We extract luggage collections, dimensional specs, material details, pricing, and availability from Samsonite. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 Specs objects from samsonite.com. All fields typed and schema-versioned.
"sku": "134679-1041", "title": "Proxis Spinner 55/20", "collection": "Proxis", "material": "Roxkin", "dimensions": "55 x 40 x 20 cm", "weight": "2.2 kg", "volume": "38 L", "warranty": "10 year global"
| # | sku | title | collection | material | dimensions | weight |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Stock objects from samsonite.com. All fields typed and schema-versioned.
"sku": "134679-1041", "price": 399.0, "list_price": 399.0, "currency": "EUR", "discount_pct": 0, "in_stock": true, "colour_variant": "Black", "scraped_at": "2026-05-12T09:14:00Z"
| # | sku | price | list_price | currency | discount_pct | in_stock |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from samsonite.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "134679-1041", "rating": 5, "author": "James T.", "date": "2026-04-12", "title": "Incredibly light", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | rating | author | date | title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variants & Colours objects from samsonite.com. All fields typed and schema-versioned.
"sku": "134679-1776", "parent_id": "134679", "colour_name": "Silver", "colour_hex": "#C0C0C0", "in_stock": true, "price": 399.0, "size_category": "Cabin", "size_label": "55cm"
| # | sku | parent_id | colour_name | colour_hex | image_urls | in_stock |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Hierarchy objects from samsonite.com. All fields typed and schema-versioned.
"sku": "134679-1041", "primary_category": "Luggage", "sub_category": "Cabin Luggage", "collection_name": "Proxis", "position": 4, "url": "https://www.samsonite.co.uk/proxis-spinner-55cm-black/134679-1041.html", "scraped_at": "2026-05-12T09:14:00Z"
| # | sku | breadcrumbs | primary_category | sub_category | collection_name | position |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline captures every technical specification, colour variant, and pricing update across regional Samsonite storefronts. Built for precision and scale.
Capture exact height, width, depth, weight, and volume metrics for every suitcase. Normalised into consistent units across regions.
Extract specific material types like Roxkin or Curv, along with TSA lock presence, wheel count, and expandability flags.
Monitor base prices, active discounts, and seasonal sale events across regional domains. Timestamped for historical analysis.
Map parent products to all available colour and size variations. Track stock availability per specific SKU variant.
Extract data from samsonite.com, samsonite.co.uk, samsonite.de, and other local sites using geo-targeted proxies.
Scrape customer ratings, review text, and verified buyer badges. Paginate through the entire review history for sentiment analysis.
Track out-of-stock statuses and low-stock warnings dynamically rendered on the product pages.
Group products by their official collections like Proxis, C-Lite, or Magnum Eco to analyse category assortments.
Receive only updated records. Our change detection system compares current runs against historical hashes to save processing bandwidth.
Brief in. Clean data out.
Specify the regional sites, categories, or specific collections you need to track. We map the extraction schema.
We configure Playwright crawlers, proxy routing, and data normalisation rules specific to Samsonite's frontend.
We test schema adherence, unit standardisation for dimensions, and variant mapping accuracy before launch.
Structured data is pushed to your preferred endpoint via S3, Snowflake, or Webhook on your defined schedule.
Extracting luggage data requires navigating dynamic variant loading and regional geo-blocks. Here is how we manage the pipeline.
Samsonite loads specific pricing and stock data only when a user selects a colour or size variant. We use Playwright to simulate these interactions, capturing the complete variant matrix.
Samsonite redirects users based on IP. We route requests through residential proxies matching the target region to ensure you see the correct local pricing and product availability.
US sites use inches and pounds, while EU sites use centimetres and kilograms. Our pipeline parses and normalises these metrics into a unified schema for cross-region comparison.
Frontend structures change during seasonal sales. We use fallback selector chains combining CSS, XPath, and JSON-LD to maintain extraction continuity.
We hash the output of every SKU. If the price, stock, or specs remain unchanged, the record is filtered out of the daily delta feed, reducing your ingestion costs.
Luggage brands monitor Samsonite's pricing tiers, material innovations, and weight-to-volume ratios to position their own products.
Third-party sellers track regional price discrepancies and stock shortages to optimise their purchasing and resale strategies.
Analysts track the introduction of new materials like Roxkin and the expansion of eco-friendly collections to gauge industry trends.
Retailers adjust their pricing algorithms based on Samsonite's promotional calendars and discount depths.
Design teams analyse customer reviews and dimensional data to identify gaps in the cabin luggage market.
Procurement teams monitor stock availability across regions to infer supply chain bottlenecks and manufacturing cycles.
"Luggage manufacturing relies on precise dimensional and material data. Samsonite provides the industry benchmark, but extracting it requires a dedicated pipeline."
Extracting data from Samsonite requires handling geo-routing, dynamic inventory states, and complex variant matrices. DataFlirt manages the proxy rotation, JavaScript execution, and schema validation so your engineers can focus on pricing models and market analysis.
Everything supported by our samsonite.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 manages the crawl orchestration and deduplication. Playwright handles the JavaScript rendering required for variant selection and dynamic pricing.
We route requests through residential ISP proxies matching the target region. This prevents Samsonite's geo-redirects from blocking access to local catalogues.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored securely in managed PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About samsonite.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We can target specific category URLs, search terms, or collection pages to limit the extraction scope to the exact products you need.
We use geo-targeted residential proxies. If you request data for samsonite.co.uk, the crawler routes through UK IPs to capture the correct GBP pricing and local stock levels.
Yes. We parse the raw strings provided by the site and can normalise them into a standard unit system (e.g., centimetres and kilograms) regardless of the source region.
We support daily, weekly, or custom cadences. For stock monitoring, we can configure higher frequency runs on a targeted list of fast-moving SKUs.
Yes. Our Playwright integration interacts with the variant selectors on the product page to load and extract the unique SKU, price, and image data for every combination.
We deliver data in JSON, CSV, or Parquet. Files can be pushed directly to your AWS S3 bucket, Snowflake instance, or sent via Webhook.
20-minute scoping call. Pilot dataset within the week. Production within two. From monitoring regional pricing to extracting detailed luggage specifications. Tell us your requirements, and we will configure the pipeline.
