We extract technical garment specifications, pricing signals, stock depth, and customer reviews from Rohan. 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 rohan.co.uk. All fields typed and schema-versioned.
"sku": "05734", "title": "Men's Bags Trousers", "category": "Mens Trousers", "price": 85.0, "currency": "GBP", "fabric_technology": "Airlight", "weight_grams": 330, "upf_rating": "40+"
| # | product_id | sku | title | category | sub_category | price |
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Complete list of extractable fields for Pricing & Stock objects from rohan.co.uk. All fields typed and schema-versioned.
"sku": "05734", "variant_id": "05734-BLK-32R", "colour": "Black", "size": "32", "leg_length": "Regular", "price": 85.0, "in_stock": true, "scraped_at": "2026-05-12T10:15:00Z"
| # | sku | variant_id | colour | size | leg_length | price |
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Complete list of extractable fields for Technical Specs objects from rohan.co.uk. All fields typed and schema-versioned.
"sku": "05734", "material_composition": "100% Polyamide", "drying_time": "3 hours", "pocket_count": 4, "security_pockets": 2, "wind_resistance": "High", "sun_protection": "UPF 40+"
| # | sku | material_composition | breathability | waterproof_rating | wind_resistance | drying_time |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Customer Reviews objects from rohan.co.uk. All fields typed and schema-versioned.
"review_id": "REV-98234", "sku": "05734", "star_rating": 5, "verified_buyer": true, "review_title": "Excellent travel trousers", "fit_rating": "True to size", "date_posted": "2026-03-14"
| # | review_id | sku | reviewer_name | verified_buyer | star_rating | review_title |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Categories & Hierarchy objects from rohan.co.uk. All fields typed and schema-versioned.
"category_id": "cat-mens-trousers", "category_name": "Men's Trousers", "parent_category": "Mens", "breadcrumb": "Home > Mens > Trousers", "product_count": 42, "category_url": "https://www.rohan.co.uk/mens-trousers"
| # | category_id | category_name | parent_category | breadcrumb | product_count | filter_attributes |
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Our Rohan scraper handles the complexities of apparel eCommerce: variant matrices, dynamic stock levels, hidden technical specifications, and paginated review feeds.
Map every combination of size, colour, and leg length to its specific SKU, price, and stock availability.
Extract granular garment data including weight, pack size, drying time, UPF rating, and proprietary fabric technologies like Barricade and Airlight.
Capture base prices, sale discounts, and clearance markdowns across all product categories, timestamped per run.
Monitor inventory levels for specific sizes and colours to forecast restocks or identify discontinued lines.
Extract full review text, star ratings, and sub-ratings for fit, quality, and value across the entire product catalogue.
Parse material composition percentages and specific wash care instructions for textile analysis.
Extract high-resolution image URLs mapped to specific colour variants for visual database construction.
Crawl category hierarchies and breadcrumbs to maintain accurate product taxonomy and classification.
Run continuous pipelines that only emit records when prices drop, stock changes, or new reviews appear.
Brief in. Clean data out.
Select target categories, specific product lines, or the entire Rohan catalogue. We map the extraction schema.
We configure Playwright crawlers to handle dynamic size selectors and variant rendering on rohan.co.uk.
Automated checks ensure weight metrics, prices, and stock statuses meet schema constraints before launch.
Clean JSON, CSV, or Parquet delivered to your AWS S3 bucket or Snowflake instance on your required cadence.
Modern storefronts hide variant data behind JavaScript events. Here is how we extract complete product matrices reliably.
Rohan's product pages update pricing and stock dynamically when a user clicks a colour or size. Our Playwright nodes iterate through every available combination in the DOM, triggering the necessary state changes to capture accurate SKU-level data.
Technical specifications are often presented in bullet points or mixed text blocks. We use regex and NLP pipelines to parse out specific metrics like weight in grams, UPF ratings, and pocket counts into strict numeric or categorical fields.
To prevent IP bans and rate limiting from commercial CDN protections, we route requests through UK-based residential proxies with rotated TLS fingerprints, ensuring uninterrupted daily crawls.
Customer reviews are often loaded asynchronously via third-party providers. We intercept these API calls or paginate through the rendered DOM to extract the complete historical review corpus for every garment.
For daily monitoring, we hash the state of each variant. If the price and stock remain identical to the previous run, the record is skipped. You only ingest actual changes, reducing warehouse compute costs.
Outdoor apparel brands monitor Rohan's pricing strategies, seasonal sale timing, and clearance discounts.
Product development teams analyse weight-to-warmth ratios, pocket configurations, and fabric technologies across the market.
Retail analysts track stock depletion rates across specific sizes and colours to model consumer demand patterns.
Marketing teams extract review text to understand customer complaints regarding fit, durability, or waterproofing.
Supply chain analysts track the usage of specific material compositions (e.g., elastane blends, polyamide) in premium outdoor gear.
Data science teams use structured apparel attributes and images to train visual search and product recommendation models.
"Rohan provides some of the most detailed technical apparel specifications in the outdoor market, but extracting weight, pack size, and fabric data requires a structured pipeline."
Most apparel scrapers fail at the variant level. Rohan's matrix of sizes, leg lengths, and colours is dynamically rendered. DataFlirt executes full browser sessions to capture exact stock depth and pricing per SKU variant, bypassing basic HTTP client limitations.
Everything supported by our rohan.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 manages the crawl frontier and deduplication, while Playwright handles the DOM interactions required to expose variant-specific pricing and stock data.
UK-based residential proxy pools rotate per request, masking automated behaviour and bypassing commercial bot mitigation systems.
Scheduled via Apache Airflow, pipelines execute on scalable Kubernetes clusters, ensuring daily catalogue refreshes complete within strict SLA windows.
Data delivered to where your team already works — no new tooling required.
About rohan.co.uk scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product data, pricing, and reviews is generally permissible for business intelligence purposes. DataFlirt extracts only public information and does not bypass authentication walls or scrape personal user data.
We use headless browsers to interact with the page just like a user would. The crawler selects each colour and size combination, waits for the DOM to update, and records the specific price, SKU, and stock status for that exact variant.
Yes. We write custom parsing logic to extract specific metrics from Rohan's product descriptions and specification tabs, normalising data like 'Weight: 330g' into strict numeric fields.
For full catalogue extraction, we recommend daily runs. For specific high-priority categories or clearance monitoring, we can configure hourly delta runs to capture rapid stock depletion.
Yes. We paginate through the entire review history for each product, capturing the text, date, verified status, and detailed sub-ratings for fit, quality, and value.
Yes. We offer a sample extraction of up to 100 products during the scoping phase, allowing your engineering team to validate the schema and data quality before contract signing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of technical specifications or continuous monitoring of stock levels across all variants, we build and manage the infrastructure. Tell us your requirements.
