High street & fast fashion

H&M Product Data

Womenswear, Menswear, Shoes, Accessories from hm.com, collected into one H&M dataset you can query, download, or have delivered.

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source specification

Source: hm.com
Segment: High street & fast fashion
Origin: Sweden — founded 1947 in Västerås
Categories: Womenswear, Menswear, Shoes, Accessories
Records: 39,148
Formats: CSV · JSONL · API
Refresh: Daily

about the source

What H&M sells, and how its catalogue behaves

H&M is one of the largest apparel retailers in the world and operates at a scale that makes its catalogue useful as a market-wide index rather than a single competitor view. The assortment spans core basics that persist for years alongside trend pieces with short lifecycles, and the two behave very differently in a price series — which is precisely what makes the source interesting.

why teams track it

H&M as a high-street benchmark

H&M is the volume anchor of the mass market, so its entry price on a category effectively sets the floor everyone else is measured against. Retail analysts use the feed for basket-level price indices, and private-label teams use it to check whether their own margin assumptions still hold as H&M moves.

Visit hm.com

collection method

How we read hm.com

The H&M collector uses H&M's listing API together with the article endpoints that back its product pages, so variant and stock detail arrives structured.

What it captures from H&M

Article-level variants with per-colour codes and imagery
Marked-down price alongside the original list price
Materials and sustainability attributes where H&M publishes them
Availability signals per size where the storefront exposes them

live dataset

39,148 H&M products on record

Full H&M catalogue for the UAE or Saudi Arabia — women, men, kids, baby, home, beauty and sport with local prices, category paths, colours, sizes, materials and images.

39,148

Product records

Fields observed

Daily

Re-crawled

Columns in the current H&M crawl

ageGroupstring · 87% of rows
brandstring
categorystring
categoryPathstring
colorsarray
compositionarray
createdAtdate
currencystring
descriptionstring
discountedPricenumber · 1% of rows
genderstring · 88% of rows
imagesarray
marketplacestring
materialsarray
namestring
nameArstring
pricenumber
productTypestring · 95% of rows
regionstring
sizesarray
skustring
subCategorystring
subSubCategorystring · 81% of rows
updatedAtdate
variantsarray

Run inputs

Region (region)
Which H&M store to pull the catalogue from.
United Arab Emirates · Saudi Arabia

H&M scraper API referenceShopping data overview Use it as training data

related sources

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Massimo Dutti

Spain — Inditex group, Barcelona

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COS

United Kingdom — launched 2007, H&M Group

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A Pointe Etc

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questions

H&M data, answered

Does the feed separate H&M markdowns from list price?

Yes. H&M exposes both the current selling price and the original price on discounted articles, and we carry both through as separate fields rather than collapsing them. That makes discount depth directly computable, which is usually the number pricing teams actually want rather than the sale price on its own.

Can you cover H&M Group brands beyond H&M itself?

We already run dedicated collectors for COS and Arket, both H&M Group labels, and they are delivered on the same schema. Running the group as one combined feed with a brand field is a supported configuration, so you can analyse the portfolio as a whole or split it back out per label.

How many H&M products are in the dataset?

39,148 product records at the latest count. The dataset is re-crawled daily.

How fast does the H&M assortment change?

High-street assortments turn over in weeks, so one snapshot of hm.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 H&M data?

Download the latest H&M crawl from the datasets catalogue as CSV or JSONL, query it through the API under the dataset id "hm", or ask us for a scheduled delivery into your own storage.

Try H&M data first

Download 100 rows from the latest hm.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.