We extract furniture listings, bedding variations, pricing signals, store-level stock data, and reviews from Dunelm. 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 dunelm.com. All fields typed and schema-versioned.
"sku": "100018472", "title": "Dorma Winchester Bedspread", "brand": "Dorma", "price": 120.0, "currency": "GBP", "category": "Bedding > Bedspreads", "composition": "100% Cotton", "dimensions": "235cm x 235cm"
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Stock objects from dunelm.com. All fields typed and schema-versioned.
"sku": "100018472", "current_price": 120.0, "discount_pct": 0, "is_clearance": false, "home_delivery_available": true, "click_collect_available": true, "stock_status": "In Stock", "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | base_price | current_price | discount_pct | is_clearance | home_delivery_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Store Inventory objects from dunelm.com. All fields typed and schema-versioned.
"sku": "100018472", "store_name": "Nottingham", "postcode": "NG7 2UU", "available_qty": 14, "collection_time": "Available in 3 hours", "status": "In Stock", "last_checked": "2026-05-12T09:15:00Z"
| # | sku | store_id | store_name | postcode | distance_miles | available_qty |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Variations objects from dunelm.com. All fields typed and schema-versioned.
"parent_sku": "100018470", "variant_sku": "100018472", "colour": "Navy", "size": "Double", "price": 120.0, "stock_status": "In Stock"
| # | parent_sku | variant_sku | colour | size | price | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews objects from dunelm.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "100018472", "star_rating": 5, "review_title": "Luxurious feel", "review_body": "Excellent quality bedspread, very warm.", "review_date": "2026-04-10", "recommended_flag": true
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Dunelm scraper handles every layer of the platform: homewares listings, dynamic pricing, store-level stock tracking, and the review corpus - with JavaScript rendering and session management built in.
Title, dimensions, composition, care instructions, images, and category paths scraped at SKU level.
Capture current price, clearance flags, and promotional discounts across the entire homewares range.
Extract store-level inventory data for any UK postcode, tracking collection times and stock depth.
Map complex parent-child relationships for bedding sizes, curtain measurements, and furniture finishes.
Extract base pricing matrices for custom curtains and blinds based on fabric and dimension inputs.
Full review text, star ratings, and recommendation flags paginated across all product review pages.
Traverse the entire Dunelm taxonomy to track new product launches and category expansions.
Simulate user location context to access accurate local store availability and delivery estimates.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or weekly cadences.
Brief in. Clean data out.
Provide category URLs, SKU lists, or specific UK postcodes for store-level stock tracking. We design the schema.
We configure Scrapy / Playwright crawlers, UK proxy rotation, and session management for dunelm.com.
Schema validation, null-rate checks, price-outlier detection, and variant mapping verification before launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Tracking store-level stock and dynamic variations requires serious infrastructure. Here is how we stay resilient.
Retailers block automated traffic. Our crawlers use residential ISP proxies localised to the UK with realistic browser fingerprints and full cookie session management to ensure uninterrupted extraction.
Dunelm product pages and stock widgets are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution to capture dynamic pricing and availability.
Click & Collect availability requires local context. We automate postcode injection into the browser session to accurately extract store-level stock data for specific UK regions.
Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and structured data extraction, so layout changes do not break your data pipeline.
For large SKU catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Retailers monitor Dunelm pricing, clearance events, and promotional windows to maintain competitive positioning.
Merchandisers track category expansion in homewares and furniture to identify trending product types.
Correlate Click & Collect stock levels across UK regions to estimate inventory velocity and demand.
Textile and furniture brands track how their products are positioned, priced, and reviewed on Dunelm.
Analysts evaluate Dunelm product catalogue scale versus competitors like John Lewis and Next.
ML teams use structured product descriptions, dimensions, and composition data to train retail NLP models.
"Dunelm's catalogue represents a massive node in the UK homewares market, but tracking store-level stock and dynamic variations requires serious infrastructure."
Extracting accurate data from Dunelm means handling complex variant matrices, simulating local UK postcodes for store inventory, and rendering heavy JavaScript for pricing. DataFlirt absorbs that complexity, delivering clean, structured records so your engineering team can focus on data modelling rather than maintaining scrapers.
Everything supported by our dunelm.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 residential ISP proxies localised to the UK. Rotation happens per-request with sticky sessions where required to prevent blocks.
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 dunelm.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Dunelm is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We automate the injection of specific UK postcodes into the session context to accurately extract store-level stock data and collection times for regional queries.
Yes. We can script inputs for dimensions and fabrics to extract base pricing matrices for custom curtains and blinds.
We can configure hourly pipelines for high-velocity SKUs. Full catalogue refreshes typically complete within a 12-hour window.
Yes. We map parent-child relationships for all sizes, colours, and finishes, ensuring complete matrix coverage.
Our smallest packages start at a defined SKU list or specific category with weekly delivery. We price based on volume and delivery frequency.
Yes. We provide a sample run of up to 500 SKUs as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous stock-monitoring feed across the UK - we scope, build, and operate the pipeline. Tell us what you need.
