We extract home tours, 'Steal This Look' product lists, material guides, and the Architect/Designer Directory from Remodelista. Delivered as clean JSON, CSV, or Parquet to your warehouse.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Home Tours & Articles objects from remodelista.com. All fields typed and schema-versioned.
"article_id": "RM-84921", "title": "A Scandi-Inspired Kitchen in Brooklyn", "author": "Margot Guralnick", "publish_date": "2023-11-14T08:00:00Z", "category": "Kitchens", "location": "Brooklyn, New York"
| # | article_id | url | title | author | publish_date | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Steal This Look objects from remodelista.com. All fields typed and schema-versioned.
"product_name": "Aalto Stool 60", "brand": "Artek", "retailer": "Design Within Reach", "price": 350.0, "currency": "USD", "room_type": "Dining Room"
| # | look_id | article_url | room_type | product_name | brand | retailer |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Architect Directory objects from remodelista.com. All fields typed and schema-versioned.
"name": "Jane Doe", "firm_name": "Doe Architecture", "location": "San Francisco, CA", "website": "https://doearch.example.com", "specialties": "['Residential', 'Sustainable Design']", "email": "hello@doearch.example.com"
| # | profile_id | name | firm_name | location | website | |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sourcing Guides objects from remodelista.com. All fields typed and schema-versioned.
"title": "Remodeling 101: Soapstone Countertops", "category": "Remodeling 101", "material_type": "Soapstone", "cost_estimate": "$70 - $120 per square foot", "suppliers": "['M. Teixeira Soapstone', 'Vermont Marble']", "pros_cons": "Heat resistant, requires regular oiling"
| # | guide_id | title | category | material_type | pros_cons | cost_estimate |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for High-Res Imagery objects from remodelista.com. All fields typed and schema-versioned.
"image_id": "IMG-99231", "image_url": "https://cdn.remodelista.com/wp-content/uploads/2023/11/brooklyn-kitchen-max.jpg", "alt_text": "Minimalist white kitchen with oak accents", "room_tag": "Kitchen", "resolution": "2400x1600", "photographer": "Matthew Williams"
| # | image_id | source_article_url | image_url | alt_text | caption | room_tag |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Remodelista embeds valuable product and directory data within narrative text. Our parsers convert these editorial formats into clean, relational datasets.
Extract exact product names, retailers, and prices from curated room designs and mapping them to external URLs.
Scrape the complete Architect/Designer Directory including contact details, firm locations, and portfolio links.
Bypass compressed CDN thumbnails to extract maximum resolution image URLs for computer vision or editorial use.
Map unstructured article tags into a clean, queryable taxonomy for room types, styles, and geographic locations.
Link featured products back to external retailer URLs and brand websites to monitor affiliate and outbound traffic paths.
Parse pros, cons, and pricing estimates from Remodelista material guides into structured comparison tables.
Capture bylines, publication dates, and category silos for content analysis and editorial trend mapping.
Navigate JavaScript-heavy category pages to ensure zero article drops across the entire historical archive.
Monitor RSS and category feeds to extract new home tours daily without executing full database re-crawls.
Brief in. Clean data out.
Provide target categories, directory filters, or specific article types. We design the extraction schema together.
We configure Scrapy crawlers, handle image URL resolution, and parse unstructured editorial text for product links.
Schema validation, null-rate checks on product links, and image resolution verification before launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on your defined schedule.
Extracting data from an editorial platform requires specialised text parsing and media resolution. Here is how we build reliable pipelines.
Articles embed product links directly in narrative paragraphs. We use NLP and regex pipelines to extract structured brand, pricing, and retailer data from editorial text blocks.
Remodelista serves compressed images via CDNs for performance. Our scrapers rewrite image URLs to extract the raw, high-resolution source files directly from the backend.
Category pages rely on infinite scroll. We run full Playwright browser sessions to trigger lazy-loaded articles and ensure complete extraction of historical archives.
Retailer links in older 'Steal This Look' posts frequently 404. Our pipeline validates outbound links during extraction, flagging dead URLs so your dataset remains actionable.
We maintain a hash index of the Architect Directory to only push updates when design firms change their contact details, locations, or portfolio links.
Retailers track featured products to identify trending styles, monitor competitor placements, and adjust inventory.
B2B suppliers extract the Architect/Designer Directory for targeted outreach to active firms based on project specialties.
Design platforms ingest home tours and material guides to enrich their own editorial databases and search indexes.
Analysts process room tags, colour palettes, and material mentions to predict interior design trends across regions.
ML teams use tagged, high-resolution room images to train object detection and interior style classification models.
Agencies track outbound retailer links to calculate editorial ROI and map affiliate revenue potential across publishers.
"Remodelista holds a decade of curated interior design intelligence, but extracting structured product data from editorial prose requires purpose-built parsing."
Most teams struggle to convert narrative home tours into relational product databases. DataFlirt handles the heavy lifting: resolving image CDNs, parsing inline retailer links, and mapping unstructured tags into a clean taxonomy so your team can focus on design analytics.
Everything supported by our remodelista.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 orchestrates the crawl while Playwright handles infinite scroll and lazy-loaded image hydration on editorial pages.
Custom Python pipelines extract structured product names, prices, and retailer URLs from unstructured narrative text.
Pipelines run on AWS Lambda and ECS. Airflow manages daily incremental runs to capture new home tours as they publish.
Data delivered to where your team already works — no new tooling required.
About remodelista.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public editorial content and directories is generally permissible under applicable web scraping laws. DataFlirt targets only public, non-authenticated articles, product links, and directory profiles. We do not extract personal user data or circumvent authentication walls.
Yes. Our parsers isolate product names, prices, and outbound retailer links from the editorial text, returning them as structured arrays mapped to specific room types.
We provide maximum-resolution image URLs by default. We can also configure S3 pipelines to download and store the binary image files directly in your designated bucket.
Pipelines can be configured for daily or weekly incremental runs, capturing newly published articles and directory additions without re-scraping the entire historical archive.
Yes, we extract full firm profiles, including contact details, specialities, geographic locations, and direct links to their portfolio websites.
We map Remodelista's internal tagging system into a normalised taxonomy for room types, architectural styles, and materials to ensure the output data is immediately queryable.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full export of the Architect Directory or a continuous feed of 'Steal This Look' products — we scope, build, and operate the pipeline. Tell us what you need.
