We extract vintage furniture listings, dealer intelligence, pricing signals, and curation metadata from Chairish. 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 chairish.com. All fields typed and schema-versioned.
"product_id": "CH-9824152", "title": "Mid-Century Modern Milo Baughman Style Lounge Chair", "category": "Furniture", "sub_category": "Chairs > Lounge Chairs", "price": 2400.0, "currency": "USD", "condition": "Vintage/Excellent", "style": "Mid-Century Modern", "material": "Walnut, Velvet"
| # | product_id | title | category | sub_category | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Dealer Profiles objects from chairish.com. All fields typed and schema-versioned.
"dealer_id": "D-41294", "name": "Palm Springs Modern", "location": "Palm Springs, CA", "rating": 4.9, "review_count": 342, "active_listings": 128, "joined_date": "2018-04-12"
| # | dealer_id | name | location | rating | review_count | active_listings |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Shipping objects from chairish.com. All fields typed and schema-versioned.
"product_id": "CH-9824152", "list_price": 2800.0, "current_price": 2400.0, "discount_pct": 14, "make_offer_eligible": true, "local_pickup_available": true, "local_pickup_zip": "92262", "ships_from": "Palm Springs, CA"
| # | product_id | list_price | current_price | discount_pct | make_offer_eligible | shipping_cost |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Curation & Metadata objects from chairish.com. All fields typed and schema-versioned.
"product_id": "CH-9824152", "is_chairish_pink": false, "vintage_antique": "Vintage", "authenticity_verified": true, "era": "1970s", "maker": "Milo Baughman", "origin": "United States", "condition_notes": "Minor wear consistent with age and history."
| # | product_id | is_chairish_pink | vintage_antique | authenticity_verified | tags | era |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Search Results objects from chairish.com. All fields typed and schema-versioned.
"keyword": "burl wood credenza", "position": 3, "product_id": "CH-7741021", "title": "1970s Burl Wood and Brass Credenza", "price": 4500.0, "dealer": "NYC Vintage", "is_promoted": false, "scraped_at": "2026-05-12T10:14:33Z"
| # | keyword | position | product_id | title | price | dealer |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Chairish scraper handles the complexity of highly variable vintage listings: unstructured dimensions, dynamic shipping calculators, dealer catalogues, and deep category pagination.
Extract title, dimensions, condition, era, maker, materials, and every metadata field Chairish surfaces — scraped at the product level.
Monitor specific vintage dealers, track their catalogue updates, active listing counts, and response times.
Capture list price, current price, discount percentages, and Make an Offer eligibility status across thousands of items.
Extract local pickup availability, origin zip codes, and white-glove shipping parameters to map logistics networks.
Capture Chairish Pink curation flags, style tags, authenticity verification, and material composition.
Paginate across specific decor categories, eras, or styles to aggregate market availability.
Extract high-resolution image asset links for visual AI training and interior design mood boards.
Extract detailed condition notes, wear-and-tear descriptions, and vintage/antique classifications.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide dealer URLs, category links, or keyword sets. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for chairish.com.
Schema validation, null-rate checks on dimensions, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting structured data from a vintage marketplace requires handling highly variable schemas and dynamic content.
Chairish employs standard rate limiting on deep category pagination. Our crawlers use US-based residential ISP proxies with randomised request timing to maintain access without triggering blocks.
Shipping calculators and Make an Offer modules load dynamically. We run full Playwright browser sessions to trigger these network requests and capture the resulting data.
Vintage items do not share the uniform structure of modern retail. Dimensions and materials are often entered as free text. Our selectors extract these fields cleanly, allowing downstream normalisation.
For large dealer catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes for critical fields like dimensions or price, ensuring schema drift is caught immediately.
Appraisers and auction houses track fair market value, pricing trends, and time-on-market for specific eras, makers, and styles.
Vintage dealers monitor rival inventory, pricing strategies, and markdown cadences to remain competitive in specific regional markets.
ML teams use high-resolution imagery and curated style tags to train interior design recommendation engines and computer vision models.
Design firms aggregate inventory data to source specific pieces for large-scale hospitality or residential projects efficiently.
Logistics companies analyze white-glove shipping routes and local pickup density to optimise regional freight networks.
Buyers identify underpriced local-pickup items for regional resale or cross-platform arbitrage.
"Chairish hosts the internet's most curated index of vintage and antique furniture — a goldmine of pricing and style data, provided you can extract the metadata cleanly."
Extracting structured data from Chairish requires navigating deep category pagination, dynamic shipping calculators, and highly variable product schemas. Vintage items do not share the uniform structure of modern retail. We extract and normalise dimensions, materials, and eras into a unified schema, so your data team receives clean, queryable records.
Everything supported by our chairish.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 and interaction flows for dynamic shipping modules.
We maintain pools of US residential ISP proxies. Rotation happens per-request to bypass rate limits on deep category pagination.
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 chairish.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Chairish is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated product, pricing, and dealer data. We do not extract personal user data or circumvent authentication walls.
We use US-based residential ISP proxies and request timing modelled on human behaviour to paginate through deep category hierarchies without triggering rate limits or IP bans.
Yes. We extract the source URLs for all listing images, which can be used to download the assets directly for visual AI training or catalogue population.
Vintage sellers often input dimensions in unstructured text formats. We extract the raw string and can apply post-processing regex to normalise height, width, and depth into structured numeric columns.
Yes. Provide a list of dealer profile URLs, and we will configure a pipeline to monitor their active inventory, capturing new arrivals and price changes on a daily or weekly cadence.
Full catalogue refreshes or targeted dealer tracking can be scheduled daily. Changes to list price, discount percentages, and Make an Offer status are captured during each run.
Yes. We capture the boolean flag indicating whether a listing accepts offers, which is critical for understanding true market clearing prices versus listed prices.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of mid-century modern seating or continuous tracking of top vintage dealers — we scope, build, and operate the pipeline. Tell us what you need.
