We extract product listings, dimension variations, fabric options, lead times, and pricing signals from Room and Board. 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 roomandboard.com. All fields typed and schema-versioned.
"sku": "249813", "title": "Jasper Sofa", "category": "Living Room", "base_price": 1899.0, "material": "Fabric", "finish": "Walnut", "assembly_required": false, "lead_time_weeks": 4
| # | sku | title | category | base_price | material | finish |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Upholstery & Fabrics objects from roomandboard.com. All fields typed and schema-versioned.
"sku": "249813", "fabric_name": "Tatum", "fabric_grade": "A", "colour": "Grey", "composition": "100% Polyester", "durability": "Family Friendly", "price_modifier": 0.0, "swatch_available": true
| # | sku | fabric_name | fabric_grade | colour | composition | durability |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Availability objects from roomandboard.com. All fields typed and schema-versioned.
"sku": "249813", "base_price": 1899.0, "configured_price": 2099.0, "delivery_surcharge": 119.0, "in_stock": true, "lead_time_weeks": 4, "zip_code": "90210", "clearance_status": false
| # | sku | base_price | configured_price | delivery_surcharge | in_stock | lead_time_weeks |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Dimensions & Specs objects from roomandboard.com. All fields typed and schema-versioned.
"sku": "249813", "overall_width": 86.0, "overall_depth": 36.0, "overall_height": 32.0, "seat_height": 18.0, "arm_height": 24.0, "inside_width": 76.0, "inside_depth": 22.0, "weight": 145.0
| # | sku | overall_width | overall_depth | overall_height | seat_height | arm_height |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Collections & Rooms objects from roomandboard.com. All fields typed and schema-versioned.
"collection_id": "C902", "collection_name": "Jasper", "room_type": "Living Room", "designer": "Room and Board", "related_skus": "['249813', '249814']", "total_items": 12, "description": "Mid-century modern styling.", "lifestyle_images": 4
| # | collection_id | collection_name | room_type | designer | related_skus | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our scraper handles every layer of the platform: base models, dynamic fabric configurations, dimensional variants, and ZIP-based lead times - with JavaScript rendering and session management built in.
Base models, collections, categories, and sub-categories scraped at SKU level with parent-child variant mapping.
Iterate through every fabric grade, colour, and material finish to capture specific configured pricing and imagery.
Extract exact measurements including overall width, seat depth, arm height, and clearance for spatial planning.
Simulate ZIP code inputs to extract regional stock status, delivery surcharges, and estimated lead times in weeks.
Capture base URLs and parameters for product silhouettes, lifestyle shots, and fabric swatches.
Extract textual data for care instructions, construction details, and assembly requirements per product.
Track base price, configured price modifications, and clearance status across the entire catalogue.
Map individual SKUs back to their parent collections and related room layouts for complete assortment context.
Run continuous pipelines at daily or weekly cadences with change-detection diffing for price and stock updates.
Brief in. Clean data out.
Provide category URLs, specific collections, or full-site requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and dynamic configuration handlers for roomandboard.com.
Schema validation, null-rate checks, price-outlier detection, and variant combination sampling before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Furniture sites rely on complex configurators. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Furniture pricing changes based on fabric grade, leg finish, and dimensions. Our crawlers systematically iterate through the JavaScript configurator state to capture exact pricing and lead times for every possible SKU combination.
Room and Board lead times and delivery fees vary by region. We simulate location contexts using specific ZIP codes to extract accurate regional data, ensuring your supply chain models reflect reality.
We intercept network requests to extract raw image CDN URLs, bypassing low-resolution frontend thumbnails to deliver the highest quality assets for interior design platforms and AI models.
Frontend DOM structures change frequently. Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and JSON state extraction - so a layout update does not break your data pipeline.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops - and respond before you notice. SLA uptime is contractual.
Furniture retailers monitor base prices and fabric-grade markups to optimise their own pricing strategies.
Merchandising teams analyse category depth, material trends, and dimension distributions to identify market gaps.
Design software providers ingest exact 3D-compatible dimensions and high-res imagery for room planning tools.
Analysts track lead time fluctuations across ZIP codes to gauge manufacturing backlog and supply chain health.
Designers monitor the introduction of new fabrics, colours, and sustainable materials across collections.
ML teams use structured dimension and style data to train spatial awareness and furniture recommendation models.
"Room and Board offers one of the most configurable furniture catalogues available - but extracting every fabric and dimension combination requires serious infrastructure."
Most teams underestimate the investment required: reliable configurator scraping requires full JavaScript rendering, systematic state iteration, and regional ZIP code simulation. DataFlirt absorbs that complexity so your engineers can focus on the analysis - not the infrastructure.
Everything supported by our roomandboard.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, state iteration, and configurator interaction.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to maintain ZIP code context.
Pipelines run on AWS Lambda and ECS. 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 roomandboard.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and dimension data. We do not extract personal data or circumvent authentication walls.
We use Playwright to simulate user interactions, systematically selecting each fabric grade, colour, and leg finish to trigger the frontend state changes, capturing the resulting price and image updates.
Yes. We can inject target ZIP codes into the session context to extract location-specific lead times, in-store availability, and delivery surcharges.
Full catalogue refreshes at weekly or daily cadences complete within a defined window. Delta runs can be configured to check specific high-velocity categories more frequently.
Yes. We capture the complete specifications tab, parsing overall width, depth, height, seat dimensions, arm height, and weight into structured numeric fields.
Absolutely. We provide a sample run of specific collections or categories 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 price-monitoring feed across every fabric combination - we scope, build, and operate the pipeline. Tell us what you need.
