We extract furniture listings, material specifications, stock depth, and pricing signals from alinea.com. 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 alinea.com. All fields typed and schema-versioned.
"sku": "27384910", "title": "Canapé 3 places en velours", "category": "Canapés", "price": 899.0, "currency": "EUR", "eco_participation": 8.5, "in_stock": true, "delivery_estimate": "3-5 jours"
| # | sku | title | category | sub_category | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Offers objects from alinea.com. All fields typed and schema-versioned.
"sku": "27384910", "base_price": 999.0, "current_price": 899.0, "discount_pct": 10, "promo_active": true, "promo_label": "Soldes d'hiver", "currency": "EUR", "scrape_timestamp": "2023-11-14T08:12:00Z"
| # | sku | base_price | current_price | discount_pct | discount_abs | promo_active |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Specifications objects from alinea.com. All fields typed and schema-versioned.
"sku": "27384910", "weight_kg": 45.2, "width_cm": 210, "height_cm": 85, "depth_cm": 90, "assembly_required": false, "primary_material": "Velours", "origin_country": "France"
| # | sku | weight_kg | width_cm | height_cm | depth_cm | assembly_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Store Inventory objects from alinea.com. All fields typed and schema-versioned.
"sku": "27384910", "store_id": "AL_045", "store_name": "Alinea Paris Herblay", "postal_code": "95220", "city": "Herblay", "in_stock": true, "stock_quantity": 3, "click_and_collect_eligible": true
| # | sku | store_id | store_name | postal_code | city | in_stock |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews objects from alinea.com. All fields typed and schema-versioned.
"review_id": "REV-938471", "sku": "27384910", "rating": 4.5, "author_name": "Marie D.", "review_date": "2023-10-05", "review_title": "Très confortable", "review_body": "Magnifique couleur et assise ferme.", "recommended": true
| # | review_id | sku | rating | author_name | review_date | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Alinea scraper handles the complexities of furniture retail data: variant matrices, dynamic store inventory lookups, and eco-participation pricing logic with JavaScript rendering built in.
Title, descriptions, dimensions, weight, and images scraped at the SKU level with parent-child variant mapping for colours and sizes.
Capture base price, promotional price, discount percentages, and eco-participation fees timestamped per crawl.
Extract normalised dimensions, materials, care instructions, and assembly requirements into structured JSON fields.
Query stock levels across physical retail locations using postal codes to map local availability and click-and-collect eligibility.
Extract home delivery lead times and shipping cost tiers based on product weight and dimensions.
Full review text, star ratings, helpful vote counts, and recommendation flags paginated across all review pages.
Map the full taxonomy from top-level departments down to specific sub-categories to maintain catalogue hierarchy.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or weekly cadences.
Only emit records with changed fields since the last run to reduce compute cost and downstream processing load.
Brief in. Clean data out.
Provide category URLs, keyword sets, or SKU lists. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and CAPTCHA handling for alinea.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Retail sites deploy aggressive bot mitigation to protect pricing data. Here is how we stay resilient.
We use French residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass rate limits.
Alinea relies on JavaScript for store stock lookups and variant price changes. We run full Playwright browser sessions to capture data that headless HTTP clients miss entirely.
Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and JSON-LD extraction, so a layout change does 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 downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops.
Furniture retailers monitor pricing, promotional windows, and eco-participation fees to adjust their own pricing strategies.
Merchandising teams analyse category depth, material trends, and colour availability to inform product development.
Analysts track new product launches and category saturation trends to identify whitespace in the European furniture market.
ML teams use structured furniture datasets to train visual recommendation engines and spatial planning algorithms.
Logistics teams correlate stock depth indicators and delivery lead times with market events to optimise procurement models.
Location strategists map store-level inventory availability to understand regional demand patterns.
"Alinea represents a rich dataset of European furniture trends, material usage, and pricing structures, but extracting it requires parsing complex variant matrices."
Most teams underestimate the investment required: reliable Alinea scraping requires residential proxies, full JavaScript rendering for store inventory lookups, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our alinea.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 handles JavaScript rendering, cookie sessions, and store inventory interactions.
We maintain pools of residential ISP proxies across French regions. Rotation happens per-request to avoid rate limiting.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About alinea.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail sites 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 use French residential ISP proxies, full Playwright browser sessions, and request timing modelled on human behaviour to ensure reliable extraction.
Full catalogue refreshes at daily cadence complete within a 4-8 hour window. High-priority SKUs can be tracked at hourly intervals.
Yes. We can simulate location contexts using postal codes to extract store-specific stock levels and click-and-collect availability.
Our smallest packages start at a defined category or SKU list with weekly delivery. Contact us with your use case for a scoped quote.
Yes, we extract the base price, any active promotional discounts, and the mandatory eco-participation fees as distinct fields.
Absolutely. We provide a sample run of up to 500 SKUs as part of the pre-engagement scoping process so you can validate schema fit.
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 the entire site, we scope, build, and operate the pipeline. Tell us what you need.
