UNIQLO Scraper — Products, Prices, Stock & Reviews

Extract the full UNIQLO product catalog in minutes — names, prices, promotions, colors, sizes, images, ratings, live stock availability, and customer reviews — exported as structured JSON, CSV, or Excel.

Whether you track competitor pricing, monitor inventory, build a fashion dataset, or power a price-comparison app, this UNIQLO scraper turns UNIQLO's online store into clean, ready-to-use data. No login, no browser automation, no flaky page-scraping — just fast, reliable product data from any UNIQLO market.

Why use this UNIQLO scraper?

• 🛍️ Complete catalog — pull every product in a market (≈1,200+ for US) or filter down to exactly what you need.
• 💲 Pricing & promotions — base price, promo price, currency, and merchandising flags (sale, limited-time, new, multibuy).
• 📦 Real-time stock availability — per-size, per-color in-stock status and quantities, so you know what's actually buyable.
• ⭐ Customer reviews — ratings, written reviews, fit feedback, and reviewer details for sentiment and product research.
• 🌍 Any region & language — US, UK, Japan, Germany and more, each in its local language and currency.
• 🔎 Powerful filtering — search by keyword, category, color, size, price range, and promo flag.
• ⚡ Fast & robust — concurrent enrichment and proxy support for large, dependable runs.

Use cases

• Competitor & price monitoring — track UNIQLO prices and discounts over time.
• Inventory & availability tracking — detect stockouts and restocks by size and color.
• Market & assortment research — analyze catalog breadth, categories, and pricing tiers across regions.
• Product reviews & sentiment analysis — mine ratings and fit feedback for insights.
• Dropshipping & retail apps — feed product catalogs into price-comparison or shopping tools.
• Data science & ML — build fashion/apparel datasets for modeling.

What data you get

Per product: product ID, name, gender, currency, base & promo price, average rating and rating count, color list, size list, main image, and a direct product URL. Optionally, per-SKU stock availability and customer reviews (see below).

Input

Configure the run from the Apify Console UI or via JSON.

Field	Type	Description
region	string	Market code, default us (e.g. uk, jp, de).
lang	string	Language code, default en.
query	string	Full-text keyword search.
categoryId	string	Category id (leaf categories only).
colorCodes	array	Filter by color; multiple values combine as OR.
sizeCodes	array	Filter by size; multiple values combine as OR.
flagCodes	array	Promo flags like discount, limitedOffer, salesStart.
priceRanges	array	Price buckets like 10.0-20.0, 80.0-*; multiple = OR.
sort	enum	1 recommended, 2 price ↑, 3 price ↓, 4–6 other.
fetchVariants	boolean	Include per-SKU stock availability (in stock, quantity, status). On by default; turn off for a faster catalog-only run.
fetchReviews	boolean	Include customer reviews per product. Off by default.
maxReviewsPerProduct	integer	Cap reviews per product (default 20, 0 = all).
variantConcurrency	integer	Products enriched in parallel (default 5, max 20).
maxItems	integer	Stop after N products. 0 = entire catalog.
proxyConfiguration	object	Proxy settings (Apify Proxy recommended).

Valid filter values (colors, sizes, flags, price buckets, categories) are self-describing: every result set includes the codes that apply to it, so you can discover and refine filters without guesswork.

Example input

{
  "region": "us",
  "lang": "en",
  "query": "jeans",
  "sort": "2",
  "maxItems": 200,
  "fetchVariants": true,
  "proxyConfiguration": { "useApifyProxy": true }
}

Output

Each product is one dataset record:

{
  "productId": "E492040-000",
  "l1Id": "492040",
  "name": "Ultra Stretch Skinny Fit Jeans",
  "genderName": "WOMEN",
  "priceGroup": "00",
  "currency": "USD",
  "basePrice": 39.9,
  "promoPrice": 29.9,
  "ratingAverage": 4.5,
  "ratingCount": 128,
  "colorCount": 3,
  "colors": ["GRAY", "BLACK", "NATURAL"],
  "sizes": ["S", "M", "L"],
  "mainImage": "https://image.uniqlo.com/...",
  "url": "https://www.uniqlo.com/us/en/products/E492040-000/00",
  "region": "us",
  "lang": "en",
  "scrapedAt": "2026-06-19T..."
}

Stock availability (fetchVariants: true)

Adds variantCount, inStockVariantCount, anyInStock, and a variants array of per-size, per-color availability:

{
  "l2Id": "09731308",
  "colorName": "WHITE",
  "sizeName": "M",
  "statusCode": "IN_STOCK",
  "statusLocalized": "In stock",
  "quantity": 38,
  "inStock": true,
  "backInStock": false
}

Customer reviews (fetchReviews: true)

Adds reviewCount and a reviews array:

{
  "reviewId": 16969537,
  "rate": 5,
  "fit": 3,
  "title": "Comfortable and Flattering",
  "comment": "I love the fit of these shorts...",
  "name": "Summer",
  "gender": "Female",
  "ageRange": "35 to 44 years",
  "location": "California",
  "purchasedSize": "26inch",
  "purchasedColorName": "65 BLUE",
  "helpfulCount": 0,
  "createdAt": "2026-06-..."
}

Export any of this to JSON, CSV, Excel, or XML, or pull it via the Apify API.

Pricing

This actor uses pay-per-event pricing — you only pay for the data you receive:

Event	When charged	Price
Product detail	per product returned	$0.50 / 1,000 products
Availability data	per product enriched with stock availability	$0.50 / 1,000 products
Review	per customer review returned	$0.50 / 1,000 reviews

Events are charged only for successfully delivered data. A catalog-only run (fetchVariants: false, fetchReviews: false) is billed for product details alone; enabling availability and reviews adds those events.

FAQ

Is scraping UNIQLO legal? This actor collects only publicly available product information. As with any web data, review the target site's terms and applicable laws, and use the data responsibly.

Do I need an account or API key for UNIQLO? No. The actor needs no UNIQLO login or credentials.

Which regions are supported? Any UNIQLO market — set region and lang (e.g. us/en, uk/en, jp/ja, de/de).

How do I get only discounted items? Set flagCodes to discount (and/or limitedOffer), optionally combined with a keyword or category.

Can I limit cost while testing? Yes — set maxItems to a small number and turn off fetchVariants/fetchReviews for the cheapest possible run.