We extract product catalogues, dynamic pricing, store-level stock availability, and technical specifications from Power.dk. Delivered as clean JSON, CSV, or Parquet.
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 power.dk. All fields typed and schema-versioned.
"product_id": "p-123456", "ean": "8806090600000", "brand": "Samsung", "title": "Samsung 65' 4K QLED TV", "price": 7999.0, "energy_class": "G"
| # | product_id | ean | brand | title | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from power.dk. All fields typed and schema-versioned.
"product_id": "p-123456", "current_price": 7999.0, "previous_price": 9999.0, "discount_pct": 20, "campaign_name": "Weekend Sale", "is_outlet": false
| # | product_id | current_price | previous_price | discount_pct | campaign_name | is_outlet |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Click&Collect objects from power.dk. All fields typed and schema-versioned.
"product_id": "p-123456", "web_stock_status": "in_stock", "click_collect_available": true, "store_id": "s-45", "store_name": "Power Frederiksberg", "store_stock_status": "low_stock"
| # | product_id | web_stock_status | web_stock_qty | click_collect_available | store_id | store_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Technical Specifications objects from power.dk. All fields typed and schema-versioned.
"product_id": "p-123456", "spec_group": "Display", "spec_name": "Refresh Rate", "spec_value": "120 Hz", "weight_kg": 24.5, "power_consumption_kwh": 112
| # | product_id | spec_group | spec_name | spec_value | weight_kg | dimensions_mm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from power.dk. All fields typed and schema-versioned.
"review_id": "r-9876", "product_id": "p-123456", "rating": 5, "review_title": "Fantastisk TV", "review_text": "Billedkvaliteten er i top.", "date_posted": "2023-11-15"
| # | review_id | product_id | author | rating | review_title | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Power.dk scraper handles every layer of the platform: product catalogues, dynamic pricing, store-level inventory, and technical specifications — with JavaScript rendering and session management built in.
Title, EAN, brand, descriptions, and high-resolution images scraped across all electronics categories.
Capture standard prices, campaign discounts, and B2B pricing with timestamped precision.
Monitor Click&Collect availability and stock levels across specific Danish physical store locations.
Extract granular specs, dimensions, and connectivity options mapped to structured JSON.
Capture EU energy labels and consumption metrics required for compliance and green-tech analysis.
Track condition-specific pricing for returned or display models in the Power.dk outlet section.
Pull customer ratings, review text, and verified buyer status across the product catalogue.
Execute full browser sessions to hydrate dynamic pricing widgets and asynchronous stock checks.
Track weekend sales, Black Friday deals, and seasonal campaigns before they expire.
Brief in. Clean data out.
Provide category URLs, EAN lists, or specific store IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for power.dk.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern electronics retailers invest in bot protection and dynamic rendering. Here's how we stay resilient.
Power.dk relies on standard bot protection. We route requests through EU residential proxies with realistic browser fingerprints to maintain access.
Inventory levels and store-specific availability load asynchronously. We run Playwright sessions to trigger API calls and capture the true stock state.
We utilise fallback chains targeting EANs and structured LD+JSON data, ensuring layout changes don't break the pipeline.
We hash last-seen values for prices and stock. Subsequent runs only emit diffs, reducing downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes and schema drift automatically.
Retailers track Power.dk pricing to adjust their own electronics and appliance offers.
Distributors monitor stock depth across physical stores to optimise supply chain decisions.
Brands analyse category coverage and placement to identify gaps in the Danish electronics market.
Manufacturers audit listings to ensure adherence to minimum advertised pricing.
Secondary market players monitor outlet deals and condition-specific pricing.
Product teams aggregate review data to understand defect rates and feature requests.
"Power.dk holds critical pricing and inventory signals for the Nordic electronics market — data that demands precise, structured extraction."
Extracting data from modern electronics retailers requires handling asynchronous inventory calls, dynamic campaign pricing, and strict bot protection. DataFlirt manages the infrastructure complexity so your engineering team can focus on analysis and repricing logic.
Everything supported by our power.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. Playwright handles JavaScript rendering for dynamic stock and pricing APIs.
We maintain pools of residential ISP proxies in the EU region to ensure high success rates against regional blocks.
Pipelines run on AWS ECS. Airflow handles scheduling and dependency management. State stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About power.dk scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing, specification, and stock data from Power.dk is generally permissible. DataFlirt extracts only public, non-authenticated data. We do not extract personal data or circumvent authentication walls.
We use EU-based residential ISP proxies and full Playwright browser sessions with realistic fingerprints. We monitor for rate spikes and trigger pool rotation automatically.
Yes. We can simulate location contexts or trigger store-specific API endpoints to extract Click&Collect availability and stock quantities for physical Power stores.
We can configure pipelines for daily catalogue sweeps or high-frequency hourly polling on specific high-value SKUs or categories.
Yes. We extract EANs, MPNs, and brand data, which is critical for matching Power.dk products against your internal catalogue or competitor sites.
Yes. We extract outlet listings, including the specific condition of the item (e.g., returned, display model) and the corresponding discounted price.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full catalogue extraction or continuous price monitoring across thousands of SKUs — we scope, build, and operate the pipeline. Tell us what you need.
