We extract product listings, colourway variations, size-level inventory flags, and promotional pricing from Boden. 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 Metadata objects from boden.co.uk. All fields typed and schema-versioned.
"product_id": "W0842", "title": "Cashmere Crew Neck Jumper", "category": "Womens", "base_price": 130.0, "currency": "GBP", "fabric_composition": "100% cashmere", "page_url": "https://www.boden.co.uk/en-gb/cashmere-crew-neck-jumper/sty-w0842"
| # | product_id | title | category | sub_category | base_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Inventory & Sizes objects from boden.co.uk. All fields typed and schema-versioned.
"sku": "W0842-NAV-12", "colourway": "Navy", "size": "12", "stock_status": "in_stock", "low_stock_warning": false, "current_price": 130.0
| # | sku | parent_id | colourway | size | stock_status | low_stock_warning |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from boden.co.uk. All fields typed and schema-versioned.
"sku": "W0842-PNK-10", "base_price": 130.0, "sale_price": 91.0, "discount_pct": 30, "clearance_flag": true, "timestamp": "2026-10-04T08:12:00Z"
| # | sku | base_price | sale_price | discount_pct | promo_eligible | clearance_flag |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from boden.co.uk. All fields typed and schema-versioned.
"review_id": "REV-992841", "rating": 5, "title": "Perfect everyday jumper", "body": "Soft, true to size, and washes well on a delicate cycle.", "fit_rating": "True to size", "date": "2026-09-15"
| # | review_id | sku | rating | title | body | fit_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Media & Assets objects from boden.co.uk. All fields typed and schema-versioned.
"sku": "W0842-NAV", "colourway": "Navy", "primary_image_url": "https://boden.co.uk/media/w0842_nav_main.jpg", "swatch_url": "https://boden.co.uk/media/w0842_nav_swatch.jpg", "model_height": "5ft 9in", "model_size": "UK 10"
| # | sku | colourway | primary_image_url | gallery_urls | video_url | swatch_url |
|---|---|---|---|---|---|---|
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Our Boden scraper handles every layer of the retail platform: product grids, dynamic size availability, promotional overlays, and customer reviews - with JavaScript rendering and session management built in.
Title, category, fabric composition, care instructions, and fit notes - scraped at the parent product level.
Parent to child ASIN-style relationships mapping every colourway and pattern variation to its base product.
Capture in-stock, out-of-stock, and low-stock warnings for every specific size and colour combination.
Track RRP, sale price, discount percentages, and clearance flags across the entire catalogue.
Extract detailed material breakdowns and sustainability tags for compliance and attribute analysis.
Capture aggregate customer feedback on fit, length, and quality to inform returns forecasting.
Full review text, star ratings, and verified buyer flags paginated across all product reviews.
Extract localised pricing and inventory for Boden UK, US, and EU storefronts from a unified schema.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide category URLs, search terms, or specific product IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for boden.co.uk.
Schema validation, null-rate checks, price-outlier detection, and sample data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Apparel sites use dynamic frontends to manage inventory state. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Retail sites deploy bot mitigation to block aggressive scraping. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management - trained on real user behaviour patterns.
Boden's size and colour selectors rely on client-side JavaScript to fetch inventory state. We run full Playwright browser sessions with JavaScript execution to capture accurate stock flags that headless HTTP clients miss entirely.
Frontend layouts change during seasonal sales. Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and structured data extraction - so a layout change does not break your data pipeline overnight.
For large apparel 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.
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.
Apparel retailers monitor Boden's RRP, promotional cadence, and clearance discounts to optimise their own pricing strategies.
Merchandising teams analyse category depth, colourway proliferation, and fabric choices to inform seasonal range planning.
Supply chain teams track size-curve depletion rates and out-of-stock flags to model demand and improve procurement accuracy.
Fashion analysts aggregate metadata on dominant prints, patterns, and silhouettes to validate macro industry trends.
Retailers track exactly when Boden moves specific categories to clearance and at what discount depth, informing their own markdown timing.
Computer vision teams use high-resolution product imagery mapped to structured attribute data to train classification models.
"Boden's catalogue holds high-signal data on seasonal colour trends, size-curve depletion rates, and promotional cadence - structured for retail analysts."
Apparel scraping requires precise variant mapping. Extracting a product is insufficient; you must track inventory flags at the SKU-size-colour level, handle dynamic promotional overlays, and render JavaScript-heavy image galleries. DataFlirt manages this complexity natively so your team can focus on merchandising insights.
Everything supported by our boden.co.uk 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 across target regions. 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 boden.co.uk scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail websites is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline.
Yes. We support boden.co.uk, bodenusa.com, and specific EU localized storefronts. We can normalise pricing and sizing logic across regions into a unified schema.
Real-time streaming pipelines achieve sub-60-minute latency for price and stock signals on a defined SKU set. Full catalogue refreshes at daily cadence complete within a 4-6 hour window.
Yes. We extract inventory status at the granular size and colour level, allowing you to model exact size-curve depletion rates rather than generic product availability.
Our smallest packages start at a defined category list 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.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed across seasonal ranges - we scope, build, and operate the pipeline. Tell us what you need.
