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High street & fast fashion

Zara Product Data

Womenswear, Menswear, Shoes, Bags, Accessories from zara.com, collected into one Zara dataset you can query, download, or have delivered.

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source specification

Source
zara.com
Segment
High street & fast fashion
Origin
Spain — founded 1975 in A Coruña
Categories
Womenswear, Menswear, Shoes, Bags, Accessories
Records
4,484
Formats
CSV · JSONL · API
Refresh
Daily

about the source

What Zara sells, and how its catalogue behaves

Zara is the flagship chain of Inditex and the reference point for the whole fast-fashion category. Its buying model turns new styles around in weeks rather than seasons, which means the catalogue on zara.com is one of the fastest-moving in retail: colourways appear, sell through, and disappear inside a single month. A snapshot taken today and a snapshot taken three weeks from now describe substantially different assortments.

why teams track it

Zara as a high-street benchmark

Because Zara sets the pace, its assortment is the benchmark competitors trend-map against. Merchandising teams use the feed to see which silhouettes and colour stories get scaled, pricing teams use it to position their own entry price points, and trend forecasters use the drop cadence itself as a leading signal for the rest of the high street.

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collection method

How we read zara.com

The Zara collector uses Zara's own category and product JSON endpoints, read through the storefront's internal ajax layer rather than by parsing rendered HTML.

What it captures from Zara

  • Per-colourway product variants with their own image sets
  • Composition and care text extracted from the product detail payload
  • Category and subcategory path as Zara itself classifies the item
  • Full-size price history when the feed is collected on a schedule

live dataset

4,484 Zara products on record

Product catalogue from Zara — names, prices, colours, materials and images.

4,484

Product records

15

Fields observed

Daily

Re-crawled

Columns in the current Zara crawl

  • brandstring
  • categorystring
  • colorsarray
  • createdAtdate
  • currencystring
  • descriptionstring
  • discountedPricenumber · 2% of rows
  • imagesarray
  • marketplacestring
  • materialsarray
  • namestring
  • pricenumber
  • subCategorystring
  • subSubCategorystring · 98% of rows
  • updatedAtdate

Run inputs

None. The Zara dataset is filled by a scheduled crawl of zara.com, not by per-request runs.

questions

Zara data, answered

Which Zara region and language does the feed cover?
The default collector runs against the US English storefront, which carries USD pricing and the US assortment. Zara localises both catalogue and price by market, so if you need EU, UK, or APAC pricing we run a separate collection per locale and return them as distinct feeds you can join on product reference. Adding locales is part of standard onboarding rather than a custom build.
How quickly do new Zara drops appear in the data?
That is set by the refresh cadence you choose rather than by any limit on our side. Teams tracking drop velocity typically run Zara daily, which is enough to catch a style within a day of it going live. Slower cadences still capture the assortment accurately, they just blur the exact moment a product landed.
How many Zara products are in the dataset?
4,484 product records at the latest count. The dataset is re-crawled daily.
How fast does the Zara assortment change?
High-street assortments turn over in weeks, so one snapshot of zara.com goes stale quickly. The dataset is re-crawled on a schedule and recent runs are kept as dated snapshots, so arrivals, sell-outs, and price moves show up as differences between runs.
How do I get Zara data?
Download the latest Zara crawl from the datasets catalogue as CSV or JSONL, query it through the API under the dataset id "zara", or ask us for a scheduled delivery into your own storage.

Try Zara data first

Download 100 rows from the latest zara.com crawl and check them against your own numbers before committing.

Talk to an engineer

Explore collected catalogue fields and discuss your data requirements — how we work.

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