We extract product listings, sizing inventory, pricing signals, and material specs from Superga. 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 superga.com. All fields typed and schema-versioned.
"sku": "S000010-901", "style_code": "2750", "title": "2750 Cotu Classic", "category": "Sneakers", "material": "Cotton Canvas", "sole_type": "Vulcanised Rubber", "base_price": 65.0, "currency": "EUR"
| # | sku | style_code | title | category | collection | material |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sizing & Inventory objects from superga.com. All fields typed and schema-versioned.
"sku": "S000010-901", "colour": "White", "size_eu": "42", "size_uk": "8", "size_us_m": "9", "in_stock": true, "stock_level": 14, "restock_date": "None"
| # | sku | style_code | colour | size_eu | size_uk | size_us_m |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from superga.com. All fields typed and schema-versioned.
"sku": "S000010-901", "base_price": 65.0, "sale_price": 52.0, "discount_pct": 20, "currency": "EUR", "promo_eligible": false, "outlet_flag": true, "region": "IT"
| # | sku | base_price | sale_price | discount_pct | currency | promo_eligible |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variant Mapping objects from superga.com. All fields typed and schema-versioned.
"parent_sku": "S000010", "variant_sku": "S000010-901", "colour_name": "White", "colour_hex": "#FFFFFF", "is_primary": true, "gender": "Unisex", "size_range": "35-46", "image_urls": "['url1.jpg', 'url2.jpg']"
| # | parent_sku | variant_sku | colour_name | colour_hex | image_urls | is_primary |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locations objects from superga.com. All fields typed and schema-versioned.
"store_id": "IT-104", "name": "Superga Torino", "type": "Flagship", "city": "Turin", "country": "Italy", "latitude": 45.0703, "longitude": 7.6869, "phone": "+39 011 123456"
| # | store_id | name | type | address | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles the Superga storefront architecture, extracting nested variants, real-time stock levels, and regional pricing rules without triggering rate limits.
SKU, title, description, style codes, and care instructions extracted for every shoe model.
Track in-stock status across EU, UK, and US sizing charts for every specific variant.
Link parent styles to all available colourways with exact hex codes and names.
Monitor base prices, seasonal sales, and outlet discounts across regional storefronts.
Extract upper, lining, and outsole composition details directly from product descriptions.
Track limited edition drops and designer collaborations with specific metadata.
Extract global retail and franchise locations with precise geographic coordinates.
Capture high-resolution product imagery and lifestyle shots linked to specific SKUs.
Support for superga.co.uk, superga-usa.com, and superga.it from a unified schema.
Brief in. Clean data out.
Provide categories, regions, or specific SKUs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for superga.com.
Schema validation, null-rate checks, and size-grid testing before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Footwear sites rely heavily on dynamic inventory states. Here is how we extract accurate sizing and stock data at scale.
Size availability is loaded dynamically. We use Playwright to execute JavaScript and intercept inventory API responses to capture exact stock states.
Colourways often have unique URLs or hash fragments. Our crawlers map parent styles to all child variants to ensure complete catalogue coverage.
Superga redirects users based on IP. We use region-specific residential proxies to target exact regional storefronts without forced redirects.
We match request rates to human browsing patterns, preventing IP bans while maintaining throughput for daily catalogue sweeps.
Retail sites update layouts seasonally. Our monitors alert on missing fields or DOM changes, triggering selector updates before data drops.
Footwear brands track Superga's baseline and discount pricing to inform their own promotional calendars.
Retailers monitor stock depth on core lines like the 2750 to anticipate wholesale availability.
Fashion analysts track colourway popularity and sell-out rates to predict seasonal trends.
Auditing third-party sellers against official Superga retail prices to enforce pricing policies.
Commercial real estate analysts track Superga store openings and closures globally.
Merchandisers compare canvas versus leather SKU counts to understand material shifts.
"Superga's classic canvas lines generate massive global demand, but tracking real-time availability across regional sites requires dedicated infrastructure."
Extracting footwear data means dealing with multi-dimensional variants: styles, colours, and sizes. DataFlirt handles the complex DOM traversal and inventory API requests so your team receives clean, normalised product records ready for analysis.
Everything supported by our superga.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 for dynamic inventory grids.
We maintain pools of residential ISP proxies to bypass regional redirects and access local pricing.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management.
Data delivered to where your team already works — no new tooling required.
About superga.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Superga is generally permissible. We target only public product, pricing, and store data. We do not extract personal data or circumvent authentication walls.
We use region-specific residential proxies to prevent Superga from redirecting our crawlers, allowing us to capture accurate local pricing and inventory.
Yes. We capture the complete size grid for every variant and flag which specific sizes are currently unavailable.
We can configure pipelines for daily catalogue sweeps or hourly checks on specific high-priority SKUs.
Yes. We parse the product descriptions to extract details about the upper, lining, and outsole materials.
Yes. We provide a sample run of up to 100 SKUs during the scoping phase so you can validate the schema.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily stock feed or a one-off catalogue export, we scope, build, and operate the pipeline. Tell us what you need.
