We extract apparel listings, Worn Wear used inventory, material compositions, Footprint Chronicles data, and pricing signals from Patagonia. 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 Main Apparel objects from patagonia.com. All fields typed and schema-versioned.
"sku": "84212", "title": "Men's Nano Puff® Jacket", "category": "Mens", "sub_category": "Jackets & Vests", "price": 239.0, "currency": "USD", "available_colours": "['Black', 'Forge Grey', 'Nouveau Green']", "weight_grams": 337
| # | sku | title | category | sub_category | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Worn Wear objects from patagonia.com. All fields typed and schema-versioned.
"worn_wear_id": "WW-84212-M-BLK", "original_sku": "84212", "condition_grade": "Excellent", "price": 119.0, "original_price": 239.0, "year_made": 2021, "flaws_noted": "None", "in_stock": true
| # | worn_wear_id | original_sku | title | condition_grade | condition_description | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Materials & ESG objects from patagonia.com. All fields typed and schema-versioned.
"sku": "84212", "recycled_pct": 100, "fair_trade_certified": true, "bluesign_approved": true, "fabric_composition": "1.4-oz 20-denier 100% recycled polyester ripstop", "insulation_type": "60-g PrimaLoft Gold Insulation Eco", "origin_country": "Vietnam", "factory_name": "Pungkook Corporation"
| # | sku | recycled_pct | fair_trade_certified | bluesign_approved | fabric_composition | insulation_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from patagonia.com. All fields typed and schema-versioned.
"review_id": "REV-992144", "sku": "84212", "rating": 5, "fit_slider_value": "True to size", "review_title": "Perfect for layering", "primary_use": "Everyday Wear", "date_posted": "2023-11-12", "helpful_votes": 14
| # | review_id | sku | reviewer_nickname | rating | fit_slider_value | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category & SERP objects from patagonia.com. All fields typed and schema-versioned.
"category_id": "mens-jackets-vests", "position": 1, "sku": "84212", "title": "Men's Nano Puff® Jacket", "price": 239.0, "badge_text": "Bestseller", "colour_count": 8, "scraped_at": "2023-11-14T08:12:00Z"
| # | category_id | keyword | position | sku | title | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the complexities of Patagonia's Salesforce Commerce Cloud backend, dynamic Worn Wear inventory, and nested material composition data.
Title, price, descriptions, fit matrices, and weight specifications extracted across all primary categories and sub-categories.
Monitor used inventory drops, condition grades, and secondary market pricing across the Worn Wear platform.
Extract recycled material percentages, Fair Trade certifications, and Footprint Chronicles factory origin data per SKU.
Map every available size and colour combination, including out-of-stock variants and seasonal colour additions.
Capture text reviews, star ratings, and the critical customer fit slider (runs small/large) for product analysis.
Track discount percentages, Web Specials inventory, and historical price changes across the catalogue.
Support for patagonia.com, eu.patagonia.com, and regional variants for global pricing comparisons.
High-resolution product imagery and technical diagram URLs captured and delivered alongside metadata.
Receive only changed records on subsequent runs. Track new product launches and discontinued items automatically.
Brief in. Clean data out.
Specify target categories, Worn Wear segments, or specific data points like material composition and factory origins.
We configure crawlers to handle Demandware pagination, dynamic inventory endpoints, and rate limits.
Schema validation, null-rate checks on nested material tags, and price-outlier detection before production.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting structured data from modern headless commerce platforms requires specific infrastructure. Here is how we maintain pipeline stability.
Patagonia uses Salesforce Commerce Cloud. Instead of parsing complex DOM trees for inventory, we intercept the underlying JSON API responses for accurate, real-time stock and pricing data across all colourways.
Worn Wear inventory is highly dynamic with single-SKU items dropping frequently. We utilise high-frequency polling on specific category endpoints to capture items before they sell out.
Aggressive crawling triggers Akamai edge blocks. We distribute requests across our residential proxy network and pace page loads to mimic organic browsing patterns.
Material compositions and factory origin data are deeply nested within product pages. Our extraction logic normalises these fields into flat, queryable columns for your data warehouse.
To capture accurate EU vs US pricing, we maintain isolated browser sessions with region-specific cookies and exit nodes, preventing currency redirect loops.
Apparel brands analyse Patagonia's material compositions, recycled percentages, and factory disclosures to benchmark their own sustainability initiatives.
Retail strategists track Worn Wear pricing models and inventory velocity to understand the economics of brand-owned resale platforms.
Outdoor brands monitor Web Specials and seasonal discount depth to optimise their own promotional calendars.
Merchandisers track colourway availability and size-run depth to identify trending styles in the outdoor apparel sector.
Analysts map the Footprint Chronicles data to understand global textile sourcing and manufacturing dependencies.
Design teams mine customer reviews and fit-slider data to identify common design flaws or sizing issues in technical outerwear.
"Patagonia's catalogue is the industry benchmark for sustainable material sourcing and circular economy pricing — but it requires a pipeline to analyse at scale."
Most teams underestimate the investment required: reliable Patagonia scraping requires handling Demandware endpoints, Worn Wear's dynamic inventory, and nested size-colour matrices. DataFlirt absorbs that complexity so your engineers focus on analysis.
Everything supported by our patagonia.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, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 patagonia.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We track the Worn Wear subdomain, extracting unique item IDs, condition grades, pricing, and specific noted flaws. This requires distinct pipeline logic from the main apparel catalogue due to the single-SKU nature of used inventory.
Yes. We extract the material composition text, recycled percentages, and binary flags for certifications like Fair Trade and Bluesign, as well as factory origin data from the Footprint Chronicles.
For the main catalogue, we typically run daily diffs. For high-velocity segments like Worn Wear or Web Specials, we can configure hourly polling pipelines to capture inventory before it sells out.
Yes. We can extract from patagonia.com, eu.patagonia.com, and other regional variants. We use geo-located proxies to ensure accurate local pricing and prevent forced currency redirects.
Yes. We map the entire size and colourway matrix for each product, recording null or false availability flags for variants that are currently out of stock.
We deliver structured JSON, CSV, or Parquet files directly to your AWS S3 bucket, Google Cloud Storage, or data warehouse (BigQuery/Snowflake) on a schedule.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue extract or continuous monitoring of Worn Wear inventory — we scope, build, and operate the pipeline. Tell us what you need.
