Chairish Scraper - Luxury Vintage Furniture Prices
Pricing
from $5.00 / 1,000 results
Chairish Scraper - Luxury Vintage Furniture Prices
Scrape luxury vintage and antique furniture from Chairish.com. Extract prices, seller info, dimensions, materials, style, brand, condition, and images via JSON-LD Product schema.
Pricing
from $5.00 / 1,000 results
Rating
0.0
(0)
Developer
lulz bot
Actor stats
0
Bookmarked
2
Total users
1
Monthly active users
2 days ago
Last modified
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Chairish Scraper
Scrape luxury vintage and antique furniture listings from Chairish.com -- the design lover's marketplace for vintage, antique, and contemporary furniture, decor, and art.
What data can you extract?
For each product listing, the scraper extracts:
- Product details: title, description, product ID
- Pricing: current price, currency, availability
- Attributes: brand/maker, material, color, style, condition
- Dimensions: width, height, depth (in inches)
- Seller info: seller name, location, country
- Ratings: aggregate rating value, review count
- Images: all product images (full URLs), image count
- Category: hierarchical category path and category code
- Metadata: product URL, scrape timestamp
How to use
Search by keyword
Enter search terms like "mid century modern chair", "art deco lamp", or "vintage dining table". The scraper will search Chairish and extract product data from the results.
Browse by collection or category
Provide collection/category URLs directly:
https://www.chairish.com/collection/furniturehttps://www.chairish.com/collection/arthttps://www.chairish.com/collection/lighting
Scrape specific products
Provide direct product URLs to scrape individual listings:
https://www.chairish.com/product/12345678/vintage-eames-chair
Input parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
searchQueries | string[] | ["mid century modern chair"] | Search terms to find products |
startUrls | URL[] | [] | Direct product or collection URLs |
maxResults | integer | 50 | Maximum total results (0 = unlimited) |
maxPages | integer | 3 | Max listing pages per query/collection |
proxyConfiguration | object | {} | Proxy settings for large runs |
Example output
{"productId": "3974825","title": "1960s Vintage Carimate Chair by Vico Magistretti for Cassina","description": "Carimate lounge chair by Vico Magistretti for Cassina, Italy, 1962...","price": 2900,"currency": "USD","availability": "In Stock","condition": "Used","category": "Furniture > Chairs > Arm Chairs, Recliners & Sleeper Chairs","categoryCode": "SEATING:ACCENTCHAIR:LOUNGE","brand": "Cassina","material": "Beech/Rush","color": "Red","style": "Mid-Century Modern","dimensions": "24.02in W x 28.35in D x 28.35in H","widthIn": 24.02,"heightIn": 28.35,"depthIn": 28.35,"seller": "HOPP Home","sellerLocation": "New York, LFP","sellerCountry": "US","ratingValue": null,"reviewCount": null,"imageUrl": "https://chairish-prod.freetls.fastly.net/image/product/master/...","images": ["..."],"imageCount": 6,"url": "https://www.chairish.com/product/3974825/...","searchQuery": "mid century modern chair","scrapedAt": "2026-04-25T12:00:00.000Z"}
How it works
- Search/Browse: The scraper fetches search results or collection pages from Chairish, which are server-side rendered HTML
- Product discovery: Extracts all product links from listing pages and follows pagination
- Detail extraction: Visits each product page and extracts structured data from JSON-LD
Productschema embedded in the HTML, supplemented by Open Graph meta tags - Data enrichment: Parses additional details (style, condition) from the rendered page text
Tips
- Chairish has tens of thousands of active listings across furniture, art, lighting, and decor
- Use specific search queries for better-targeted results
- Collection URLs like
/collection/furnitureprovide broad browsing - The scraper respects rate limits; use proxy configuration for large-scale runs
- Each listing page contains approximately 48 products
Cost estimation
Using pay-per-event pricing at $0.005 per result:
- 50 results = ~$0.25
- 500 results = ~$2.50
- 5,000 results = ~$25.00