# Poshmark Sold Listings Scraper - sold prices & dates (`ciel_labs/poshmark-sold-listings-price-comps`) Actor
SOLD Poshmark listings as clean records: sold price & date, brand, size, condition. Filter by brand, category, keyword. First 25 free, then $0.004/record.
- **URL**: https://apify.com/ciel\_labs/poshmark-sold-listings-price-comps.md
- **Developed by:** [Lawrence Sundar](https://apify.com/ciel_labs) (community)
- **Categories:** E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $4.00 / 1,000 sold listing delivereds
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
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 & Price Comps
**The comps resellers actually price against — SOLD Poshmark listings with sold price + sold date, by brand or category. Pennies per record.**
Active asking prices tell you what sellers *hope* to get. Sold listings tell you what buyers *actually paid* — and when. This actor returns clean, sheet-ready **sold** comps from Poshmark's public sold feeds: sold price, sold date, brand, size, condition, and a direct link to every listing.
- **$0.004 per record**, first **25 records of every run free**. 500 fresh Nike comps ≈ $1.90.
- Pure pay-per-event: no run-start fee. Tune your filters and re-run freely.
### What you get
One flat record per sold listing — drop it straight into a spreadsheet, pricing model, or repricer:
| Field | Description |
|---|---|
| `id` | Poshmark listing id |
| `title` | Listing title |
| `sold_price` | What it actually sold for |
| `currency` | Listing currency (`USD` on poshmark.com) |
| `original_price` | Seller's original price (`null` when the seller didn't set one) |
| `sold_at` | Sold timestamp (when the listing's inventory flipped to sold) |
| `brand` | Brand |
| `size` | Size as displayed |
| `condition` | `nwt` (new with tags) · `used` · `null` when not stated |
| `department` | `Women` · `Men` · `Kids` · … |
| `category` | `Shoes` · `Dresses` · `Bags` · … |
| `listing_url` | Direct link to the listing page |
| `image_url` | Cover photo |
| `seller_handle` | Public seller username |
| `raw` | Full original listing block (optional, off by default) |
### Usage
- **Default run (free):** no input needed — the latest 25 sold Nike listings, $0.
- **Sold comps for a brand:** `brand: "lululemon athletica"`, `maxItems: 200`
- **What do Dunk Lows actually sell for?** `brand: "Nike"`, `keyword: "dunk low"`, `maxItems: 100`
- **Sold women's dresses over $50:** `category: "Women-Dresses"`, `minPrice: 50`
- **Brand within a category:** `brand: "Coach"`, `category: "Women-Bags"` (brand feed, category-filtered)
#### Input reference
| Field | Type | Default | Notes |
|---|---|---|---|
| `brand` | string | `Nike` (when nothing else given) | Brand name as on Poshmark |
| `category` | string | — | Category page slug, e.g. `Women-Dresses`, `Men-Shoes` |
| `keyword` | string | — | Case-insensitive title filter (applied client-side) |
| `size` | string | — | Exact size, e.g. `M`, `10` |
| `minPrice` / `maxPrice` | integer | — | Sold-price band, inclusive (USD) |
| `department` | string | — | `Women` · `Men` · `Kids` · `Home` · … |
| `maxItems` | integer | `25` | First 25 free, then $0.004/record |
| `includeRaw` | boolean | `false` | Attach the full original listing block |
Give a **brand and/or a category**. When both are set, the brand's sold feed is fetched and the category filters it.
### How it works (and what it deliberately doesn't do)
This actor reads Poshmark's **public brand/category sold pages** — the same pages any browser sees, no login, no private API:
- **Robots-clean by design.** Poshmark's `robots.txt` disallows its `/search` and `/api` endpoints — this actor never touches them. Keyword filtering therefore runs client-side over the fetched sold records instead of through Poshmark search.
- **Sequential, rate-limited fetching.** One page at a time with a politeness delay. No hammering.
- **No PII beyond the public seller handle.** No buyer data exists on these pages at all.
- **Sold means sold.** Every record is individually verified as sold (`inventory.status = sold_out` with a sold timestamp) before it's delivered — an active listing is never charged or emitted.
### Honest limitations
- **Newest-first, up to ~5,000 per query.** Poshmark caps any single feed at about 5,000 results; sorting is by recency of listing activity. For deep history, slice by category/size/price band across runs.
- **No free-text search.** Keyword matching is a client-side title filter over the brand/category feed you fetched (see robots posture above) — a keyword-only run without a brand or category is not supported.
- **Sold price is the listing's final price.** Poshmark does not publish accepted-offer amounts; where a sale closed via a private offer, the listed price is what the page reports.
- **`original_price` is null when the seller never set one** (about 40% of live records) — we don't invent a fake comp.
- **US site.** Data comes from poshmark.com (USD).
### FAQ
**Why sold listings instead of active ones?** Pricing against asks inflates your expectations. Sold comps are the number the market actually cleared at — the same reason eBay's "sold items" filter is the reseller standard.
**Can I monitor continuously?** Schedule the actor (e.g. daily) with your brand/filters; each run returns the newest sold listings first. Deduplicate downstream by `id`.
**What if a brand has no sold listings?** You get an empty (free) dataset and a warning in the log — check the brand's spelling as it appears on poshmark.com.
# Actor input Schema
## `brand` (type: `string`):
Brand whose SOLD listings to fetch, exactly as it appears on Poshmark — e.g. Nike, lululemon athletica, Coach. Give a brand and/or a category; with neither, the run defaults to Nike.
## `category` (type: `string`):
Category page slug, e.g. Women-Dresses, Men-Shoes, Women-Bags. If a brand is ALSO given, the brand's sold feed is fetched and this becomes a category filter on it.
## `keyword` (type: `string`):
Case-insensitive title filter, e.g. dunk low. Applied client-side over the fetched sold listings (Poshmark's search endpoint is robots-disallowed — this actor stays on robots-clean pages).
## `size` (type: `string`):
Exact size filter (case-insensitive), e.g. M, 10, XL.
## `minPrice` (type: `integer`):
Only include listings that SOLD for at least this much (USD).
## `maxPrice` (type: `integer`):
Only include listings that SOLD for at most this much (USD).
## `department` (type: `string`):
Department filter, e.g. Women, Men, Kids, Home.
## `maxItems` (type: `integer`):
Maximum sold listings to return. The first 25 records of every run are FREE; each record after that costs $0.004.
## `includeRaw` (type: `boolean`):
Attach the full original Poshmark grid record to each row (for pipelines that want every field).
## Actor input object example
```json
{
"brand": "Nike",
"maxItems": 25,
"includeRaw": false
}
````
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"brand": "Nike"
};
// Run the Actor and wait for it to finish
const run = await client.actor("ciel_labs/poshmark-sold-listings-price-comps").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "brand": "Nike" }
# Run the Actor and wait for it to finish
run = client.actor("ciel_labs/poshmark-sold-listings-price-comps").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 '{
"brand": "Nike"
}' |
apify call ciel_labs/poshmark-sold-listings-price-comps --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=ciel_labs/poshmark-sold-listings-price-comps",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Poshmark Sold Listings Scraper - sold prices & dates",
"description": "SOLD Poshmark listings as clean records: sold price & date, brand, size, condition. Filter by brand, category, keyword. First 25 free, then $0.004/record.",
"version": "0.1",
"x-build-id": "fhTbvHN2z79TSz6WS"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/ciel_labs~poshmark-sold-listings-price-comps/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-ciel_labs-poshmark-sold-listings-price-comps",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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/ciel_labs~poshmark-sold-listings-price-comps/runs": {
"post": {
"operationId": "runs-sync-ciel_labs-poshmark-sold-listings-price-comps",
"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/ciel_labs~poshmark-sold-listings-price-comps/run-sync": {
"post": {
"operationId": "run-sync-ciel_labs-poshmark-sold-listings-price-comps",
"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": {
"brand": {
"title": "Brand",
"type": "string",
"description": "Brand whose SOLD listings to fetch, exactly as it appears on Poshmark — e.g. Nike, lululemon athletica, Coach. Give a brand and/or a category; with neither, the run defaults to Nike."
},
"category": {
"title": "Category",
"type": "string",
"description": "Category page slug, e.g. Women-Dresses, Men-Shoes, Women-Bags. If a brand is ALSO given, the brand's sold feed is fetched and this becomes a category filter on it."
},
"keyword": {
"title": "Keyword",
"type": "string",
"description": "Case-insensitive title filter, e.g. dunk low. Applied client-side over the fetched sold listings (Poshmark's search endpoint is robots-disallowed — this actor stays on robots-clean pages)."
},
"size": {
"title": "Size",
"type": "string",
"description": "Exact size filter (case-insensitive), e.g. M, 10, XL."
},
"minPrice": {
"title": "Min sold price",
"minimum": 0,
"type": "integer",
"description": "Only include listings that SOLD for at least this much (USD)."
},
"maxPrice": {
"title": "Max sold price",
"minimum": 0,
"type": "integer",
"description": "Only include listings that SOLD for at most this much (USD)."
},
"department": {
"title": "Department",
"type": "string",
"description": "Department filter, e.g. Women, Men, Kids, Home."
},
"maxItems": {
"title": "Max records",
"minimum": 1,
"type": "integer",
"description": "Maximum sold listings to return. The first 25 records of every run are FREE; each record after that costs $0.004.",
"default": 25
},
"includeRaw": {
"title": "Include raw listing block",
"type": "boolean",
"description": "Attach the full original Poshmark grid record to each row (for pipelines that want every field).",
"default": false
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```