Pricing

from $2.00 / 1,000 results

Sellpy Product Search Scraper

Scrape Sellpy.se product listings with 51+ data fields per item. Capture pricing, inventory status, brand info, images, customer favorites, and ranking metrics — perfect for market analysis, price monitoring, and resale business intelligence.

Pricing

from $2.00 / 1,000 results

Rating

0.0

(0)

Developer

Stealth mode

Actor stats

Bookmarked

Total users

Monthly active users

10 days ago

Last modified

Sellpy Product Search Scraper: Extract Secondhand Fashion Data at Scale

What Is Sellpy?

Sellpy is a leading European secondhand fashion marketplace operating primarily in Sweden (.se), Germany (.de), and neighboring Nordic countries. It connects millions of buyers and sellers of pre-owned clothing, shoes, and accessories. With thousands of active listings updated daily, Sellpy represents a valuable dataset for understanding fashion trends, pricing dynamics, and consumer demand in the circular economy. The Sellpy Product Search Scraper automates extraction of this marketplace data into structured, analyzable records.

Overview

The Sellpy Product Search Scraper extracts detailed product information from Sellpy's search results, transforming marketplace pages into structured datasets. It is designed for:

Fashion analysts tracking trends and price movements in secondhand markets
Marketplace researchers benchmarking inventory and pricing strategies
Fashion retailers monitoring competitor listings and consumer demand
Data scientists building models on circular fashion consumption patterns
Price aggregators feeding Sellpy data into comparison tools

The scraper handles pagination, respects marketplace structure, and returns 50+ fields per product including pricing data, images, brand classification, and marketplace-specific metadata.

Input Format

The scraper accepts a JSON configuration object for flexible search-based extraction:

{
  "urls": [
    "https://www.sellpy.se/search/Kvinna/Kläder/Klänningar?page=2"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 200
}

Field	Type	Description
`urls`	array	Direct links to Sellpy search results pages. Can include filter parameters (category, size, price range, page number). Supports .se, .de, and other regional Sellpy domains.
`max_items_per_url`	integer	Maximum products to extract per search URL (e.g., `200`). Useful for controlling dataset size or testing. Default: `20`.
`ignore_url_failures`	boolean	If `true`, scraper continues if a URL fails. If `false`, the entire run stops on first error. Recommended: `true` for bulk operations.

Tip: Use category-filtered URLs (e.g., Women/Clothes/Dresses) to target specific product segments. Pagination parameters are supported—add ?page=1, ?page=2, etc. to URLs.

Output Format

Sample output

{
  "created_at": 1777544948,
  "updated_at": 1782532817,
  "user": "Z9EgUawPFj",
  "bag": "D2lXAtZ1Nz",
  "metadata": {
    "size": "SHOES-EU-45",
    "season": [
      "Spring",
      "Summer",
      "Fall"
    ],
    "color": [
      "Red",
      "Black"
    ],
    "brand": "Asics",
    "model": "T516N",
    "demography": "Men",
    "country_of_origin": "VN",
    "type": "Running shoes",
    "condition": "Very good",
    "product_code": "F451015 PV"
  },
  "images": [
    "https://prod.images.sellpy.net/photoRobot-case-14-k-10/J76Y3hZiKu-fd92-0.jpg",
    "https://prod.images.sellpy.net/photoRobot-case-14-k-10/J76Y3hZiKu-fd92-90.jpg",
    "https://prod.images.sellpy.net/photoRobot-case-14-k-10/J76Y3hZiKu-fd92-270.jpg",
    "https://prod.images.sellpy.net/phone-images/J76Y3hZiKu-91ee.jpg",
    "https://prod.images.sellpy.net/phone-images/J76Y3hZiKu-994c.jpg"
  ],
  "sizes": [
    "SHOES-EU-45"
  ],
  "p2p": false,
  "is_reserved": false,
  "segment": "men",
  "item_io": "rLRCT4wPCb",
  "categories": {
    "lvl0": [
      "Men"
    ],
    "lvl1": [
      "Men > Shoes"
    ],
    "lvl2": [
      "Men > Shoes > Sport shoes"
    ]
  },
  "storage_site": "K",
  "is_on_shelf": true,
  "searchable_external_category": [
    "Men > Shoes > Sport shoes"
  ],
  "sale_type": "regular",
  "personalization_size_category": "SHOES-EU-45-Men > Shoes > Sport shoes",
  "title_output_order": [
    "brand",
    "type",
    "size"
  ],
  "body_output_order": [
    "brand",
    "type",
    "size",
    "sizeEstimated",
    "model",
    "material",
    "color",
    "demography",
    "extra"
  ],
  "item_ab_test_fraction": 0.2893018385419257,
  "brand_classification": {
    "styles": [
      "Performance",
      "Athleisure"
    ],
    "age_groups": [
      "Gen Y",
      "Gen X"
    ],
    "price_point": 4,
    "origin_vibe": "Japanese",
    "ethos": "Tech / Performance",
    "aesthetic_tone": "Functional"
  },
  "materials": null,
  "keywords": [
    "athletic shoes",
    "red sneakers",
    "performance footwear",
    "cushioned sole",
    "sports shoes",
    "outdoor footwear"
  ],
  "style": [
    "athleisure"
  ],
  "brand_groups": [
    "Athletic & Sportswear",
    "Footwear & Socks"
  ],
  "concept": [
    "Runner's High",
    "Athletic Wear & Training Shoes",
    "Activewear & Sportswear",
    "The Marathon Shop"
  ],
  "weight": 0.6,
  "item_packaging": "FGxNnLyDDp",
  "favourite_count": 3,
  "favorite_count_bucket": 2,
  "favorite_count_bucket_nordic": 1,
  "favorite_count_bucket_dach": 1,
  "favorite_count_bucket_eu": 0,
  "relevance_ranking_normal_dist_15_similar_item": null,
  "relevance_ranking_normal_dist_15": null,
  "proximity_bucket_v1": 1,
  "proximity_bucket_v2": 3,
  "sales_channel": "market",
  "pricing": {
    "amount": 2500,
    "currency": "CZK"
  },
  "is_for_sale": true,
  "sale_started_at": 1781798688003,
  "last_chance": false,
  "price_se": {
    "amount": 109000,
    "currency": "SEK"
  },
  "price_drop_se": {
    "show_until": 1781885087698,
    "old_price": {
      "amount": 115500,
      "currency": "SEK"
    }
  },
  "first_offered_at_se": 1777908755473,
  "featured_in": [
    "21651652-591f-4358-a153-371c95e78077",
    "8441a027-e90d-4fb0-9cb1-9fb409e7966d",
    "3ba91ead-f978-48b2-b68e-d33ca207c994",
    "83a97683-5d60-468c-9556-b8e3363ccc76",
    "52786708-e94c-4470-b9ed-013c291cad09",
    "dee4c350-8b91-493c-8f1c-f5d3097d1b75",
    "23336ec7-b11a-4ea3-906e-1cdc30e7a7df",
    "415c8534-b905-4f2e-bdd5-7b46f92b87df",
    "3d486eb4-9362-42b3-90ca-78f15d0c7bcf",
    "c0d3d298-1cf0-4cd2-aef4-3bc159c1110c",
    "91b2fa12-28bc-4d19-ba19-e4c29ac44821",
    "de981fa2-ff62-46d0-8578-69c95a863ef3",
    "fe5087f4-d5d1-4ce4-a559-8887190d57f7",
    "ae65e87a-ff29-4e1b-889c-17a6f997dec8",
    "c023de45-cc45-445e-a654-ecb1880b91bf",
    "2efcf323-d911-4a27-9f5f-cdaa25bce22a",
    "11a39d3b-0181-42cb-a8d6-6472cfd51da0",
    "d2e4d407-e6a1-45f8-ad76-baae8cbc87cd",
    "0ee2fe4e-5887-4b35-83a9-a801865968fd",
    "dd8c6a4a-5946-4659-bd88-eadb52a70c24",
    "3109642a-a12f-424a-b9e2-aa2ab68a7b1f",
    "80a8757f-4de5-4f91-a9e3-dec553912dec"
  ],
  "object_id": "fMmJQ6Ww5C",
  "highlight_result": {
    "user": {
      "value": "Z9EgUawPFj",
      "match_level": "none",
      "matched_words": []
    },
    "metadata": {
      "size": {
        "value": "__ais-highlight__SHOE__/ais-highlight__S-EU-45",
        "match_level": "full",
        "fully_highlighted": false,
        "matched_words": [
          "shoe"
        ]
      },
      "season": [
        {
          "value": "Spring",
          "match_level": "none",
          "matched_words": []
        },
        {
          "value": "Summer",
          "match_level": "none",
          "matched_words": []
        },
        {
          "value": "Fall",
          "match_level": "none",
          "matched_words": []
        }
      ],
      "color": [
        {
          "value": "Red",
          "match_level": "none",
          "matched_words": []
        },
        {
          "value": "Black",
          "match_level": "none",
          "matched_words": []
        }
      ],
      "brand": {
        "value": "Asics",
        "match_level": "none",
        "matched_words": []
      },
      "model": {
        "value": "T516N",
        "match_level": "none",
        "matched_words": []
      },
      "demography": {
        "value": "Men",
        "match_level": "none",
        "matched_words": []
      },
      "type": {
        "value": "Running __ais-highlight__shoe__/ais-highlight__s",
        "match_level": "full",
        "fully_highlighted": false,
        "matched_words": [
          "shoe"
        ]
      }
    },
    "sizes": [
      {
        "value": "__ais-highlight__SHOE__/ais-highlight__S-EU-45",
        "match_level": "full",
        "fully_highlighted": false,
        "matched_words": [
          "shoe"
        ]
      }
    ],
    "keywords": [
      {
        "value": "athletic __ais-highlight__shoe__/ais-highlight__s",
        "match_level": "full",
        "fully_highlighted": false,
        "matched_words": [
          "shoe"
        ]
      },
      {
        "value": "red sneakers",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "performance footwear",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "cushioned sole",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "sports __ais-highlight__shoe__/ais-highlight__s",
        "match_level": "full",
        "fully_highlighted": false,
        "matched_words": [
          "shoe"
        ]
      },
      {
        "value": "outdoor footwear",
        "match_level": "none",
        "matched_words": []
      }
    ],
    "style": [
      {
        "value": "athleisure",
        "match_level": "none",
        "matched_words": []
      }
    ],
    "featured_in": [
      {
        "value": "21651652-591f-4358-a153-371c95e78077",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "8441a027-e90d-4fb0-9cb1-9fb409e7966d",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "3ba91ead-f978-48b2-b68e-d33ca207c994",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "83a97683-5d60-468c-9556-b8e3363ccc76",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "52786708-e94c-4470-b9ed-013c291cad09",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "dee4c350-8b91-493c-8f1c-f5d3097d1b75",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "23336ec7-b11a-4ea3-906e-1cdc30e7a7df",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "415c8534-b905-4f2e-bdd5-7b46f92b87df",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "3d486eb4-9362-42b3-90ca-78f15d0c7bcf",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "c0d3d298-1cf0-4cd2-aef4-3bc159c1110c",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "91b2fa12-28bc-4d19-ba19-e4c29ac44821",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "de981fa2-ff62-46d0-8578-69c95a863ef3",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "fe5087f4-d5d1-4ce4-a559-8887190d57f7",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "ae65e87a-ff29-4e1b-889c-17a6f997dec8",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "c023de45-cc45-445e-a654-ecb1880b91bf",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "2efcf323-d911-4a27-9f5f-cdaa25bce22a",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "11a39d3b-0181-42cb-a8d6-6472cfd51da0",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "d2e4d407-e6a1-45f8-ad76-baae8cbc87cd",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "0ee2fe4e-5887-4b35-83a9-a801865968fd",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "dd8c6a4a-5946-4659-bd88-eadb52a70c24",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "3109642a-a12f-424a-b9e2-aa2ab68a7b1f",
        "match_level": "none",
        "matched_words": []
      },
      {
        "value": "80a8757f-4de5-4f91-a9e3-dec553912dec",
        "match_level": "none",
        "matched_words": []
      }
    ]
  },
  "ranking_info": {
    "forced_typo_first_in_ranking": true,
    "nb_typos": 0,
    "first_matched_word": 0,
    "proximity_distance": 0,
    "user_score": 900,
    "geo_distance": 0,
    "geo_precision": 1,
    "nb_exact_words": 0,
    "words": 1,
    "filters": 1
  },
  "from_url": "https://www.sellpy.com/search?page=2&query=shoe"
}

Each scraped product returns a comprehensive record with 50+ fields covering product details, marketplace metadata, and pricing:

Product Identification & Metadata

Field	Meaning
`Object ID`	Unique product identifier in Sellpy's system
`Title Output Order`	Product name/title as displayed
`Body Output Order`	Product description text
`Images`	Array of product image URLs (multiple angles)
`Created At`	When the listing was first created
`Updated At`	Last modification timestamp
`User`	Seller/owner information

Classification & Attributes

Field	Meaning
`Categories`	Product category hierarchy (e.g., Women > Clothes > Dresses)
`Brand Classification`	Detected or assigned brand name
`Brand Groups`	Brand grouping for analytics (luxury, fast-fashion, etc.)
`Materials`	Fabric composition (e.g., cotton, polyester, silk)
`Style`	Style classification (casual, formal, sports, etc.)
`Sizes`	Available sizes or size category
`Personalization Size Category`	Standardized size mapping for cross-market comparison
`Concept`	Product concept or sub-category
`Keywords`	Search keywords associated with the product
`Segment`	Market segment classification

Marketplace Status & Operations

Field	Meaning
`Is For Sale`	Boolean indicating if product is currently available
`Is Reserved`	Whether the item is reserved by a buyer
`Is On Shelf`	Physical warehouse/storage status
`Sale Type`	Type of sale (standard, auction, bundle, etc.)
`Sale Started At`	When the sale listing began
`Sales Channel`	Which Sellpy market (SE, DE, etc.) the product is listed in
`Storage Site`	Warehouse or fulfillment location code
`Item Packaging`	Packaging method or status

Pricing & Financial Metrics

Field	Meaning
`Pricing`	Base price in local currency
`Price SE`	Price in Swedish kronor (if applicable)
`Price Drop SE`	Discount amount or percentage reduction (Sweden market)
`First Offered At SE`	Initial offering price in SE market
`Featured In`	Premium placement or featured listing status
`Last Chance`	Indicator if listing is ending soon

Engagement & Performance Metrics

Field	Meaning
`Favourite Count`	Number of users who favorited the product
`Favorite Count Bucket`	Binned favorite count (e.g., 0-10, 11-50)
`Favorite Count Bucket Nordic`	Nordic market-specific favorite distribution
`Favorite Count Bucket DACH`	Germany/Austria/Switzerland market-specific buckets
`Favorite Count Bucket EU`	Broader EU engagement metrics
`Highlight Result`	Whether product is highlighted in search results
`Ranking Info`	Internal ranking score or tier

Advanced Analytics Fields

Field	Meaning
`Item AB Test Fraction`	A/B test cohort assignment for experimentation
`Relevance Ranking Normal Dist 15`	Relevance score for general search (standard distribution)
`Relevance Ranking Normal Dist 15 Similar Item`	Relevance when shown as similar product recommendation
`Proximity Bucket V1` / `Proximity Bucket V2`	Geographic proximity scoring versions
`P2P`	Peer-to-peer transaction indicator or rating
`Item IO`	Item input/output classification for operations
`Bag`	Bag/cart assignment or tracking
`Searchable External Category`	SEO or external category mapping
`Metadata`	Additional unstructured metadata

How to Use

Find search URLs — Navigate to Sellpy (.se, .de, or other regional domain) and perform product searches. Copy the full URL including filter parameters (e.g., category, size, price).
Configure input — Paste search URLs into the urls array. Adjust max_items_per_url to control extraction volume (e.g., 50 for quick tests, 200 for full dataset).
Handle failures gracefully — Set ignore_url_failures: true to skip broken or blocked URLs without stopping the entire run.
Run the scraper — Start the actor and monitor progress via the log console.
Export and analyze — Download results as JSON, CSV, or Excel for analysis in BI tools, spreadsheets, or databases.

Best practices:

Use narrow search filters (e.g., specific brand, size range, price range) to focus data collection.
Test with max_items_per_url: 20 first to validate output structure.
For large-scale collection, space requests over time to avoid rate limiting.

Use Cases & Business Value

Fashion trend analysis: Track which brands, styles, and materials gain traction in secondhand markets
Pricing intelligence: Monitor price drops, discounts, and seasonal patterns across regions
Competitive benchmarking: Analyze how competitor sellers price similar items
Inventory research: Understand stock levels and product availability trends
Circular economy insights: Study consumer preferences for sustainable fashion
Market expansion: Identify underserved categories or geographic opportunities

By automating product data collection, teams eliminate weeks of manual research and unlock data-driven insights into the fast-growing secondhand fashion market.

Conclusion

The Sellpy Product Search Scraper delivers comprehensive, machine-readable fashion marketplace data. With 50+ fields covering product attributes, pricing, and engagement metrics, it serves researchers, analysts, and businesses building tools in the circular economy space. Start scraping today to harness the power of Sellpy's rich product catalog.

Elcorteingles Product Search Scraper

stealth_mode/elcorteingles-product-search-scraper

Scrape product listings from El Corte Inglés Portugal with 51+ data fields including pricing, inventory, images, and detailed product metadata. Perfect for price monitoring, market intelligence, and competitive analysis in Portuguese e-commerce.

Stealth mode

Walgreens Product Search Scraper

stealth_mode/walgreens-product-search-scraper

Scrape product search results from Walgreens with 51+ data fields including pricing, inventory, images, ratings, and fulfillment details. Perfect for price monitoring, retail analytics, and product intelligence across thousands of SKUs.

Stealth mode

Walgreens Reviews Scraper

stealth_mode/walgreens-reviews-scraper

Stealth mode

Faire Product Search Scraper

soft_alexist/faire-product-search-scraper

Extract detailed product listings from Faire.com wholesale marketplace. Scrape product names, images, pricing, brand info, promotional status, and 14+ fields per item — perfect for market research, price monitoring, and product catalog building.

Soft Alexist

Priceoye Product Search Scraper

stealth_mode/priceoye-product-search-scraper

Scrape product search results from Priceoye.pk instantly. Capture product titles, prices, ratings, brand info, stock status, and 40+ fields per item — perfect for price monitoring, market analysis, and competitive intelligence in Pakistan's e-commerce market.

Stealth mode

🛍️ Vinted Scraper

scrapio/vinted-scraper

Scrape Vinted listings including product titles, prices, brands, sizes, conditions, seller details, locations, images, favorites, and listing URLs. Perfect for resale market research, price tracking, competitor analysis, inventory monitoring, and trend discovery.

Scrapio

Qvc Product Search Scraper

stealth_mode/qvc-product-search-scraper

Scrape QVC product listings with detailed pricing, availability, and assets data. Extract 12+ fields per item including product numbers, descriptions, images, reviews, and shipping info — perfect for price monitoring, competitive analysis, and inventory tracking.

Stealth mode

Apohem Product Search Scraper

stealth_mode/apohem-product-search-scraper

Scrape product data from Apohem.se with precision. Extract prices, stock status, brand info, promotions, medical classifications, and 40+ fields per product — perfect for price monitoring, market research, and product aggregation.

Stealth mode

Vivantis Product Search Scraper

stealth_mode/vivantis-product-search-scraper

Scrape beauty and fragrance product listings from Hondoscenter with precision. Capture SKUs, prices, stock status, ratings, images, and 30+ fields per product — perfect for price monitoring, inventory sync, and ecommerce analytics.

Stealth mode

Boots Product Search Scraper

stealth_mode/boots-product-search-scraper

Scrape product listings from Boots.com with detailed pricing, inventory, and review data. Collect 20+ fields per item including variants, stock status, promotional offers, and delivery options — perfect for price monitoring, competitive analysis, and market research.

Stealth mode