webdata_labs~poshmark-sold-comps-scraper/run-sync": { "post": { "operationId": "run-sync-webdata_labs-poshmark-sold-comps-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "query": { "title": "Search query", "type": "string", "description": "Keyword to search on Poshmark, e.g. 'nike air max women' or 'lululemon align leggings'.", "default": "nike air max women" }, "brand": { "title": "Brand (optional)", "type": "string", "description": "Optional Poshmark brand name/slug. If set, the Actor starts from the brand page instead of search.", "default": "" }, "availability": { "title": "Availability", "enum": [ "sold", "available", "all" ], "type": "string", "description": "Which listings to pull. 'Sold' gives true sold comps - what items actually sold for.", "default": "sold" }, "maxItems": { "title": "Max listings", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum listing cards to extract (the page is scrolled to lazy-load more). 50-200 gives stable pricing stats.", "default": 50 }, "includeActiveComparison": { "title": "Compare against active listings", "type": "boolean", "description": "When scraping sold items, also scrape current active listings for the same query and compute the active-vs-sold price spread. Doubles the run cost.", "default": false }, "targetMarginPercent": { "title": "Target margin %", "minimum": 0, "maximum": 95, "type": "integer", "description": "Share of the median sold price you want to keep as margin. Used only to compute 'suggestedMaxBuyPrice' (a naive rule of thumb that ignores marketplace fees and shipping).", "default": 50 }, "proxyEnabled": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route the browser through Apify Proxy. Recommended (residential) if Poshmark starts blocking requests on repeated runs.", "default": false }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy settings used when 'Use Apify Proxy' is enabled. Residential is recommended for Poshmark.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }, "startUrl": { "title": "Custom start URL (optional)", "type": "string", "description": "Optional full Poshmark search/brand URL. Overrides query, brand, and availability.", "default": "" } } }, "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 } } } } } } } } } } ```