We extract product listings, pricing signals, size-level availability, brand intelligence, partner programme data, reviews, and category rankings from Zalando. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from zalando.com. All fields typed and schema-versioned.
"article_id": "NI114D08N-Q11", "brand_name": "Nike", "product_name": "AIR MAX 90 — Trainers", "category": "Trainers", "price": 109.95, "currency": "EUR", "discount_pct": 0, "rating": 4.3, "review_count": 6182, "is_zalando_sustainable": false, "free_returns": true
| # | article_id | sku_id | brand_name | product_name | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Sales objects from zalando.com. All fields typed and schema-versioned.
"article_id": "NI114D08N-Q11", "price": 109.95, "original_price": 139.95, "discount_pct": 21, "is_sale": true, "zalando_plus_price": 104.45, "size_stock_status": "EU 44 → in_stock", "price_timestamp": "2026-05-12T08:00:00Z"
| # | article_id | sku_id | price | original_price | discount_pct | is_sale |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from zalando.com. All fields typed and schema-versioned.
"review_id": "rv_zal_8840291", "article_id": "NI114D08N-Q11", "star_rating": 4, "verified_purchase": true, "review_title": "Classic silhouette, great comfort", "fit_feedback": "true_to_size", "size_purchased": "EU 44", "review_date": "2026-05-03"
| # | review_id | article_id | reviewer_name | verified_purchase | star_rating | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Brand & Category Intel objects from zalando.com. All fields typed and schema-versioned.
"brand_id": "NI114", "brand_name": "Nike", "partner_programme": "partner", "total_products": 3841, "avg_price": 79.90, "avg_discount_pct": 14, "sustainable_product_pct": 31, "scraped_at": "2026-05-12T09:00:00Z"
| # | brand_id | brand_name | brand_url | partner_programme | total_products | avg_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Zalando scraper covers every layer of Europe's largest fashion platform: product catalogues, size-level availability, sale and markdown events, brand partner intelligence, sustainability labels, and the review corpus — across all major European markets.
Product name, brand, category, material composition, care instructions, sustainability labels, delivery promise, and every metadata field Zalando surfaces — at SKU level with full size and colour variant mapping.
Capture full price, sale price, Zalando Plus pricing, markdown depth, and sale event timestamps — per article and per size. Track the entire summer and winter sale cycle.
Per-size availability status per article on every crawl. Detect restock events, size sellouts, and low-stock signals in near real-time.
Full review text, star ratings, fit feedback, size purchased, helpful votes, and country of reviewer — paginated across all review pages.
Zalando Sustainable label, material certifications, and pre-owned item flags captured per SKU — for ESG reporting, sustainability benchmarking, and compliance datasets.
All products per brand with partner programme tier, average pricing, average discount depth, new arrival velocity, and category rank — track brand health across the Zalando ecosystem.
zalando.de, zalando.co.uk, zalando.fr, zalando.it, zalando.es, zalando.nl, zalando.pl, zalando.se, zalando.be and 16 more markets — unified schema with country-normalised pricing.
Track organic position and featured placement for any keyword or category across any Zalando market — with new-arrival and sale-item badge capture.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide brand lists, category URLs, or article ID sets across your target Zalando markets. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and anti-bot handling per Zalando market.
Schema validation, null-rate checks, size-stock accuracy checks, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Zalando uses sophisticated bot mitigation across its 25+ European markets. Here's how we stay resilient — and why teams choose managed infrastructure over DIY.
Zalando's bot detection operates on TLS fingerprints, browser headers, and behavioural signals across all European markets. Our crawlers use country-matched residential ISP proxies with realistic fingerprints and randomised timing — appearing as genuine in-country consumer traffic.
Zalando product pages, size selectors, and review sections are heavily JavaScript-rendered. We run full Playwright sessions with scroll simulation and tab interaction — capturing size availability and review data that HTTP clients miss entirely.
Zalando maintains separate frontend codebases per market that evolve independently. Our per-market selector strategy uses CSS, XPath, text-pattern matching, and structured data extraction as fallback layers — so a regional DOM update doesn't break your feed.
For large article catalogues across multiple markets, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and storage. Size-stock changes and sale events generate targeted updates.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops across every market — and respond before you notice. SLA uptime is contractual, not aspirational.
Fashion brands and wholesale buyers monitor Zalando sale cycles, markdown depths, and Zalando Plus pricing to benchmark their own pricing and plan markdown strategies.
Brand managers track their own and competitor portfolios on Zalando — product count, review velocity, average rating, and category rank across markets.
Buyers and merchandisers analyse category saturation, average price points, and new arrival velocity across Zalando's 25+ markets to identify whitespace and regional trends.
ML teams use Zalando product and review datasets to train fashion recommendation engines, visual similarity models, and attribute classifiers.
ESG analysts and sustainability teams track Zalando Sustainable label adoption, material certification coverage, and pre-owned product share across brand portfolios.
PE firms and analysts track brand portfolio growth, average selling prices, and review velocity to evaluate European fashion platform dynamics.
"Zalando is Europe's largest fashion platform — spanning 25+ markets, 6,000+ brands, and 700M+ product visits per month. That scale of pricing and availability signal is only useful if you can query it."
Scraping Zalando reliably across European markets requires country-matched residential proxies, full JavaScript rendering, per-market selector maintenance, and GDPR-aware data handling. DataFlirt absorbs all of that so your analysts can focus on the European fashion intelligence — not the infrastructure.
Everything supported by our zalando.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, size-selector interaction, and review pagination. Per-market configurations managed via scrapy-playwright middleware.
We maintain country-matched pools of residential ISP proxies across DE/UK/FR/IT/ES and 20+ additional EU regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting across all active Zalando markets. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About zalando.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Zalando is generally permissible under applicable EU and UK law — consistent with the hiQ v. LinkedIn ruling and similar precedents. DataFlirt targets only public, non-authenticated product, pricing, and review data. We operate with GDPR-aware data handling and do not extract personal data or circumvent authentication walls. We recommend clients review Zalando's ToS independently and consult legal counsel for specific use cases.
We use country-matched residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our per-market selectors have multi-layer fallback chains. We monitor for block-rate spikes in real time and trigger pool rotation or solver queues automatically.
We support all 25+ Zalando national storefronts including .de, .co.uk, .fr, .it, .es, .nl, .pl, .se, .be, .at, .ch, .dk, .fi, .no, .cz, .ro, .sk, .si, .lt, .lv, .ee, .ie, .pt, .hu, and .gr — from a unified schema with market-normalised pricing.
Each record includes both the local currency price and a currency code field. We normalise across EUR, GBP, PLN, SEK, DKK, CHF, NOK, and CZK — making cross-market pricing analysis straightforward without manual currency conversion.
Yes. Our pipeline captures per-size availability per market on every crawl. You can configure high-cadence monitoring on a defined article set across multiple Zalando markets to detect regional availability differences, restock events, and size depletion patterns.
Yes. We capture the Zalando Sustainable badge, material certifications (e.g. GOTS, Oeko-Tex), recycled material flags, and pre-owned item identifiers per SKU. This data is increasingly critical for ESG reporting and retail sustainability benchmarking.
Our smallest packages start at a defined article list or brand set (typically 2,000–20,000 articles) across one to three markets with weekly delivery. For larger multi-market catalogues or sale-event monitoring, we price based on volume and cadence. Contact us for a scoped quote.
Absolutely. We provide a sample run of up to 500 articles — including size availability and review data across your target markets — as part of the pre-engagement scoping process, so you can validate schema fit and field completeness before signing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off European catalogue snapshot or a continuous sale-monitoring feed across 25 markets — we scope, build, and operate the pipeline. Tell us what you need.
