Zalando Data Scraping Services

Country is a dimension, not a setting

Zalando operates separate storefronts per country, and they diverge on the things that matter commercially.

• Price differs by market. The same article carries different prices in Germany, Poland and Sweden, and the gaps are strategic rather than incidental.
• Assortment differs. A brand or article ranged in one storefront may be absent from another entirely.
• Markdown timing differs. Sale periods and depth are set per market, so a single-market view misreads the cadence.
• Tax display differs. Prices are shown inclusive of local VAT at local rates, so a raw cross-country comparison is invalid before normalisation.
• Currency differs. Euro, złoty, krona, koruna — and converting silently at an undocumented rate corrupts the comparison.

Every record carries storefront_country, the price in local currency, and the tax basis. Where you need a converted view we supply the daily rate as a separate field rather than baking it in, so the conversion is auditable.

Partner Programme sellers on the same product pages

Zalando runs a marketplace alongside its wholesale business. Partner Programme sellers list on the same article pages as Zalando's own stock, and the commercial meaning is different.

• Zalando's own stock reflects wholesale buying and Zalando's own markdown decisions. That is what a brand's trading team negotiates against.
• A Partner Programme seller's stock is a third party pricing independently. For a brand, that is a channel and price integrity question, not a wholesale one.
• Both can be present simultaneously on the same article at different prices and different size availability.

We capture seller_type and the seller name where displayed, plus which offer held the default position. For brands, this is frequently the field that reveals partners discounting their articles below the agreed wholesale-driven price — and it is invisible in a dataset that reports one price per article.

Size curves, because fashion sells by size

Zalando publishes size-level availability, and in fashion that is the field that tells you what is actually selling.

An article at full price with only the largest size remaining has sold out of everything that mattered. Article-level data reports it as in stock and not discounted, which is the opposite conclusion. We capture the full size curve with size_curve_broken and core_sizes_oos flags derived per category and market.

Size systems are normalised across EU, UK and alpha sizing with the original retained, and footwear handled on its own scales. Where an article's sizes return to stock after disappearing, that indicates a repeat order — the strongest public signal that a line is working, and only visible with continuous size-level history.

Markdown events are joined to size curve state at each step, so a markdown on a full curve reads as a genuine slow seller and a markdown on a broken curve reads as tail clearance. Same depth, opposite meaning.