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    "description": "Scrape sold Poshmark listings for resale comps. Export sold price, brand, size, category, seller, image, and URL data for pricing research.",
    "isPublic": true,
    "createdAt": "2026-06-14T13:23:43.819Z",
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    "exampleRunInput": {
      "body": "{\"query\": \"nike shoes\", \"maxItems\": 20, \"maxPages\": 2, \"sortBy\": \"added_desc\", \"proxyConfiguration\": {\"useApifyProxy\": false}}",
      "contentType": "application/json"
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    "categories": [
      "ECOMMERCE",
      "AUTOMATION",
      "BUSINESS"
    ],
    "isDeprecated": false,
    "title": "Poshmark Sold Listings Scraper",
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    "seoTitle": "Poshmark Sold Listings Scraper for Sold Comps",
    "seoDescription": "Scrape Poshmark sold listings and resale comps with sold prices, brands, sizes, sellers, images, and item URLs for resale price research in CSV or JSON.",
    "pricingInfos": [
      {
        "pricingModel": "PAY_PER_EVENT",
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              "eventDescription": "Per sold Poshmark listing saved to the dataset",
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                },
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            },
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              "eventTitle": "Sold listing saved",
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            },
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              "eventDescription": "One-time fee charged when a run starts.",
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              "isOneTimeEvent": true
            },
            "item": {
              "eventTitle": "Sold listing saved",
              "eventDescription": "Charged per sold Poshmark listing saved to the dataset.",
              "eventTieredPricingUsd": {
                "FREE": {
                  "tieredEventPriceUsd": 0.000575
                },
                "BRONZE": {
                  "tieredEventPriceUsd": 0.0005
                },
                "SILVER": {
                  "tieredEventPriceUsd": 0.00039
                },
                "GOLD": {
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    ],
    "notice": "NONE",
    "isCritical": false,
    "isGeneric": false,
    "hasNoDataset": false,
    "isSourceCodeHidden": true,
    "standbyUrl": null,
    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## Poshmark Sold Listings Scraper\n\nA scraper that collects public sold-listing results from Poshmark search pages and turns them into a structured dataset of resale comparables (sold comps). It paginates sold-search results, extracts listing metadata and sales information — including sold price and currency, original list price when shown, brand, size, category/department, seller identifiers, listing identifiers and public URLs, image links, status/inventory indicators, and timestamps (listing, sold, and extraction times) — and outputs records suitable for pricing research, trend analysis, and automated workflows.\n\n## Use cases\n\n- Resellers and flippers: research recent sold comps to price inventory before purchase or listing.  \n- Ecommerce analysts: monitor secondhand demand, compare resale price ranges, and build trend reports by brand, category, or style.  \n- Pricing teams: use real-market sold data as evidence when setting price bands for pre-owned apparel, shoes, accessories, and collectibles.  \n- Researchers and data teams: aggregate sold listings for dashboards, enrichment, and historical market studies.  \n- Resale pricing checks: collect a sample of sold comps, remove outliers, and derive median and range for pricing decisions.  \n- Brand demand reporting: run recurring searches to track sold-price ranges, category distribution, and popular sizes over time.  \n- Inventory sourcing: compare recent sold prices to expected purchase costs for lot buying decisions.  \n- Automated monitoring: schedule regular searches for tracked brands/models to refresh comps and surface outliers for review.",
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  }
}