We extract product listings, pricing signals, colourway variants, dimensions, and collection mapping from Herschel. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your schedule.
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 herschel.com. All fields typed and schema-versioned.
"sku": "10014-00001-OS", "title": "Little America Backpack", "category": "Backpacks", "collection": "Little America", "price": 109.0, "currency": "USD", "in_stock": true, "url": "https://herschel.com/shop/backpacks/little-america-backpack"
| # | sku | title | category | collection | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variants & Colourways objects from herschel.com. All fields typed and schema-versioned.
"parent_sku": "10014", "variant_sku": "10014-00007-OS", "colour_name": "Navy", "size": "OS", "price": 109.0, "in_stock": true, "variant_url": "https://herschel.com/shop/backpacks/little-america-backpack?v=10014-00007-OS"
| # | parent_sku | variant_sku | colour_name | colour_hex | size | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from herschel.com. All fields typed and schema-versioned.
"sku": "10014-00001-OS", "region": "US", "price": 109.0, "compare_at_price": 109.0, "currency": "USD", "in_stock": true, "scraped_at": "2023-10-24T08:12:00Z"
| # | sku | region | price | compare_at_price | discount_pct | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Technical Specs objects from herschel.com. All fields typed and schema-versioned.
"sku": "10014-00001-OS", "volume_litres": 25.0, "height_cm": 48.9, "width_cm": 28.6, "depth_cm": 17.8, "material": "EcoSystem 600D Fabric", "laptop_sleeve_size": "15-inch", "water_resistant": true
| # | sku | volume_litres | height_cm | width_cm | depth_cm | material |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Structure objects from herschel.com. All fields typed and schema-versioned.
"breadcrumb_1": "Home", "breadcrumb_2": "Shop", "collection_name": "Heritage", "category_url": "https://herschel.com/shop/collections/heritage", "product_count": 42, "scraped_at": "2023-10-24T08:15:00Z"
| # | breadcrumb_1 | breadcrumb_2 | breadcrumb_3 | collection_name | category_url | product_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Herschel scraper handles dynamic inventory states, variant hydration, regional pricing, and anti-bot circumvention to deliver clean retail intelligence.
Title, description, category, and collection mapping for every bag, luggage piece, and accessory.
Capture pricing across different geographical regions to monitor global parity and regional discounts.
Extract every colour variant linked to a parent SKU, including limited edition patterns and collaborations.
Structure physical specifications including height, width, depth, and volume in litres for accurate comparison.
Monitor in-stock and out-of-stock indicators at the variant level across the entire catalogue.
Extract URLs for all product images, lifestyle shots, and detail views for visual intelligence.
Map products to specific collections like Little America, Heritage, or Novel to analyse merchandising strategy.
Capture 'Frequently Bought Together' and recommended product algorithms directly from the product page.
Run daily or weekly extraction pipelines to track catalogue changes and stockout velocities.
Brief in. Clean data out.
Provide target categories, collections, or specific regions. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for herschel.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 headless commerce sites invest in bot mitigation. Here is how we maintain reliable access.
Commerce platforms utilise edge protection to block automated traffic. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass these filters.
Herschel relies on frontend frameworks to load pricing and inventory state dynamically. We run full Playwright browser sessions to execute JavaScript and capture data that headless HTTP clients miss entirely.
Frontend structures change during promotional events. Our selector strategy uses fallback chains including CSS, XPath, and JSON state extraction to ensure a layout change does not break your data pipeline.
For daily catalogue tracking, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes and coverage drops, responding before you notice.
Retailers monitor Herschel pricing and discount strategies across different regions to inform their own pricing models.
Merchandising teams analyse colourway breadth, collection depth, and product lifecycle to optimise their own inventory.
Computer vision models ingest high-resolution bag imagery and lifestyle shots to train product recognition algorithms.
Distributors verify regional pricing against Minimum Advertised Price agreements to enforce brand guidelines.
Analysts track new product launches, material changes, and category expansion to measure market trends.
Supply chain teams monitor stockout patterns on high-velocity SKUs to estimate production volumes and demand.
"Herschel manages a complex matrix of collections, volumes, and colourways. Extracting this requires a pipeline that understands variant structures, not just flat HTML."
Most teams underestimate the complexity of modern headless commerce builds. Reliable Herschel scraping requires residential proxies, full JavaScript execution to hydrate variant prices, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on analysis.
Everything supported by our herschel.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.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About herschel.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product 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, and request timing modelled on human behaviour. We monitor for rate limits in real time and trigger pool rotation automatically.
Yes. We can configure the pipeline to target specific geographic regions to capture localised pricing, currency, and availability.
Full catalogue refreshes can be scheduled daily or weekly. The time required depends on the total SKU count and target regions.
Yes. Our schema captures the parent-child relationship, ensuring every colour and size variant is linked correctly to the main product record.
Yes. We provide a sample run during the scoping process so you can validate schema fit, field completeness, 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 catalogue export or a continuous pricing feed across multiple regions. Tell us what you need.
