We extract apparel listings, pricing signals, size availability, material compositions, and stock levels from Kappahl. 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 kappahl.com. All fields typed and schema-versioned.
"product_id": "837492", "title": "Floral Wrap Dress", "brand": "Kappahl", "category": "Women", "price": 499.0, "currency": "SEK", "colours_available": "['Black/Floral', 'Navy']", "sizes_available": "['XS', 'S', 'M', 'L', 'XL']"
| # | product_id | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from kappahl.com. All fields typed and schema-versioned.
"product_id": "837492", "current_price": 399.0, "original_price": 499.0, "discount_pct": 20, "campaign_name": "Spring Sale", "currency": "SEK", "region": "SE", "member_price_flag": false
| # | product_id | current_price | original_price | discount_pct | campaign_name | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Availability objects from kappahl.com. All fields typed and schema-versioned.
"product_id": "837492", "colour": "Black/Floral", "size": "M", "sku": "837492-02-M", "in_stock_online": true, "stock_level": "HIGH", "low_stock_warning": false
| # | product_id | colour | size | sku | in_stock_online | stock_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Materials & Sustainability objects from kappahl.com. All fields typed and schema-versioned.
"product_id": "837492", "primary_material": "Viscose", "recycled_pct": 50, "sustainability_label": "Responsible Choice", "origin_country": "Bangladesh", "certification": "Lenzing Ecovero", "composition_breakdown": "100% Viscose"
| # | product_id | primary_material | recycled_pct | sustainability_label | origin_country | weight |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Inventory objects from kappahl.com. All fields typed and schema-versioned.
"product_id": "837492", "sku": "837492-02-M", "store_id": "ST-142", "store_name": "Stockholm Drottninggatan", "city": "Stockholm", "country": "SE", "in_stock": true, "click_and_collect_eligible": true
| # | product_id | sku | store_id | store_name | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Kappahl scraper handles every layer of the platform: apparel listings, dynamic regional pricing, size-level stock matrices, and sustainability data - with JavaScript rendering and session management built in.
Title, description, care instructions, and high-resolution image URLs scraped at the product level with parent-child variant mapping.
Extract complete grids of available sizes and colours for every garment, mapping SKUs to specific variant combinations.
Capture current price, original price, discount percentages, and campaign tags across different regional storefronts.
Extract material composition, recycled content percentages, and Kappahl's 'Responsible Choice' tags for ESG benchmarking.
Isolate and track data specifically for the Newbie brand, capturing category-specific attributes for baby and children's wear.
Query store-level availability for specific SKUs using geographic coordinates or postal codes to map offline stock.
Extract data from Kappahl Sweden, Norway, Finland, Poland, and the UK, normalising currencies and local sizing standards.
Extract clean CDN links for all product imagery, including model shots, flat lays, and detail zooms.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing to monitor markdowns.
Brief in. Clean data out.
Provide category URLs, target regions, or specific collections. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for kappahl.com.
Schema validation, null-rate checks, and variant-mapping verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Fashion retail sites use complex frontend frameworks and dynamic inventory APIs. Here is how we extract reliable data.
Kappahl relies on modern JavaScript frameworks to load pricing and availability. We run full Playwright browser sessions to ensure all client-side rendering completes before extraction.
Fashion data is nested. A single product URL contains multiple colours, each with distinct size availability and sometimes different prices. We flatten these matrices into clean, queryable relational records.
Instead of relying solely on DOM parsing, we intercept and query Kappahl's backend GraphQL and REST endpoints directly for accurate, real-time stock levels and store availability.
Prices and stock vary heavily by country. We use region-specific residential proxies and strict cookie management to ensure we extract the exact data presented to local consumers in Sweden, Norway, or Poland.
For large apparel 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 markdown tracking.
Retailers monitor Kappahl's pricing strategies, campaign timing, and markdown cadence to optimise their own promotional calendars.
Merchandising teams analyse category depth, colour availability, and sizing curves to inform seasonal buying decisions.
ESG analysts track the adoption rate of recycled materials and sustainable certifications across Kappahl's product lines.
Analysts monitor the expansion of the Newbie brand and category saturation trends to identify market opportunities.
Pricing teams correlate stock depth indicators with discount percentages to model optimal clearance strategies.
Machine learning teams use structured apparel metadata and high-resolution imagery to train computer vision models and recommendation engines.
"Kappahl's catalogue represents key Nordic fashion trends and sustainability baselines - but extracting precise size-level inventory requires dedicated infrastructure."
Fashion scraping goes beyond simple HTML parsing. Extracting Kappahl requires handling complex React state, multi-dimensional size and colour matrices, and dynamic regional pricing. DataFlirt absorbs that complexity so your engineers can focus on retail analytics, not scraping infrastructure.
Everything supported by our kappahl.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 retry logic. Playwright handles JavaScript rendering and interaction flows for dynamic inventory widgets.
We maintain pools of residential ISP proxies across European regions to ensure accurate local pricing and avoid rate limits.
Pipelines run on AWS Lambda and 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 kappahl.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail websites is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and inventory data. We do not extract personal data or circumvent authentication walls.
We extract the full variant matrix. Each record maps a specific SKU to its parent product, capturing the exact colour, size, price, and stock status for that specific combination.
We support extraction from all major Kappahl regional sites, including Sweden, Norway, Finland, Poland, and the UK, using localised residential proxies to ensure accurate currency and pricing.
Yes. We can configure the pipeline to target the entire catalogue or restrict extraction strictly to the Newbie collection, capturing baby and children's specific metadata.
We can configure pipelines to run at daily, hourly, or custom cadences. For markdown tracking, daily diffs are standard. For high-velocity stock monitoring, higher frequency runs are deployed.
Yes. By providing a list of postal codes or store IDs, we can query Kappahl's offline inventory systems to map physical stock availability for specific SKUs.
Our smallest packages start at a defined category list with weekly delivery. For full catalogue extraction across multiple regions, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off product catalogue dump or a continuous price-monitoring feed across multiple regions, we scope, build, and operate the pipeline. Tell us what you need.
