We extract SKU-level data, sizing availability, price drops, and fabric compositions from Uniqlo. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Catalogue objects from uniqlo.com. All fields typed and schema-versioned.
"product_id": "453754", "title": "HEATTECH Crew Neck Long Sleeve T-Shirt", "gender": "Men", "category": "Tops", "price": 1490.0, "currency": "INR", "review_rating": 4.6, "review_count": 842, "materials": "39% Polyester, 32% Acrylic, 21% Rayon, 8% Spandex"
| # | product_id | title | gender | category | sub_category | price |
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Complete list of extractable fields for SKU & Inventory objects from uniqlo.com. All fields typed and schema-versioned.
"sku": "453754-09-004-000", "product_id": "453754", "colour_code": "09", "colour_name": "Black", "size": "L", "stock_status": "IN_STOCK", "stock_quantity": 45, "low_stock_warning": false, "timestamp": "2026-05-12T09:14:00Z"
| # | sku | product_id | colour_code | colour_name | size | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from uniqlo.com. All fields typed and schema-versioned.
"product_id": "453754", "base_price": 1990.0, "current_price": 1490.0, "discount_pct": 25, "promo_flag": true, "promo_name": "Limited Offer", "limited_offer_end_date": "2026-05-15T23:59:59Z", "multi_buy_eligible": false
| # | product_id | base_price | current_price | discount_pct | promo_flag | promo_name |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews & Fit Data objects from uniqlo.com. All fields typed and schema-versioned.
"review_id": "REV-9823471", "product_id": "453754", "rating": 5, "title": "Perfect winter base layer", "fit_feedback": "True to size", "length_feedback": "Slightly long", "reviewer_height": "175cm", "date": "2026-04-18"
| # | review_id | product_id | rating | title | body | fit_feedback |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Uniqlo scraper maps the complex product-variant matrix: tracking every size and colour combination, extracting fit feedback, and monitoring regional price variations without triggering anti-bot blocks.
Extract the full matrix of colourways and sizes for every product ID, capturing specific SKU codes and image assets per variant.
Monitor inventory depth, out-of-stock flags, and low-stock warnings at the SKU level across designated regions.
Track base price versus current price, identifying 'Limited Offer' windows and multi-buy promotions.
Extract detailed material compositions (e.g., HEATTECH or AIRism blends) and care instructions directly from the product details.
Parse aggregated review metrics detailing customer sentiment on fit, length, and quality — crucial for return-rate analysis.
Scrape uniqlo.com, uniqlo.com/uk, uniqlo.com/in, and other regional domains to map cross-border pricing and assortment differences.
Brief in. Clean data out.
Provide category URLs, specific product IDs, or target regions. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for uniqlo.com.
Schema validation, null-rate checks, price-outlier detection, and variant matrix mapping before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern apparel sites rely heavily on client-side rendering and edge protection. Here's how we extract data reliably.
Uniqlo utilises strict edge protection and bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to maintain unflagged access.
Uniqlo's frontend relies on dynamic API calls to populate stock and pricing data. We run full Playwright browser sessions to ensure the React-based state hydrates fully before extracting the DOM.
A single Uniqlo product ID can have dozens of SKUs. Our schema specifically iterates through all available colour and size selectors to map the complete inventory matrix, capturing specific stock states for each.
For daily inventory tracking, we maintain a hash index of last-seen stock states per SKU. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes in pricing or sizes, and respond before you notice. SLA uptime is contractual.
Apparel retailers monitor Uniqlo's baseline pricing and markdown cadences to adjust their own promotional calendars.
Merchandisers analyse Uniqlo's category depth and size availability to inform their own stock procurement strategies.
Fashion analysts track the introduction and sell-through rates of specific colourways to validate seasonal trend predictions.
Product development teams scrape material compositions (e.g., HEATTECH ratios) to benchmark their own technical apparel lines.
Pricing teams monitor the duration and depth of Uniqlo's 'Limited Offers' to optimise their own clearance strategies.
Global distributors track price disparities across Uniqlo's regional sites to identify arbitrage or parallel import opportunities.
"Uniqlo's digital catalogue is a masterclass in SKU complexity — tracking stock depth across their colour-size matrix requires a pipeline built specifically for apparel."
Extracting reliable data from modern SPA apparel sites requires residential proxies, full JavaScript execution, and precise handling of variant matrices. DataFlirt manages this complexity, delivering clean SKU-level data so your merchandising team can focus on strategy, not web scraping.
Everything supported by our uniqlo.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, variant switching, and interaction flows.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions to maintain geographical pricing.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About uniqlo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available catalogue and pricing information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product and inventory data. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
Uniqlo frequently prices specific colours or sizes differently (e.g., markdowns on unpopular colours). Our Playwright sessions iterate through the DOM state for every valid colour/size combination, extracting the precise SKU and its specific price point.
Yes. We can configure pipelines to run concurrently across uniqlo.com/us, uniqlo.com/uk, uniqlo.com/in, and others, using region-specific residential proxies to ensure accurate local pricing and stock availability.
For targeted SKU lists, we can configure hourly or sub-hourly polling to detect out-of-stock events. Full category or site-wide refreshes typically run on a daily cadence.
Yes. Alongside standard text reviews, we extract the aggregated and individual slider metrics for fit (Tight to Loose), length (Short to Long), and quality, which are crucial for apparel analysis.
Our minimum engagement typically starts at weekly delivery for a defined category set (e.g., all Men's Tops across two regions). We price based on the frequency of extraction and total SKU volume.
Absolutely. We provide a sample run of up to 200 products (including all associated SKUs) to validate the schema, variant mapping, and data quality before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily dump of the outerwear category or continuous stock-monitoring across 50,000 SKUs — we scope, build, and operate the pipeline. Tell us what you need.
