We extract furniture listings, modular configurations, fabric variants, dimensions, and customer reviews from Castlery. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
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 castlery.com. All fields typed and schema-versioned.
"sku": "SOFA-OWEN-01", "title": "Owen Chaise Sectional Sofa", "category": "Living Room", "base_price": 1899.0, "currency": "USD", "rating": 4.8, "review_count": 342, "in_stock": true
| # | sku | title | category | sub_category | base_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Modular Configurations objects from castlery.com. All fields typed and schema-versioned.
"parent_sku": "SOFA-OWEN-01", "config_id": "OWEN-L-CHAISE-BOUCLE", "fabric_option": "Boucle", "fabric_colour": "Pearl White", "leg_colour": "Walnut", "configuration_price": 2199.0, "dispatch_timeline": "2-3 weeks"
| # | parent_sku | config_id | components | fabric_option | fabric_colour | leg_style |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from castlery.com. All fields typed and schema-versioned.
"review_id": "REV-89231", "sku": "SOFA-OWEN-01", "rating": 5, "author_name": "Sarah M.", "review_date": "2023-11-14", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | author_name | rating | review_date | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Stock & Delivery objects from castlery.com. All fields typed and schema-versioned.
"sku": "SOFA-OWEN-01", "postal_code": "90210", "in_stock": false, "dispatch_time": "Ships in 4 weeks", "backorder_date": "2024-02-15", "delivery_fee": 49.0, "low_stock_warning": false
| # | sku | postal_code | in_stock | dispatch_time | delivery_fee | warehouse_location |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Room Bundles objects from castlery.com. All fields typed and schema-versioned.
"bundle_id": "BNDL-LIVING-04", "title": "Mid-Century Living Set", "total_price": 2850.0, "original_price": 3100.0, "discount_amount": 250.0, "room_type": "Living Room", "component_skus": "['SOFA-OWEN-01', 'TBL-COFFEE-02']"
| # | bundle_id | title | total_price | original_price | discount_amount | component_skus |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Castlery scraper handles modular furniture configurations, fabric swatch variations, and dynamic delivery estimates with full JavaScript rendering.
Extract pricing and dimensions for every possible combination of chaise, corner, and seater modules.
Capture colour names, material types, and high-resolution swatch images across all product variants.
Extract precise width, depth, height, and seating height metrics for spatial planning and comparison.
Simulate postal codes to scrape dynamic delivery estimates, shipping fees, and backorder dates.
Map room bundles to their individual component SKUs to calculate exact discount percentages.
Scrape full review text, star ratings, verified buyer badges, and user-generated lifestyle images.
Monitor seasonal sales, clearance items, and limited-time discounts across the entire catalogue.
Extract URLs for 4K product images, 360-degree spins, and AR model files where available.
Track out-of-stock statuses and low-stock warnings to optimise your own supply chain intelligence.
Brief in. Clean data out.
Provide category URLs, specific SKUs, or target postal codes. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, managing JavaScript rendering for configuration widgets.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Furniture eCommerce relies heavily on client-side rendering for product customization. Here is how we extract the underlying data.
Castlery's modular sofa builders and fabric selectors are complex JavaScript applications. We run full Playwright browser sessions to interact with these widgets, exposing pricing and SKUs for every permutation.
A single sofa listing might contain 40 different fabric and leg combinations. Our pipeline iterates through all available selectors to build a complete matrix of child SKUs and their specific prices.
Shipping costs and lead times vary by region. We inject target postal codes into the session state to extract accurate, localized dispatch estimates and stock availability.
We use multiple fallback chains per field - CSS selectors, XPath, and Next.js state extraction - ensuring layout updates do not break your data pipeline.
For daily catalogue syncs, we maintain a hash index of last-seen values. Subsequent runs only push price changes or stock updates, reducing downstream processing load.
Furniture retailers monitor Castlery's pricing tiers, bundle discounts, and seasonal sales to adjust their own promotional strategies.
Merchandising teams analyse Castlery's category depth, fabric options, and modular configurations to identify gaps in their own catalogues.
Logistics teams track Castlery's dispatch timelines and backorder dates across different postcodes to benchmark fulfillment efficiency.
Product developers mine customer reviews to identify common complaints about assembly, comfort, or fabric durability.
Designers track the introduction of new fabrics (e.g., boucle, performance velvet) and colorways to forecast interior design trends.
eCommerce teams extract room bundle data to understand how Castlery cross-sells items and styles distinct room aesthetics.
"Castlery's modular furniture catalogue contains thousands of hidden configuration states. We extract every fabric, leg style, and dimension combination."
Extracting DTC furniture data requires mapping complex parent-child relationships for modular items. DataFlirt handles the JavaScript rendering needed to expose every swatch, dimension, and pricing tier so your engineering team can focus on data modelling.
Everything supported by our castlery.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 executes the JavaScript required to hydrate modular furniture configurators.
We maintain pools of residential ISP proxies to bypass basic rate limiting and ensure stable access to regional storefronts.
Pipelines run on AWS ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in Postgres.
Data delivered to where your team already works — no new tooling required.
About castlery.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our Playwright integration interacts with Castlery's configuration UI to expose and extract every combination of fabric, colour, leg style, and module arrangement, along with the corresponding price for each.
We simulate user sessions by injecting target postal codes. This allows us to extract localized dispatch timelines, delivery fees, and stock availability just as a real user would see them.
Yes. We capture the direct URLs for all product images, including high-resolution fabric swatches and lifestyle gallery photos.
For daily catalogue syncs, pricing and stock data is typically less than 24 hours old. We can configure higher-frequency pipelines for specific SKUs if you need intraday updates during major sales events.
Yes. We extract the bundle metadata and map it to the individual component SKUs, allowing you to calculate the exact discount applied to the set versus buying items separately.
Our minimum engagement covers a full extraction of the Castlery catalogue with weekly updates. Contact us with your specific requirements for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a weekly catalogue sync or daily stock monitoring across modular configurations, we build and operate the pipeline. Tell us your requirements.
