H&M is one of the world’s largest fashion retailers, operating in more than 70 markets with a catalog spanning clothing, accessories, beauty, and home. The H&M API gives you structured access to that catalog: product search, live pricing across markets, store locations, category browsing, and supplier information.
What the H&M API covers
Product search - keyword search across H&M’s global catalog. Filter by category, gender (women, men, kids), age group, and market. Returns product name, price, currency, sale indicator, and product URL.
Category browsing - H&M’s category hierarchy from top-level departments (women, men, kids, home) down to sub-categories (jackets, dresses, accessories). Useful for systematic catalog ingestion and for building browse-style UIs.
Product details - the full product record per SKU:
- Name and description
- Brand (H&M, H&M Home, COS, Arket, and others within the group)
- Category path
- Current price and sale price (where applicable)
- Available colors with color names and image URLs
- Available sizes and size guide
- Materials composition (e.g. “100% cotton”, “80% polyester, 20% elastane”)
- Care instructions
- Product images per color
Store locator - H&M store locations by country and city. Returns store name, address, coordinates, opening hours, and available services (click and collect, alterations).
Supplier details - H&M’s published supply chain data linked to product categories. Includes supplier facility name, country of manufacture, and compliance status. Useful for supply chain transparency products and ESG analysis.
Search autocomplete - term suggestions for search-as-you-type functionality.
Multi-market pricing
H&M prices the same product differently across markets. Querying the API with a specific market code returns prices in local currency for that market. This makes cross-market price analysis straightforward - query the same product ID across different market codes and compare.
const markets = ['GB', 'US', 'SE', 'DE', 'FR'];
const productId = '0992849001';
const prices = await Promise.all(
markets.map(async (market) => {
const res = await fetch(
`https://h-m-hennes-mauritz1.p.rapidapi.com/products/${productId}?market=${market}`,
{
headers: {
'X-RapidAPI-Key': process.env.RAPIDAPI_KEY,
'X-RapidAPI-Host': 'h-m-hennes-mauritz1.p.rapidapi.com',
},
}
);
const data = await res.json();
return { market, price: data.price, currency: data.currency };
})
);
// prices = [{ market: 'GB', price: 24.99, currency: 'GBP' }, ...]For cross-border grey market analysis, this pattern is the foundation.
Use cases
Price monitoring - H&M runs frequent promotional events: seasonal sales, member-price weekdays, and category-specific markdowns. Monitoring a set of products for price drops is straightforward with the API and a simple polling loop.
Affiliate feed management - affiliate product feeds need current prices and availability. Fashion feeds go stale fast as prices change and sizes sell out. The H&M API keeps your feed accurate.
Fashion catalog ingestion - for comparison sites, style apps, or outfit recommendation tools that include H&M as a retailer source, the category browsing and product detail endpoints give you the full catalog.
Competitor price analysis - if you are a fashion brand or retailer, tracking H&M’s pricing on comparable product types helps you position your own pricing and monitor promotional intensity.
Supply chain transparency - the supplier data is uncommon in retail APIs. For ESG reporting products, responsible sourcing tools, or supply chain intelligence platforms, H&M’s published supplier information is a useful signal.
Multi-market retail intelligence - H&M’s global presence makes it useful as a benchmark for retail pricing across markets. A product that tracks H&M prices across regions can surface anomalies and cross-border arbitrage opportunities.
Kohl’s as a complement
For the US market, the Kohl’s Data API covers a different US retail segment - department store with strong private label and national brands. Pair H&M for global fashion with Kohl’s for US department store depth.
