We extract product listings, technical specifications, dynamic pricing, and stock depth from Komplett.no. 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 komplett.no. All fields typed and schema-versioned.
"sku": "1204855", "title": "ASUS GeForce RTX 4090 ROG Strix OC", "brand": "ASUS", "category": "Datautstyr", "sub_category": "Skjermkort", "price_nok": 24990.0, "stock_status": "15+ på lager", "rating": 4.8, "review_count": 42
| # | sku | title | brand | manufacturer_part_number | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Technical Specifications objects from komplett.no. All fields typed and schema-versioned.
"sku": "1204855", "interface": "PCI Express 4.0 x16", "memory_type": "24 GB GDDR6X", "dimensions": "35.76 cm x 14.93 cm x 7.01 cm", "ports": "2 x HDMI, 3 x DisplayPort", "power_consumption": "450W", "warranty_months": 36
| # | sku | form_factor | socket_type | memory_type | interface | dimensions |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Stock objects from komplett.no. All fields typed and schema-versioned.
"sku": "1204855", "current_price": 24990.0, "list_price": 26990.0, "discount_pct": 7, "b2b_price_ex_vat": 19992.0, "stock_count": 18, "expected_delivery_date": "2026-05-14", "price_timestamp": "2026-05-12T08:15:00Z"
| # | sku | current_price | list_price | discount_pct | b2b_price_ex_vat | stock_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews objects from komplett.no. All fields typed and schema-versioned.
"review_id": "REV-992841", "sku": "1204855", "author": "TechEnthusiast99", "rating": 5, "date": "2026-04-20", "title": "Massive card, massive performance", "helpful_votes": 14, "verified_buyer": true
| # | review_id | sku | author | rating | date | title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Demovarer (Outlet) objects from komplett.no. All fields typed and schema-versioned.
"outlet_sku": "1204855-DEMO", "original_sku": "1204855", "condition_grade": "B-Grade", "price": 21990.0, "original_price": 24990.0, "discount_abs": 3000.0, "defects_description": "Minor scratches on shroud, fully functional.", "accessories_missing": "PCIe power adapter missing"
| # | outlet_sku | original_sku | condition_grade | price | original_price | discount_abs |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Komplett scraper handles heavily nested technical specifications, dynamic stock indicators, and B2B pricing layers. We deliver normalised catalogues ready for immediate analysis.
Extract fully structured technical data including socket types, memory speeds, dimensions, and I/O ports across all hardware categories.
Capture B2C pricing in NOK, B2B pricing excluding VAT, list prices, and active campaign discounts timestamped per crawl.
Monitor exact unit counts in the main warehouse, supplier stock status, and expected delivery dates for pre-order items.
Scrape the Komplett outlet section to track B-grade pricing, condition descriptions, and refurbished stock levels.
Extract customer sentiment, star ratings, and helpfulness votes across high-value electronics and appliances.
Map recommended accessories and PC Builder compatibility constraints linked to primary component SKUs.
Extract and normalise data across komplett.no, komplett.se, and komplett.dk using a unified schema.
Preserve the exact category and sub-category hierarchy to match competitor catalogues against Komplett's structure.
Run continuous pipelines at daily cadences with change-detection, pushing only updated stock and pricing records.
Brief in. Clean data out.
Provide category URLs, brand filters, or search terms. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and dynamic stock widget hydration for komplett.no.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting accurate stock and pricing from Komplett requires handling dynamic frontend frameworks and strict rate limits.
Komplett loads exact stock counts and expected delivery dates asynchronously. We use Playwright to execute JavaScript and intercept the underlying API responses, ensuring 100% accuracy on availability data.
Tech specs on Komplett vary wildly between categories. A motherboard has different fields than a washing machine. Our pipeline maps these dynamic tables into a flattened, queryable JSON structure.
To avoid geo-blocking and rate limits, we route requests through residential ISP proxies located in Norway, Sweden, and Denmark, maintaining realistic request patterns.
We maintain a hash index of last-seen values per SKU. Subsequent runs only push diffs for price and stock changes, reducing downstream processing load.
Every run emits structured logs. We alert on null-rate spikes, category layout changes, and coverage drops, fixing selectors before you miss a data delivery.
Nordic electronics retailers monitor Komplett's pricing and campaign discounts to optimise their own pricing strategies.
Hardware manufacturers track category visibility, review sentiment, and stock depth for their own product lines.
Retailers track Komplett's inventory levels on high-demand items like GPUs and consoles to anticipate market shortages.
Resellers monitor the Demovarer section for heavily discounted B-grade stock to refurbish and flip.
Supply chain teams correlate review velocity and stock depletion rates to predict consumer electronics demand.
Brands audit Komplett listings to ensure adherence to Minimum Advertised Price agreements across the Nordic region.
"Komplett.no holds the most detailed taxonomy of PC components and consumer electronics in the Nordics. Querying it requires purpose-built infrastructure."
Extracting data from Komplett requires handling dynamic stock widgets, B2B authentication flows, and heavily nested technical specifications. DataFlirt manages the residential proxies, extraction logic, and schema validation so your team can focus on pricing strategy rather than maintaining web scrapers.
Everything supported by our komplett.no 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 the broad category crawling, while Playwright renders specific product pages to extract JavaScript-loaded stock APIs.
We route requests through region-specific residential IPs to ensure accurate local pricing and avoid geo-based rate limiting.
Pipelines run on scalable AWS infrastructure, orchestrated by Airflow to ensure daily deliveries meet strict SLAs.
Data delivered to where your team already works — no new tooling required.
About komplett.no scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing, specifications, and stock data is generally permissible. DataFlirt extracts only public information and does not bypass authentication walls to access gated user data.
Komplett uses JavaScript to load exact warehouse counts asynchronously. We use Playwright to execute the page scripts and intercept the underlying API responses to capture accurate stock depth.
Yes. We support komplett.no, komplett.se, and komplett.dk, normalising the data into a single consistent schema regardless of the regional frontend.
We typically run daily full-catalogue refreshes. For specific high-priority SKUs or outlet tracking, we can configure sub-hourly polling pipelines.
We extract the public B2B pricing excluding VAT. We do not extract customer-specific negotiated pricing as that requires account authentication.
We start with targeted category extractions, such as all PC components or all Demovarer listings, delivered on a daily schedule.
Yes. We provide a sample extraction of up to 500 products during the scoping phase so you can evaluate the schema structure and field completeness.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily price feed or a complete component specification catalogue, we build and operate the pipeline. Tell us your requirements.
