We extract designer lighting catalogues, technical specifications, finish variants, and pricing signals from Lightology. 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 Fixture Specs objects from lightology.com. All fields typed and schema-versioned.
"sku": "LGY-10492", "title": "Melt Pendant", "brand": "Tom Dixon", "lumens": 800, "colour_temperature": "2700K", "wattage": 9.0, "dimming_type": "ELV", "ip_rating": "IP20"
| # | sku | title | brand | designer | category | lumens |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Stock objects from lightology.com. All fields typed and schema-versioned.
"sku": "LGY-10492", "base_price": 1250.0, "sale_price": 1050.0, "discount_pct": 16, "in_stock": true, "lead_time_days": 14, "ships_free": true, "stock_status_text": "Usually ships in 2 weeks"
| # | sku | base_price | sale_price | discount_pct | currency | in_stock |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variants & Finishes objects from lightology.com. All fields typed and schema-versioned.
"parent_sku": "LGY-10492", "variant_sku": "LGY-10492-SMK", "finish_name": "Smoke", "finish_family": "Grey", "price_delta": 0.0, "swatch_url": "https://images.lightology.com/swatches/smoke.jpg", "availability": "In Stock"
| # | parent_sku | variant_sku | finish_name | finish_family | size_name | price_delta |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Brands & Collections objects from lightology.com. All fields typed and schema-versioned.
"brand_name": "Tom Dixon", "collection_name": "Melt", "designer_name": "Tom Dixon", "country_of_origin": "United Kingdom", "warranty_years": 1, "total_products": 42
| # | brand_id | brand_name | collection_name | designer_name | country_of_origin | brand_description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from lightology.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "LGY-10492", "author": "Sarah M.", "rating": 5, "title": "Stunning focal point", "date_posted": "2023-11-14", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | author | rating | title | body_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Lightology scraper handles product configurators, nested technical specifications, and dynamic lead times with JavaScript rendering and anti-bot circumvention built in.
Lumens, colour temperature, CRI, wattage, voltage, and dimming compatibility scraped directly from product spec tables.
Capture every finish, shade colour, and size combination. We map parent-child SKUs to ensure variant-level accuracy.
Monitor retail pricing, promotional sales, and clearance discounts across the entire catalogue.
Track Quick Ship eligibility, specific lead time days, and out-of-stock statuses for supply chain forecasting.
Extract designer attributions, collection names, and brand hierarchies to categorise the lighting market.
Parse height, width, depth, and canopy dimensions into normalised numeric fields for spatial analysis.
Full review text, star ratings, and verified buyer flags paginated across all product review pages.
High-resolution product image URLs, technical spec sheet PDFs, and finish swatch images linked to variants.
Run continuous pipelines at daily cadences with change-detection diffing to monitor new product launches and price shifts.
Brief in. Clean data out.
Provide brand names, category URLs, or specific SKUs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for lightology.com.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting technical lighting data requires navigating dynamic product configurators and strict bot protection. Here is how we manage the infrastructure.
Lightology uses dynamic JavaScript to load pricing and lead times when a user selects a specific finish or size. We run full Playwright browser sessions to iterate through these configurators, capturing data that headless HTTP clients miss entirely.
E-commerce platforms block data centre IPs rapidly. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to maintain access without triggering rate limits.
Technical specifications are often formatted inconsistently across different brands. We use text-pattern matching and structured data extraction to ensure fields like 'Colour Temperature' and 'Lumens' map correctly regardless of DOM layout.
For large lighting catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load for price and stock updates.
Every run emits structured logs to our observability stack. We alert on null-rate spikes in critical fields like pricing or dimensions and respond before the data reaches your warehouse.
Lighting retailers and distributors monitor Lightology pricing, promotional calendars, and brand restrictions to optimise their own pricing strategies.
Merchandising teams analyse brand coverage, category depth, and new designer launches to identify gaps in their own product catalogues.
Procurement teams track lead times and stock availability across major brands to anticipate supply chain bottlenecks in the lighting industry.
Proptech and interior design software companies ingest technical specifications and 3D-ready dimensions to populate their material libraries.
Lighting manufacturers audit how their products are presented, checking specification accuracy, image quality, and MAP compliance.
Analysts track the adoption of LED technology, colour temperature trends, and smart-home integration across thousands of fixtures.
"Lightology holds the most comprehensive technical specification dataset for designer lighting available online, but extracting variant level data requires deep DOM traversal."
Most teams underestimate the investment required: reliable Lightology scraping requires residential proxies, full JavaScript rendering for finish configurators, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our lightology.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 for dynamic product configurators.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request to prevent rate limiting.
Pipelines run on AWS 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 lightology.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Lightology is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and specification data. We do not extract personal data or circumvent authentication walls.
Lightology uses dynamic JavaScript configurators for finishes and sizes. We use Playwright to iterate through these options, capturing the specific price, SKU, and lead time for every variant combination.
Yes. We parse the technical specification tables on the product pages, mapping fields like wattage, voltage, lumens, CRI, and dimensions into structured, normalised numeric fields.
Full catalogue refreshes at daily cadence complete within a 4-8 hour window depending on category size. We can configure specific high-priority brands for more frequent polling.
We extract the direct URLs to the PDF specification sheets and installation instructions, delivering them as string fields in the final payload.
Yes. We provide a sample run of up to 500 products 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 designer lighting brands, we scope, build, and operate the pipeline. Tell us what you need.
