Sellpy Product Search Scraper avatar

Sellpy Product Search Scraper

Pricing

from $2.00 / 1,000 results

Go to Apify Store
Sellpy Product Search Scraper

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

Stealth mode

Maintained by Community

Actor stats

0

Bookmarked

3

Total users

1

Monthly active users

22 days ago

Last modified

Share

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 Actor supports two scraping modes — use only one at a time:

  1. Scrape by URLs — scrape data directly from a list of Sellpy search result URLs.
{
"urls": [
"https://www.sellpy.se/search/Kvinna/Kläder/Klänningar?page=2"
],
"ignore_url_failures": true,
"max_items_per_url": 200
}
  1. Scrape by search filters — scrape data using a keyword and additional filters (sort order, price range, condition, etc.) instead of providing URLs.
{
"keyword": "dress",
"sort_by": "saleStartedAt_desc",
"is_fast_delivery": true,
"price_min": "50",
"price_max": "20000",
"condition": "Mycket bra",
"page": 1,
"max_items_per_url": 200
}

There is also a General settings group that applies to both modes.

1. Scrape by URLs

Use this mode when you already have specific search result URLs. When this mode is used, all options in the "Scrape by search filters" section will be disabled.

FieldTypeDefaultDescription
urlsarray(required)Direct links to Sellpy search result pages to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. URLs can include filter parameters (category, size, price range, page number) and support .se, .de, and other regional Sellpy domains.
ignore_url_failuresbooleantrueIf true, the scraper continues running when a URL fails instead of stopping the entire run. Recommended for bulk jobs.

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.

2. Scrape by search filters

Use this mode when you want to search using a keyword and additional filter attributes instead of scraping by URLs. If you use this mode, leave the urls field above empty.

FieldTypeDefaultDescription
keywordstringThe keyword to search for.
sort_bystring ("", saleStartedAt_desc, price_asc, price_desc)Sort results by Relevance (empty), Newest (saleStartedAt_desc), Price: Low to High (price_asc), or Price: High to Low (price_desc).
is_fast_deliverybooleanfalseIf true, only include items eligible for fast delivery.
price_minstringMinimum price to filter items by.
price_maxstringMaximum price to filter items by.
conditionstring ("", Bra, Mycket bra, Nytt, Acceptabelt, Dåligt)Item condition filter: All, Bra (Good), Mycket bra (Very good), Nytt (New), Acceptabelt (Acceptable), Dåligt (Poor).
pageintegerThe page number to start scraping from.

3. General settings

Applies to both scraping modes above.

FieldTypeDefaultDescription
max_items_per_urlinteger20The maximum number of products to extract per search URL (e.g., 200). Useful for controlling dataset size or testing.

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

FieldMeaning
Object IDUnique product identifier in Sellpy's system
Title Output OrderProduct name/title as displayed
Body Output OrderProduct description text
ImagesArray of product image URLs (multiple angles)
Created AtWhen the listing was first created
Updated AtLast modification timestamp
UserSeller/owner information

Classification & Attributes

FieldMeaning
CategoriesProduct category hierarchy (e.g., Women > Clothes > Dresses)
Brand ClassificationDetected or assigned brand name
Brand GroupsBrand grouping for analytics (luxury, fast-fashion, etc.)
MaterialsFabric composition (e.g., cotton, polyester, silk)
StyleStyle classification (casual, formal, sports, etc.)
SizesAvailable sizes or size category
Personalization Size CategoryStandardized size mapping for cross-market comparison
ConceptProduct concept or sub-category
KeywordsSearch keywords associated with the product
SegmentMarket segment classification

Marketplace Status & Operations

FieldMeaning
Is For SaleBoolean indicating if product is currently available
Is ReservedWhether the item is reserved by a buyer
Is On ShelfPhysical warehouse/storage status
Sale TypeType of sale (standard, auction, bundle, etc.)
Sale Started AtWhen the sale listing began
Sales ChannelWhich Sellpy market (SE, DE, etc.) the product is listed in
Storage SiteWarehouse or fulfillment location code
Item PackagingPackaging method or status

Pricing & Financial Metrics

FieldMeaning
PricingBase price in local currency
Price SEPrice in Swedish kronor (if applicable)
Price Drop SEDiscount amount or percentage reduction (Sweden market)
First Offered At SEInitial offering price in SE market
Featured InPremium placement or featured listing status
Last ChanceIndicator if listing is ending soon

Engagement & Performance Metrics

FieldMeaning
Favourite CountNumber of users who favorited the product
Favorite Count BucketBinned favorite count (e.g., 0-10, 11-50)
Favorite Count Bucket NordicNordic market-specific favorite distribution
Favorite Count Bucket DACHGermany/Austria/Switzerland market-specific buckets
Favorite Count Bucket EUBroader EU engagement metrics
Highlight ResultWhether product is highlighted in search results
Ranking InfoInternal ranking score or tier

Advanced Analytics Fields

FieldMeaning
Item AB Test FractionA/B test cohort assignment for experimentation
Relevance Ranking Normal Dist 15Relevance score for general search (standard distribution)
Relevance Ranking Normal Dist 15 Similar ItemRelevance when shown as similar product recommendation
Proximity Bucket V1 / Proximity Bucket V2Geographic proximity scoring versions
P2PPeer-to-peer transaction indicator or rating
Item IOItem input/output classification for operations
BagBag/cart assignment or tracking
Searchable External CategorySEO or external category mapping
MetadataAdditional unstructured metadata

How to Use

  1. 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).
  2. 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).
  3. Handle failures gracefully — Set ignore_url_failures: true to skip broken or blocked URLs without stopping the entire run.
  4. Run the scraper — Start the actor and monitor progress via the log console.
  5. 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.