We extract luminaire specifications, bulb compatibility, pricing signals, and energy efficiency ratings from Lampegiganten.dk. 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 Basics objects from lampegiganten.dk. All fields typed and schema-versioned.
"sku": "10014582", "title": "Philips Hue White Ambiance LED-pære E27", "brand": "Philips Hue", "price": 249.0, "currency": "DKK", "in_stock": true
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Technical Specs objects from lampegiganten.dk. All fields typed and schema-versioned.
"sku": "10014582", "material": "Plastik", "colour": "Hvid", "socket_type": "E27", "ip_rating": "IP20", "dimmable": true
| # | sku | material | colour | socket_type | max_wattage | ip_rating |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Light Characteristics objects from lampegiganten.dk. All fields typed and schema-versioned.
"sku": "10014582", "bulb_included": true, "luminous_flux_lumen": 806, "light_colour_kelvin": "2200 - 6500", "energy_efficiency_class": "F", "lifespan_hours": 25000
| # | sku | bulb_included | luminous_flux_lumen | light_colour_kelvin | colour_rendering_index | lifespan_hours |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Dimensions objects from lampegiganten.dk. All fields typed and schema-versioned.
"sku": "10014582", "height_cm": 11.0, "diameter_cm": 6.0, "weight_kg": 0.072, "suspension_length_cm": "None", "mounting_depth_cm": "None"
| # | sku | height_cm | width_cm | length_cm | diameter_cm | suspension_length_cm |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews objects from lampegiganten.dk. All fields typed and schema-versioned.
"review_id": "REV-849201", "sku": "10014582", "rating": 5, "reviewer_name": "Morten K.", "review_date": "2026-03-14", "verified_purchase": true
| # | review_id | sku | rating | reviewer_name | review_date | review_text |
|---|---|---|---|---|---|---|
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Lampegiganten.dk relies on complex HTML tables to display technical specifications. Our scraper normalises this data into clean, typed fields, ensuring you get exact socket types, IP ratings, and smart home protocols without writing parsing logic.
Extract material, colour, socket type, IP rating, operating voltage, and protection class directly from the technical details table.
Capture EU energy efficiency classes (A to G), luminous flux (lumen), and light colour (kelvin) for every applicable bulb and fixture.
Identify ZigBee, Bluetooth, WiFi, and specific ecosystem compatibility like Philips Hue, Casambi, or Tuya.
Record current DKK pricing, original list prices, and active discount percentages across the entire catalogue.
Parse availability status and estimated delivery windows (e.g., 2-4 hverdage) to monitor supply chain consistency.
Map parent-child relationships for products available in multiple finishes or sizes, ensuring no variant is missed.
Aggregate customer feedback, star ratings, and review dates to gauge product reception and quality issues.
Filter and extract data specifically for key lighting brands like Lindby, Lucande, Arcchio, or Philips.
Run daily catalogue refreshes or target specific high-velocity categories for hourly price monitoring.
Brief in. Clean data out.
Provide Lampegiganten.dk category URLs, brand filters, or specific search queries. We map the extraction schema.
We configure Scrapy spiders to traverse pagination, parse technical tables, and handle Danish language encoding.
Schema validation ensures fields like lumen, kelvin, and IP ratings are strictly typed as integers or formatted strings.
JSON, CSV, or Parquet files pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on schedule.
Extracting technical lighting data requires precise parsing of nested tables and handling regional e-commerce infrastructure.
Lighting specifications vary wildly between brands. A smart bulb has different fields than an outdoor wall light. Our pipeline uses a dynamic key-value parser to read the HTML spec tables and map them to a unified, predictable JSON schema.
Many fixtures are sold in multiple colours or lengths under a single parent URL. Our spiders interact with the variant selection elements to load and extract the specific SKU, price, and image for every single combination.
We handle Danish number formatting (comma as decimal separator) and text encoding (æ, ø, å) natively, ensuring prices are converted to standard floats and text remains uncorrupted in your database.
With tens of thousands of SKUs across deeply nested categories, standard crawlers often miss items. We use sitemap parsing combined with systematic category pagination to guarantee 100% catalogue coverage.
Instead of processing the entire 80,000+ SKU catalogue every day, our differential engine compares current runs against historical hashes, emitting only the products that saw price changes, stock shifts, or spec updates.
Lighting retailers track Lampegiganten's discounting strategies and base prices to optimise their own pricing algorithms.
Merchandising teams analyse brand representation and category depth to identify missing product lines in their own stores.
Regulators and analysts track the transition of the lighting market towards higher EU energy efficiency classes.
IoT platforms build compatibility databases by scraping socket types and supported protocols (ZigBee, WiFi) across all fixtures.
Manufacturers monitor how their products are positioned, priced, and reviewed on Europe's largest lighting retail network.
Machine learning teams extract high-resolution images paired with precise dimension and material metadata to train spatial design models.
"Lampegiganten holds the most structured technical lighting dataset in Europe, but extracting precise socket types and IP ratings requires custom parsing logic."
Extracting lighting data goes beyond simple titles and prices. Our pipelines parse complex technical specification tables, mapping intricate details like luminous flux, protection classes, and smart home protocols into a normalised schema. DataFlirt handles the extraction complexity so your team can focus on assortment strategy and pricing intelligence.
Everything supported by our lampegiganten.dk 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 is deployed selectively to render dynamic variant selectors and cookie consent walls.
We route requests through European residential proxy pools to maintain high success rates and avoid geo-blocking mechanisms.
Pipelines are scheduled via Apache Airflow and executed on Kubernetes clusters, scaling automatically to handle full catalogue sweeps.
Data delivered to where your team already works — no new tooling required.
About lampegiganten.dk scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available catalogue data is generally permissible. DataFlirt extracts only public pricing, specifications, and reviews without bypassing authentication walls or scraping personally identifiable information. We advise clients to review local regulations regarding data usage.
Lighting specifications differ vastly by product type. We use dynamic key-value parsing to extract the HTML tables, mapping the raw Danish labels to a standardised English or Danish JSON schema, ensuring fields like 'Fatning' correctly map to 'socket_type'.
Yes. Our parsers automatically convert Danish number formats (e.g., 1.299,00 kr.) into standard float types (1299.00) and normalise the currency to DKK for immediate database compatibility.
For the entire catalogue of ~80,000 SKUs, we recommend daily runs. For targeted subsets (e.g., top 5,000 competitor SKUs), we can configure hourly extraction pipelines.
Yes. We extract the assigned energy class (A-G) from the product metadata or specification tables, allowing you to track compliance and energy efficiency trends.
We build custom pipelines starting from full catalogue extractions delivered weekly. Pricing scales based on run frequency and target volume. Contact us for a precise quote.
Yes. We offer sample runs of specific categories (e.g., Smart Home Lighting) during scoping so you can validate the schema and data cleanliness before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off technical specs dump or continuous price monitoring across the lighting catalogue, we build and operate the infrastructure. Tell us your requirements.
