We extract product listings, size-level inventory, promotional pricing, and brand catalogues from Nordstrom. 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 Listings objects from nordstrom.com. All fields typed and schema-versioned.
"product_id": "7138492", "brand": "Vince", "title": "Wool & Cashmere Blend Sweater", "price": 345.0, "colour_options": "['Coastal Blue', 'Heather Grey', 'Black']", "size_options": "['XS', 'S', 'M', 'L', 'XL']", "stock_status": "In Stock"
| # | product_id | brand | title | category_tree | price | colour_options |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from nordstrom.com. All fields typed and schema-versioned.
"product_id": "7138492", "base_price": 345.0, "current_price": 276.0, "currency": "USD", "discount_pct": 20, "on_sale": true, "price_timestamp": "2026-05-12T10:14:00Z"
| # | product_id | base_price | current_price | currency | discount_pct | promo_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Fit objects from nordstrom.com. All fields typed and schema-versioned.
"review_id": "REV-982341", "product_id": "7138492", "rating": 4.5, "fit_rating": "True to size", "quality_rating": "Excellent", "date": "2026-04-20"
| # | review_id | product_id | author | rating | fit_rating | length_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Nordstrom scraper handles the complexities of fashion retail data: unrolling complex size-and-colour matrices, parsing fit notes, and tracking flash sales — with JavaScript rendering and anti-bot circumvention built in.
Extract every combination of size, colour, and width. We normalise complex variant grids into flat, queryable records.
Capture base price, markdown price, Anniversary Sale promotions, and percentage discounts — timestamped per crawl.
Track stock availability at the SKU level. Identify low-stock warnings, backorder statuses, and sold-out variants.
Extract fit recommendations, sizing charts, and aggregated customer fit feedback (e.g., 'Runs small, order one size up').
Full review text, star ratings, helpful vote counts, and specific quality/length ratings — paginated across all review pages.
Capture URLs for all product images, swatches, and runway videos, mapped to their respective colour variants.
Brief in. Clean data out.
Provide brand names, category URLs, or specific product IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, US proxy rotation, session management, and Akamai bypass for nordstrom.com.
Schema validation, null-rate checks, variant-mapping verification, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Premium retailers invest heavily in scraping detection and geo-blocking. Here is how we stay resilient — and why teams choose managed infrastructure over DIY.
Nordstrom uses aggressive bot protection that blocks headless browsers and datacenter IPs. Our crawlers use US-based residential ISP proxies with realistic TLS fingerprints, randomised request timing, and full cookie session management to bypass edge challenges.
Nordstrom alters pricing, availability, and catalogue visibility based on the IP region — often blocking non-US traffic entirely. We route all extraction through high-reputation US residential proxies to ensure you receive accurate domestic market data.
Fashion data is inherently nested. A single shoe listing might have 4 colours, 12 sizes, and 3 widths. We execute the necessary JavaScript to expose the full matrix, extracting and flattening every valid SKU combination into a normalised schema.
For large brand catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost, storage bloat, and downstream processing load. You get a clean changelog rather than full re-dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops — and respond before you notice. SLA uptime is contractual, not aspirational.
Retailers and brands track markdown velocity, promotional events, and base pricing across designer catalogues to optimise their own pricing strategies.
Premium brands audit retail partners for Minimum Advertised Price violations and unauthorised discounting during non-promotional periods.
Merchandising teams analyse category depth, brand introduction rates, and colour/style trends to inform seasonal buying decisions.
Analysts track out-of-stock rates at the size and colour level to infer sales velocity and consumer demand for specific designer items.
Machine learning teams use high-resolution product imagery, fabric descriptions, and fit notes to train visual search and recommendation engines.
Product teams aggregate review text and fit feedback (e.g., 'runs small') across thousands of SKUs to improve future manufacturing runs.
"Nordstrom holds the definitive catalogue for premium fashion and beauty retail — but extracting accurate size-level stock data requires navigating aggressive bot mitigation."
Retailers often underestimate the difficulty of scraping high-end fashion sites. Reliable extraction from Nordstrom requires bypassing Akamai edge protection, managing US-only residential proxies, and unrolling complex size-and-colour matrices. DataFlirt manages this infrastructure so your data engineering team receives normalised outputs — not blocked requests.
Everything supported by our nordstrom.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 US-based 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 nordstrom.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Nordstrom is generally permissible under applicable law in the US — reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We use US-based residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and request timing modelled on human behaviour to bypass Akamai edge protection. We monitor for block rate spikes in real time and trigger pool rotation automatically.
Yes. We execute the necessary JavaScript to unroll the entire variant matrix. You receive a structured record for every valid combination of size, colour, and width, including specific stock statuses for each variant.
Pipelines can be configured for daily catalogue refreshes or higher-frequency monitoring for specific high-value brands or promotional periods (e.g., the Anniversary Sale). Diffs are pushed immediately upon run completion.
Our smallest packages start at a defined brand list or category subset with weekly delivery. For full-catalogue extraction or custom schema requirements, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 500 products as part of the pre-engagement scoping process — so you can validate schema fit, variant mapping, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off brand catalogue dump or a continuous price-monitoring feed across 100K SKUs — we scope, build, and operate the pipeline. Tell us what you need.
