SNKRDUNK Scraper - Sneakers, Prices & Sales History

What SNKRDUNK Scraper can do

• Two ways in. Keyword search with the site's own brand and category filters and sort, or paste product links and sitemaps (one sitemap link streams in thousands of products). No URL building by hand.
• Deep product records. Every product carries 60+ fields: identity in Japanese and English, brand and model, price statistics, sizes, release info and more.
• Price statistics and sales history. Lowest, highest and average listing prices in JPY, used listing counts, offers, favourites, plus the most recent recorded sales with sizes and dates.
• Local prices and names. Japanese and English names and brands side by side, list price in JPY and localized MSRP, so cross-market comparisons need no extra lookups.
• Built for schedules. Incremental mode tags every product NEW, UPDATED, UNCHANGED, REAPPEARED or EXPIRED on recurring runs, and returns only what changed, so a daily monitor bills pennies instead of re-scraping everything.
• Fails loudly, never silently. If every connection is refused the run stops with a clear message, so "nothing found" is never confused with "could not read the site".

Choose what to collect

These inputs let you configure SNKRDUNK Scraper - Sneakers, Prices & Sales History. Open the actor on Apify to enter your values and review the current options.

Fields in the output

The documented dataset includes the fields below. Availability can depend on the source page and selected mode.

Example output

An example from this actor’s documentation. Values are illustrative; this is not a fresh live result.

{
  "styleCode": "XX1234-100",
  "productId": "20000001",
  "productCatalogId": "20000002",
  "name": "Sample Runner Low \"White/Grey\"",
  "nameJa": "サンプルランナー ロー",
  "nameEn": "Sample Runner Low \"White/Grey\"",
  "brand": "sample-brand",
  "brandName": "Sample Brand",
  "modelName": "Sample Runner",
  "category": "1",
  "price": 12800,
  "priceCurrency": "JPY",
  "priceCurrencySymbol": "JP ¥",
  "condition": "S",
  "isNew": true,
  "isUsed": false,
  "isSold": false,
  "productType": "secondHandCatalog",
  "releaseDate": "2024-03-15T00:00:00Z",
  "regularPriceJpy": 15400,
  "minPriceJpy": 12900,
  "maxPriceJpy": 24000,
  "averagePriceJpy": 15600,
  "highestSoldPriceJpy": 39800,
  "usedMinPriceJpy": 8900,
  "usedListingCount": 12,
  "offerCount": 5,
  "favoriteCount": 4200,
  "listingCountJp": 276,
  "msrpValue": 154.2,
  "msrpCurrency": "USD",
  "minSize": "22cm",
  "maxSize": "32cm",
  "availableSizes": [
    "22.5cm",
    "25cm",
    "26cm",
    "27cm"
  ],
  "lastSalePrice": 13500,
  "lastSaleAt": "2026-01-20T05:12:00Z",
  "salesTrackedCount": 2,
  "tradingHistory": [
    {
      "price": 13500,
      "soldAt": "2026-01-20T05:12:00Z",
      "size": "26.5cm",
      "condition": "new"
    },
    {
      "price": 12800,
      "soldAt": "2026-01-19T10:02:00Z",
      "size": "26cm",
      "condition": "used"
    }
  ],
  "image": "https://cdn.snkrdunk.com/sample/sample.webp",
  "url": "https://snkrdunk.com/en/sneakers/XX1234-100",
  "searchKeyword": "sample runner",
  "searchRank": 1
}

Ways to use this data

• Sneaker resellers and boutiques: track lowest listings, average prices and last sale sizes to price your inventory and spot under-retail picks.
• Analysts and data teams: build price-history datasets across brands and categories, from single models to whole sitemap scopes.
• Collectors and enthusiasts: monitor favourite models and get only the new, changed or expired listings on each scheduled run.
• E-commerce and dropshipping tools: feed product names, images, prices and availability into catalogs and alerting bots.
• Market researchers: measure brand and category depth, listing counts and engagement (favourites) across the Japanese resale market.

Before you run

Start with a small input and check the resulting records against your expected fields. Source content and actor options can change; the current Apify listing is the reference for availability and pricing.

Questions about this actor