We extract footwear listings, apparel collections, stock depth per size, pricing signals, and reviews from ugg.com. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 Footwear Listings objects from ugg.com. All fields typed and schema-versioned.
"sku": "1116109-CHE", "title": "Classic Ultra Mini", "category": "Women", "price": 140.0, "currency": "USD", "colour": "Chestnut"
| # | sku | title | category | sub_category | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Stock objects from ugg.com. All fields typed and schema-versioned.
"sku": "1116109-CHE", "price": 140.0, "list_price": 140.0, "discount_pct": 0, "in_stock": true, "available_sizes": "['5', '6', '7', '8', '9']"
| # | sku | price | list_price | discount_pct | in_stock | stock_depth |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Product Reviews objects from ugg.com. All fields typed and schema-versioned.
"review_id": "REV-982341", "sku": "1116109-CHE", "rating": 5, "title": "Perfect for winter", "body": "These are incredibly warm and comfortable.", "verified_buyer": true
| # | review_id | sku | rating | title | body | date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Categories objects from ugg.com. All fields typed and schema-versioned.
"category_id": "women-boots-classic", "name": "Classic Boots", "url": "https://www.ugg.com/women-boots-classic/", "product_count": 42, "season": "AW26", "gender": "Women"
| # | category_id | name | url | parent_category | product_count | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Materials objects from ugg.com. All fields typed and schema-versioned.
"sku": "1116109-CHE", "upper_material": "17mm Twinface sheepskin", "lining_material": "17mm sheepskin", "insole": "17mm UGGplush", "outsole": "Treadlite by UGG", "heel_height": "1.25 inches"
| # | sku | upper_material | lining_material | insole | outsole | heel_height |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Ugg scraper handles every layer of the catalogue: footwear listings, dynamic size availability, colourway mapping, and the review corpus. We manage the JavaScript rendering and proxy rotation automatically.
Extract footwear, apparel, and accessories with complete metadata including descriptions, materials, and high-resolution images.
Map parent products to individual child SKUs based on colour, capturing specific pricing and imagery for each variant.
Monitor inventory availability by exact shoe size or apparel fit. Know exactly when a specific variant drops out of stock.
Capture base price, markdown price, and promotional text across seasonal sales events.
Extract customer reviews, star ratings, and specific fit metrics like 'runs small' or 'true to size'.
Parse detailed material specifications including sheepskin grades, suede types, and proprietary outsole technologies.
Support for ugg.com, ugg.com/uk, ugg.com/eu, and other regional domains to track global pricing parity.
Reconstruct full breadcrumb trails and category trees to categorise products precisely.
Run continuous pipelines that only emit records when price, stock, or new reviews appear.
Brief in. Clean data out.
Provide category URLs or target regions. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for ugg.com.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or BigQuery dataset on agreed cadence.
Modern retail sites use dynamic rendering and bot protection. Here is how we maintain reliable extraction.
Retail sites employ edge protection to block datacenter IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to ensure consistent access.
Ugg loads colourways and size availability dynamically via JavaScript. We run full Playwright browser sessions to trigger these network requests and capture the rendered state.
A single Ugg boot might have 8 colours and 15 sizes, creating 120 unique variants. We map this parent-child hierarchy precisely so you know exactly which SKU is in stock.
We maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing downstream processing load and highlighting exact stock movements.
Every run emits structured logs. We alert on null-rate spikes, schema drift, and coverage drops, fixing selector issues before they impact your data delivery.
Retailers monitor direct-to-consumer pricing and markdown cadence to optimise their own promotional calendars.
Analysts track size-level stock depletion rates to estimate sales velocity for specific styles and colours.
Brand protection teams use official catalogue data as a baseline to identify unauthorised sellers and fake listings.
Fashion researchers analyse new product drops and colourway expansions to forecast seasonal footwear trends.
Product teams mine review text and fit ratings to understand consumer preferences and sizing issues.
Merchandisers analyse category depth and material composition to inform their own buying strategies.
"ugg.com holds critical signals on seasonal fashion trends and premium footwear pricing, but accessing size-level stock data requires custom infrastructure."
Retail scraping demands precise variant mapping. Ugg loads colourways and size availability dynamically via JavaScript. We handle the residential proxy rotation, browser fingerprinting, and payload parsing so your team receives clean, normalised data ready for analysis.
Everything supported by our ugg.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 and deduplication. Playwright handles JavaScript rendering and interaction flows for dynamic product pages.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to prevent blocks.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About ugg.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 data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to bypass edge protection systems reliably.
Yes. Our extraction normalises size data and tracks in-stock status for every individual size variant within a colourway.
We support ugg.com (US), ugg.com/uk, ugg.com/eu, and other regional variants. Pricing and stock are extracted based on the specific locale.
Pipelines can be configured for daily catalogue refreshes or higher-frequency polling for specific high-velocity SKUs to monitor stock depletion.
Our packages start at defined category or SKU lists with weekly delivery. We price based on volume, frequency, and variant complexity. Contact us for a scoped quote.
Yes. We provide a sample run of up to 200 products as part of the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous stock monitoring, we scope, build, and operate the pipeline. Tell us what you need.
