We extract commercial lighting SKUs, technical specifications, volume pricing tiers, and inventory availability from Bulbs.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 bulbs.com. All fields typed and schema-versioned.
"sku": "LED12A19-27K", "title": "12W LED A19 2700K Dimmable", "brand": "Philips", "price": 4.95, "wattage": 12.0, "lumens": 1100, "base_type": "Medium (E26)", "voltage": 120
| # | sku | title | brand | category | sub_category | price |
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Complete list of extractable fields for Pricing & Availability objects from bulbs.com. All fields typed and schema-versioned.
"sku": "LED12A19-27K", "base_price": 4.95, "case_price": 4.5, "case_quantity": 24, "tier_1_qty": 50, "tier_1_price": 4.25, "in_stock": true, "stock_message": "In Stock - Ships Today"
| # | sku | base_price | case_price | case_quantity | tier_1_qty | tier_1_price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Technical Specifications objects from bulbs.com. All fields typed and schema-versioned.
"sku": "LED12A19-27K", "cri": 90, "color_temp_k": 2700, "dimmable": true, "energy_star_certified": true, "bulb_shape": "A19", "warranty_years": 5, "spec_sheet_url": "https://www.bulbs.com/spec/LED12A19.pdf"
| # | sku | cri | color_temp_k | dimmable | energy_star_certified | dlc_qualified |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Categories & Taxonomy objects from bulbs.com. All fields typed and schema-versioned.
"category_id": "cat_led_bulbs", "category_name": "LED Bulbs", "parent_category": "Light Bulbs", "breadcrumb_path": "Home > Light Bulbs > LED Bulbs", "total_products": 4582, "top_brands": "['Philips', 'Sylvania', 'TCP', 'Satco']"
| # | category_id | category_name | category_url | parent_category | breadcrumb_path | total_products |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews & Ratings objects from bulbs.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "LED12A19-27K", "rating": 5, "reviewer_name": "Facility Manager Dave", "review_date": "2025-11-04", "review_title": "Great retrofit option", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | rating | reviewer_name | review_date | review_title |
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Our Bulbs.com scraper handles every layer of the platform: product listings, complex specification tables, dynamic volume pricing, and inventory status, with JavaScript rendering and anti-bot circumvention built in.
Title, brand, category, images, and every metadata field Bulbs.com surfaces, scraped at the individual product level.
Capture base price, case quantities, and dynamic multi-tier volume discounts timestamped per crawl.
Extract wattage, lumens, base types, CRI, colour temperature, and dimensions from unstructured HTML tables.
Monitor stock availability, backorder status, and estimated lead times across the entire catalogue.
Extract compatibility tables and recommended replacement parts for legacy lighting systems.
Capture direct URLs to manufacturer specification sheets and installation guides for offline processing.
Filter and extract specific manufacturer lines like Philips, Sylvania, or TCP across all sub-categories.
Map the entire site hierarchy, capturing breadcrumbs and category-level product counts.
Run one-off bulk exports or configure continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide category URLs, brand names, or specific SKU lists. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and parsing logic for Bulbs.com.
Schema validation, null-rate checks, price-outlier detection, and specification normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Commercial lighting catalogues present unique data extraction challenges. Here is how we maintain data integrity.
B2B suppliers monitor automated traffic. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Volume pricing and inventory statuses on Bulbs.com often load asynchronously. We run full Playwright browser sessions to ensure all client-side data is fully hydrated before extraction.
Technical specifications vary wildly between bulbs and fixtures. Our parsers use dynamic key-value extraction to normalise tables regardless of row order or missing fields.
For large catalogues, we maintain a hash index of last-seen values per SKU. 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, missing spec fields, and coverage drops.
Lighting distributors monitor retail and volume pricing tiers to adjust their own B2B pricing strategies.
Wholesalers extract clean technical specifications to backfill missing data in their own PIM systems.
Construction firms and facility managers scrape pricing to estimate lighting costs for large-scale retrofits.
Energy consultants extract wattage and lumen data to model ROI for LED upgrade projects.
Manufacturers track category saturation and competitor SKU counts to identify new product opportunities.
Analysts track backorder statuses and lead times to gauge macro supply chain health in the lighting sector.
"Bulbs.com holds a highly comprehensive commercial lighting catalogue, but extracting uniform specifications across 50,000 SKUs requires purpose-built infrastructure."
Lighting distributors underestimate the complexity of scraping technical specifications. Wattage, lumens, and base types are often buried in unstructured tables or dynamic JavaScript modules. DataFlirt normalises this data into clean schemas, handling proxy rotation and DOM changes automatically so your engineers do not have to.
Everything supported by our bulbs.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, cookie sessions, and interaction flows for dynamic pricing.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to avoid IP bans.
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 bulbs.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Bulbs.com 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. Clients should review terms of service and consult legal counsel for specific use cases.
We use Playwright to execute JavaScript on product pages, ensuring that all client-side logic responsible for rendering multi-tier volume discounts is fully hydrated before we extract the data.
Yes. We parse the unstructured HTML specification tables on each product page and normalise the keys, ensuring that metrics like CRI, colour temperature, wattage, and base type map to a clean, predictable JSON schema.
Full catalogue refreshes at a daily cadence complete within a 4-8 hour window. For critical SKUs, we can configure higher-frequency polling to capture stock status changes more rapidly.
We extract the direct URLs to the PDF specification sheets and installation guides provided by the manufacturer. We deliver these URLs in the dataset so your systems can download the documents directly.
Our smallest packages start at a defined category or brand list with weekly delivery. For full-catalogue daily refreshes, we price based on compute volume and delivery frequency. Contact us with your use case for a scoped quote.
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 50,000 SKUs, we scope, build, and operate the pipeline. Tell us what you need.
