We extract product listings, sizing grids, material specifications, pricing, and reviews from Dr. Martens. 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 drmartens.com. All fields typed and schema-versioned.
"product_id": "11822006", "title": "1460 Smooth Leather Lace Up Boots", "category": "Womens", "sub_category": "Boots", "price": 170.0, "currency": "GBP", "colours": "['Black', 'Cherry Red']", "materials": "Smooth Leather"
| # | product_id | title | category | sub_category | price | currency |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Variants & Sizing objects from drmartens.com. All fields typed and schema-versioned.
"parent_id": "11822006", "sku": "11822006-UK8", "size_uk": "8", "size_us_men": "9", "size_us_women": "10", "size_eu": "42", "in_stock": true, "colour": "Black"
| # | parent_id | sku | size_uk | size_us_men | size_us_women | size_eu |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews objects from drmartens.com. All fields typed and schema-versioned.
"review_id": "REV-98234", "product_id": "11822006", "rating": 5, "title": "Classic for a reason", "verified_buyer": true, "fit_rating": "True to size", "comfort_rating": 4, "date": "2023-10-14"
| # | review_id | product_id | author | rating | title | body |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing objects from drmartens.com. All fields typed and schema-versioned.
"sku": "11822006-UK8", "price": 170.0, "list_price": 170.0, "discount_pct": 0, "currency": "GBP", "region": "UK", "on_sale": false, "scraped_at": "2023-10-25T14:30:00Z"
| # | sku | price | list_price | discount_pct | currency | region |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Materials & Care objects from drmartens.com. All fields typed and schema-versioned.
"product_id": "11822006", "leather_type": "Smooth", "finish": "Matte", "construction_method": "Goodyear Welted", "vegan_certified": false, "sole_material": "PVC", "care_instructions": "Clean away dirt using a damp cloth and allow to dry."
| # | product_id | leather_type | finish | care_instructions | construction_method | made_in |
|---|---|---|---|---|---|---|
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Our Dr. Martens scraper extracts the full catalogue, mapping complex sizing grids, tracking regional stock levels, and parsing material specifications with high precision.
Extract boots, shoes, sandals, and accessories with complete metadata including titles, descriptions, and category hierarchies.
Map UK, US, and EU sizing variants accurately. Track availability status for every size and colour combination.
Monitor inventory levels across different regional storefronts to identify supply chain patterns.
Parse detailed product specifications including leather type, construction method, and sole material.
Collect customer feedback, star ratings, and specific fit and comfort metrics to inform product development.
Identify and track vegan-certified products and synthetic material alternatives across the catalogue.
Extract localised pricing and product availability from UK, US, EU, and other regional domains.
Run targeted pipelines to monitor fast-moving inventory and limited-edition collaborations.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences.
Brief in. Clean data out.
Provide category URLs, specific collections, or regions. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for drmartens.com.
Schema validation, null-rate checks, and sample data reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
E-commerce platforms deploy strict bot protection and complex frontend frameworks. Here is how we maintain data integrity.
E-commerce sites use advanced bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass blocks.
Product availability and sizing options are often rendered dynamically. We run full Playwright browser sessions to trigger lazy-loading and hydrate variant data.
Frontend layouts change frequently. Our selector strategy uses multiple fallback chains so a minor DOM update does not break your data feed.
We maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs. We alert on null-rate spikes and schema drift, responding before you notice missing data.
Retailers monitor direct-to-consumer pricing strategies, discount cadences, and seasonal sale events.
Merchandising teams analyse product mix, colour variations, and sizing availability to optimise their own inventory.
Supply chain analysts track the ratio of leather to synthetic materials to forecast industry material trends.
Product teams mine customer feedback on fit, comfort, and durability to inform future designs.
Analysts track out-of-stock rates across specific sizes to estimate demand velocity.
Brands monitor product descriptions and marketing copy to ensure consistency across retail partners.
"Dr. Martens maintains a highly structured footwear catalogue with complex sizing grids and material specifications - extracting this requires a pipeline built for dynamic variant mapping."
Most teams underestimate the investment required: reliable e-commerce scraping requires residential proxies, full JavaScript rendering for sizing grids, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our drmartens.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 retry logic. Playwright handles JavaScript rendering and interaction flows for complex frontend components.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to maintain regional context.
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 drmartens.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 user data or circumvent authentication walls.
We use headless browsers via Playwright to interact with the page, triggering the JavaScript events required to load availability data for every size and colour combination.
Yes. We route requests through region-specific residential proxies to load localised storefronts, capturing accurate pricing and stock data for specific markets.
Pipelines can be configured to run daily for full catalogue refreshes, or at higher frequencies for specific high-priority SKUs or limited-edition releases.
Yes. We parse the product description and specification sections to structure data points like leather type, sole material, and construction method.
Our minimum engagement typically covers a specific category or regional storefront delivered weekly. Contact us for a scoped quote based on your volume requirements.
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 build and operate the pipeline. Tell us what you need.
