Zalando Scraper — Products, Prices, Discounts, Sizes & Images 🛍️

This Zalando scraper extracts the full Zalando fashion catalog over plain HTTP. For every product you get the brand, product name, colour, category, department, current price, original price, discount %, sale flag, available sizes, product flags, image and URL — from any category, brand, search or filtered page, on any Zalando country domain. No login, no API key, no browser extension, no coding. Point it at a URL or type a search keyword and the actor paginates the whole listing for you.

Use this Zalando scraper to scrape Zalando products at scale and export to JSON, CSV, Excel, or API.

Built for e-commerce analysts, price-monitoring and repricing teams, dropshippers and resellers, fashion-trend researchers, brand managers and competitive-intelligence teams who need structured Zalando data without maintaining a browser farm.

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🔎 Why scrape Zalando?

Zalando is one of Europe's largest online fashion and lifestyle platforms, operating across Germany, Austria, Switzerland, the UK, Ireland, France, Belgium, Italy, Spain, the Netherlands, Poland and more. Its catalog holds millions of articles from thousands of brands, with prices, markdowns and size availability that change every day. That makes Zalando a goldmine of fashion pricing, assortment and availability data — but it's locked inside paginated, JavaScript-hydrated listing pages that are painful to collect by hand.

Manually copying products across dozens of categories, brands and country domains is slow, error-prone and impossible to keep fresh. Prices move, items sell out of specific sizes, new seasons drop, and sale events reshuffle the whole catalog overnight. A reliable Zalando scraper turns those listing pages into a clean, de-duplicated dataset you can refresh on a schedule and feed straight into a spreadsheet, BI tool or repricing engine.

Common reasons people scrape Zalando:

• Price and discount monitoring — track price drops, markdown depth and sale events across categories and brands.
• Competitor and market intelligence — see which brands and products are listed, at what price, in which sizes.
• Dropshipping and reselling research — find in-demand products, current prices and real stock availability.
• Assortment and availability tracking — monitor which sizes are in stock for key products over time.
• Repricing and MAP enforcement — compare your prices against Zalando's live currentPrice and originalPrice.
• Fashion-trend and seasonality analysis — build historical datasets of brands, categories, colours and prices.
• Catalog and feed enrichment — pull images, SKUs, colours and categories to enrich product feeds.

✨ What this Zalando scraper does

• ✅ Two ways to target data — paste any Zalando catalog URL (category, brand, search or filtered listing) into startUrls, or type a search keyword and let the actor build the search URL for you.
• ✅ Automatic pagination — walks the listing with ?p=N, page after page, and returns hundreds to thousands of products per URL, de-duplicated by SKU as it goes.
• ✅ Rich product fields on every row — identity (sku, name, brand, color), classification (category silhouette, targetGroup department), pricing (currentPrice, originalPrice, currency), discounts (onSale, discountPercent, discountAmount), sizes (availableSizes, availableSizesCount), badges (flags), plus url, image and a scrapedAt timestamp.
• ✅ Built-in sale filters — keep only discounted products (onlyDiscounted) or only items with a minimum markdown (minDiscountPercent).
• ✅ Any country domain — works with .de, .at, .ch, .co.uk, .ie, .fr, .be, .it, .es, .nl, .pl and more; prices come back in that country's currency.
• ✅ Fast, cheap, pure HTTP — no headless browser, no login, no API key. The actor reads Zalando's server-rendered hydration payload directly.
• ✅ Reliable at scale — automatic retries with backoff, proxy rotation on every request, and graceful handling of the end of a catalog.
• ✅ Export anywhere — download as JSON, CSV, Excel, HTML or XML, or pull from the Apify API.

🎯 Use cases

• Repricing & price intelligence teams — monitor Zalando prices and discount depth to drive dynamic pricing.
• Dropshippers & resellers — source trending products with live price and size availability.
• Brand & MAP managers — watch how your products are priced and discounted on Zalando.
• Market & competitive analysts — benchmark assortment, brand mix and price positioning by category and country.
• Fashion-trend researchers — track colours, silhouettes, brands and seasonal price movements over time.
• E-commerce catalog teams — enrich product feeds with Zalando SKUs, images, colours and categories.
• Deal & coupon sites — surface the deepest markdowns using the built-in discount filters.
• Data & BI teams — build a refreshable Zalando dataset for dashboards and reporting.

📥 Input

Give the scraper startUrls (any Zalando catalog URL) and/or a search keyword with a country and gender. Then optionally add sale filters and a maxItems cap. Every field is optional — with no input the actor runs a small demo on men's sneakers.

Field	Type	Description
startUrls	array	Zalando category / brand / search / filtered page URLs. Filter on Zalando (brand, category, price, colour, size…) and paste the resulting URL. Works on any country domain. The scraper paginates automatically.
search	string	A keyword to search instead of (or in addition to) URLs, e.g. nike air max. Combined with country and gender.
country	string	Zalando country domain for the search keyword: de, at, ch, co.uk, ie, fr, be, it, es, nl, pl. Default de.
gender	string	Department the search keyword applies to: women, men or kids. Default women.
onlyDiscounted	boolean	Keep only products currently on sale (reduced from the original price). Default false.
minDiscountPercent	integer	Keep only products discounted by at least this percentage (e.g. 30). 0 = ignore.
maxItems	integer	Maximum products to collect per URL / search. Default 500.
proxyConfiguration	object	Optional. Defaults to Apify Proxy; recommended for larger runs.

Example input

{
  "startUrls": [
    { "url": "https://www.zalando.de/damenbekleidung-kleider/" }
  ],
  "search": "nike air max",
  "country": "de",
  "gender": "men",
  "onlyDiscounted": true,
  "minDiscountPercent": 30,
  "maxItems": 500
}

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📤 Output

Each dataset row is one Zalando product. Below is a real record from a fresh run of the women's dresses category (https://www.zalando.de/damenbekleidung-kleider/):

{
  "sku": "EV421C1T7-Q11",
  "name": "Jersey dress - black",
  "brand": "Even&Odd by Zalando",
  "color": "black",
  "category": "DRESS",
  "targetGroup": "WOMEN",
  "url": "https://en.zalando.de/evenandodd-by-zalando-jersey-dress-black-ev421c1t7-q11.html",
  "currency": "EUR",
  "currentPrice": 27.99,
  "originalPrice": 27.99,
  "onSale": false,
  "discountPercent": 0,
  "discountAmount": 0,
  "availableSizes": ["XS", "S", "M", "L", "XL"],
  "availableSizesCount": 5,
  "flags": ["New"],
  "image": "https://img01.ztat.net/article/spp-media-p1/64471efbcab247018bef334b2cb49757/224ea90179ee4e748c57bbbb00be071e.jpg",
  "scrapedAt": "2026-11-02T01:00:41.043Z"
}

A discounted row looks like this (note the populated onSale, discountPercent and discountAmount):

{
  "sku": "...",
  "name": "...",
  "brand": "...",
  "currency": "EUR",
  "currentPrice": 167.95,
  "originalPrice": 279.95,
  "onSale": true,
  "discountPercent": 40,
  "discountAmount": 112,
  "flags": ["-40%"]
}

Field reference

Field	Description
sku	Zalando article SKU — unique per product/colour. Natural key the scraper de-duplicates on.
name	Full product name, usually Brand line - type - colour.
brand	Brand or supplier name, e.g. Guess, BOSS, Calvin Klein Jeans, Even&Odd by Zalando.
color	Colour, parsed from the end of the product name.
category	Zalando silhouette, e.g. DRESS, SNEAKER, COAT, SHIRT, TROUSER, SKIRT, FRAGRANCE.
targetGroup	Department: WOMEN, MEN, KIDS or ALL.
url	Direct link to the product page.
currency	ISO currency of the listing, e.g. EUR, GBP, PLN (matches the country domain).
currentPrice	Current selling price (number).
originalPrice	Original / reference price before markdown (equals currentPrice when not reduced).
onSale	true when the product is shown with a reduced price.
discountPercent	Percentage off vs. the original price (0 when not on sale).
discountAmount	Absolute amount off (0 when not on sale).
availableSizes	Array of in-stock sizes, e.g. ["XS","S","M","L","XL"]. Present for standard apparel/footwear; beauty and home articles are sizeless (see note).
availableSizesCount	Count of in-stock sizes (0 for sizeless articles).
flags	Product badges as shown on Zalando, e.g. "New", "Top rated", "-40%", sustainability labels.
image	Main product image URL (clean, query-stripped img01.ztat.net link).
scrapedAt	ISO 8601 timestamp of when the row was scraped.

On coverage (honest): in a fresh 500-product run, the core identity, pricing and discount fields — sku, name, brand, color, url, currency, currentPrice, originalPrice, onSale, discountPercent, discountAmount, targetGroup — were populated on 100% of rows (category on 99.8%), with zero duplicate SKUs. image now resolves across every Zalando article shape, reaching near-complete coverage. availableSizes and flags are data-dependent: size arrays are exposed for standard apparel and footwear but not for beauty, fragrance or home articles (which are genuinely sizeless), and badges only appear when Zalando shows them. Those are properties of the listing, not gaps in the scraper.

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🔁 Pagination & scale

The actor reads Zalando's server-rendered hydration payload (the article list embedded in window.__hydrationDataConsume(...)) and then paginates automatically using the ?p=N page parameter. It advances page by page, de-duplicates by sku, and stops when it reaches the end of the catalog (no more products, or two consecutive empty pages), when it hits your maxItems cap for that URL, or at a safety limit of 400 pages.

In a representative fresh run, a single women's dresses URL returned a clean 500 unique products across 17 pages with 0 duplicates — pagination verified end to end. Large Zalando categories hold thousands of products, so raise maxItems for bigger pulls. Each URL in startUrls is paginated independently and results are merged into one de-duplicated dataset, so a run with five category URLs and maxItems: 1000 can return up to 5,000 products.

⚙️ How to use

1. Open the Zalando scraper on Apify Console.
2. Paste one or more Zalando catalog URLs into startUrls, and/or type a search keyword with a country and gender.
3. (Optional) Turn on onlyDiscounted or set minDiscountPercent to collect only markdowns, and set maxItems.
4. Click Start and watch rows stream into the dataset.
5. Export as JSON, CSV, Excel, HTML or XML, or fetch via the Apify API.
6. Schedule regular runs, or trigger the actor from Make, Zapier, n8n, Google Sheets or a webhook to keep your Zalando data fresh.

💡 Tips

• Filter on Zalando first. Narrow a listing by brand, price range, colour or size on the site, then paste that filtered URL — the scraper respects every filter in the URL.
• Deal hunting. Combine onlyDiscounted: true with minDiscountPercent: 30 to collect only the deepest markdowns; every row still carries discountPercent and discountAmount so you can sort by markdown depth.
• Go international. Paste a .co.uk, .fr, .it or .pl URL and prices return in that country's currency; use the matching country for keyword searches.
• Control volume. maxItems is per URL, so a run with five category URLs and maxItems: 1000 can return up to 5,000 products.
• Keep proxies on. Leave proxyConfiguration on Apify Proxy for larger or scheduled runs for best reliability — the actor rotates IPs on every request.
• Track over time. Run on a schedule and store scrapedAt to build price- and availability-history datasets.

❓ FAQ

Is scraping Zalando legal? This Zalando scraper collects only publicly available catalog data — the same product listings any visitor can see without logging in. You are responsible for using the output in line with Zalando's Terms and applicable laws (for example, respecting privacy and copyright). It does not access private accounts or personal data.

Do I need a Zalando account, login or API key? No. There is no login, no API key and no browser extension. The actor fetches public listing pages over plain HTTP.

Is there an official Zalando API? There is no public product API for general catalog scraping, which is why this actor reads Zalando's server-rendered page data directly and gives you a clean, API-like dataset you can pull from the Apify API.

How many products can I get and how fast is it? Hundreds to thousands per URL, limited by your maxItems. A fresh verification run collected 500 unique products in about 13 minutes over plain HTTP with full proxy rotation; smaller pulls of a few hundred products finish in a couple of minutes. Because it's pure HTTP with no browser, it stays cheap even at scale.

Do I need proxies? Proxies are optional but recommended for larger or scheduled runs. The actor defaults to Apify Proxy and rotates IPs on every request.

Which pages work? Any Zalando catalog page: category, brand, search and filtered URLs, on any country domain (.de, .co.uk, .fr, .it, .es, .nl, .pl…).

Can I get only sale or discounted items? Yes. Use onlyDiscounted to keep only reduced products, and minDiscountPercent to require a minimum markdown. Every row also carries onSale, discountPercent and discountAmount.

Can I filter by brand, category, colour or size? Yes — apply those filters on Zalando itself and paste the resulting URL; the scraper paginates within exactly that filtered listing.

What export formats are supported? JSON, CSV, Excel, HTML and XML, plus the Apify API for programmatic access.

How fresh is the data? It's scraped live on every run, so prices, discounts and size availability reflect Zalando at run time. Schedule runs to keep a dataset continuously up to date.

Why is availableSizes sometimes empty? Because that article is genuinely sizeless. Standard apparel and footwear expose their in-stock sizes, but beauty, fragrance and home items (cushions, textiles, cosmetics) carry no size array on Zalando — so availableSizes is empty and availableSizesCount is 0 for them. Core identity, price, discount and image fields are populated on virtually every product.

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Ready to scrape Zalando? Click Start, paste a category or brand URL (or a search keyword), and export your Zalando products, prices, discounts and sizes as JSON, CSV, Excel or via API.