# Poshmark Sold Listings Scraper (resale price & markdown data) (`weltverbenzer/poshmark-sold-listings-scraper`) Actor Scrapes Poshmark SOLD listings for any search term: real sold price, original price, markdown %, size and URL. For resellers, repricing tools and market research. - **URL**: https://apify.com/weltverbenzer/poshmark-sold-listings-scraper.md - **Developed by:** [Johannes Witt](https://apify.com/weltverbenzer) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 — resale price, comps & markdown data Get the data resellers actually need: **real SOLD prices on Poshmark** — plus the original list price and the **markdown %**, so you instantly see what items truly sell for and how much they get discounted. Perfect for **resale price research, sold comps, repricing and sourcing decisions** on Poshmark. For any search term, this Poshmark scraper returns per sold item: **title, sold price, original price, markdown %, currency, size, and listing URL** — as clean JSON or CSV. ### Who it's for - **Resellers, flippers & thrifters** answering "what does this actually sell for on Poshmark, and at what discount?" - **Repricing, sourcing & inventory tools** that need *realized* resale prices (sold comps), not asking prices. - **Brand & market researchers** tracking secondhand demand, price trends and discount depth. ### What you can do with it - Pull **sold comps** for any brand, item or keyword (e.g. `lululemon align leggings`, `nike dunk`, `coach bag`). - See the **true sell-through price** and the **markdown %** (original vs. sold) per item. - Get an outlier-trimmed **median sold price** to benchmark your own pricing. - Feed realized prices into your repricing, sourcing or analytics pipeline via JSON/CSV/API. ### Why it's useful Asking prices are noise; **sold** prices are signal. This actor pulls Poshmark's sold listings reliably and adds the original-vs-sold **markdown %** — a quick read on pricing power and discount depth per item. ### Input | Field | Description | |-------|-------------| | `query` | Search term, e.g. `lululemon align leggings`, `nike dunk`, `coach handbag` | | `maxResults` | Max sold listings to return (1–2000) | | `proxyConfiguration` | Proxy (Apify Proxy supported) | ### Output (example record) ```json { "title": "Lululemon Align Pant", "soldPrice": 40, "originalPrice": 98, "markdownPct": 59.2, "currency": "USD", "size": "US 6", "url": "https://poshmark.com/listing/..." } ```` A `SUMMARY` record adds `soldMedianPrice` (outlier-trimmed) and `medianMarkdownPct`. ### FAQ **Does it return sold (not active) listings?** Yes — it targets Poshmark's *sold* listings, so you get realized prices, not asking prices. **What's the markdown %?** `(originalPrice − soldPrice) / originalPrice` — how far below list an item sold. It's `null` when a listing has no original price. **Which items can I search?** Any keyword or brand — clothing, shoes, bags, accessories, etc. **What format is the output?** Clean JSON or CSV, and the Apify API/integrations (Make, Zapier, webhooks). ### Pricing Pay-per-result — you only pay for the sold listings actually returned. Platform compute usage is included. ### Notes Returns publicly visible sold-listing data. Use responsibly and within Poshmark's terms. # Actor input Schema ## `query` (type: `string`): What to look up among SOLD Poshmark listings, e.g. 'lululemon align leggings' or 'nike dunk'. ## `maxResults` (type: `integer`): Maximum sold listings to return. ## `proxyConfiguration` (type: `object`): Proxy configuration. ## Actor input object example ```json { "query": "lululemon align", "maxResults": 100, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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": "lululemon align" }; // Run the Actor and wait for it to finish const run = await client.actor("weltverbenzer/poshmark-sold-listings-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": "lululemon align" } # Run the Actor and wait for it to finish run = client.actor("weltverbenzer/poshmark-sold-listings-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": "lululemon align" }' | apify call weltverbenzer/poshmark-sold-listings-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=weltverbenzer/poshmark-sold-listings-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Poshmark Sold Listings Scraper (resale price & markdown data)", "description": "Scrapes Poshmark SOLD listings for any search term: real sold price, original price, markdown %, size and URL. For resellers, repricing tools and market research.", "version": "0.1", "x-build-id": "Dq0h9TGEKNDF9dBeN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/weltverbenzer~poshmark-sold-listings-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-weltverbenzer-poshmark-sold-listings-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/weltverbenzer~poshmark-sold-listings-scraper/runs": { "post": { "operationId": "runs-sync-weltverbenzer-poshmark-sold-listings-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/weltverbenzer~poshmark-sold-listings-scraper/run-sync": { "post": { "operationId": "run-sync-weltverbenzer-poshmark-sold-listings-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", "required": [ "query" ], "properties": { "query": { "title": "Search term", "type": "string", "description": "What to look up among SOLD Poshmark listings, e.g. 'lululemon align leggings' or 'nike dunk'." }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Maximum sold listings to return.", "default": 100 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Proxy configuration.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```