We extract regional pricing, material specifications, SKU variations, and stock availability from Fendi. 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 Metadata objects from fendi.com. All fields typed and schema-versioned.
"product_id": "8BN244Q0JF0E66", "name": "Peekaboo ISeeU Medium", "category": "Bags", "sub_category": "Tote Bags", "made_in": "Italy", "material_composition": "100% Calf Leather"
| # | product_id | name | category | sub_category | description | material_composition |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & SKUs objects from fendi.com. All fields typed and schema-versioned.
"sku": "8BN244Q0JF0E66_TU", "colour": "Dove Grey", "size": "TU", "price": 4300.0, "currency": "EUR", "region": "it-it"
| # | sku | base_product_id | colour | size | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Imagery & Assets objects from fendi.com. All fields typed and schema-versioned.
"product_id": "8BN244Q0JF0E66", "hero_image_url": "https://fendi.com/images/8BN244Q0JF0E66_01.jpg", "gallery_image_urls": "['https://fendi.com/images/8BN244Q0JF0E66_02.jpg', 'https://fendi.com/images/8BN244Q0JF0E66_03.jpg']", "video_url": "https://fendi.com/videos/8BN244Q0JF0E66.mp4", "alt_text": "Dove grey leather bag", "aspect_ratio": "4:5"
| # | product_id | hero_image_url | gallery_image_urls | model_image_urls | video_url | lookbook_reference |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Boutique Availability objects from fendi.com. All fields typed and schema-versioned.
"store_id": "IT_MIL_01", "store_name": "Fendi Milan Montenapoleone", "city": "Milan", "country": "Italy", "phone": "+39 02 7602 1617", "available_skus": "['8BN244Q0JF0E66_TU']"
| # | store_id | store_name | address | city | country | phone |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Collections & Runway objects from fendi.com. All fields typed and schema-versioned.
"season": "Spring/Summer", "year": "2026", "collection_name": "Women's SS26", "designer": "Kim Jones", "look_number": 14, "associated_products": "['8BN244Q0JF0E66']"
| # | season | year | collection_name | designer | look_number | associated_products |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Fendi scraper handles dynamic rendering, regional geo-routing, and complex SKU hierarchies to extract precise catalogue data across all global markets.
Bags, ready-to-wear, shoes, and accessories mapped to parent-child SKUs with complete metadata.
Extract localised pricing across US, EU, UK, and APAC markets to monitor global pricing parity.
Detailed fabric breakdowns, leather types, hardware specifications, and care instructions.
Track online versus in-store availability across global flagship locations.
Capture raw CDN links for product imagery, runway shots, and 360-degree views.
Extract Complete the Look recommendations and associated SKUs for merchandising analysis.
Access fendi.com/us-en, fendi.com/it-it, and 20 other regional subdirectories from a unified schema.
Playwright execution to handle dynamic product grids, infinite scroll, and client-side hydration.
Daily or weekly runs capturing only new arrivals and price adjustments to minimise processing overhead.
Brief in. Clean data out.
Provide target regions, categories, or collections. We map the extraction schema together.
We configure Playwright crawlers, regional proxy rotation, and session management.
Schema validation, currency normalisation, and null-rate checks before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Extracting luxury data requires navigating heavy client-side rendering and aggressive geo-routing. Here is how we build resilient extraction pipelines.
Fendi routes users based on IP address. We use ISP proxies localised to target markets to capture accurate regional pricing and prevent automatic redirects to the wrong storefront.
Fendi relies heavily on client-side rendering. We execute full Playwright sessions to hydrate the DOM and extract nested product data that headless HTTP clients miss entirely.
Luxury items have nested variations across colour, size, and hardware. Our extractors flatten these combinations into queryable relational records linked to a base product ID.
We capture raw CDN URLs for high-resolution images, bypassing lazy-loading mechanisms and optimised thumbnails to deliver the highest quality visual assets.
For seasonal collections, we maintain hash indexes of catalogue state, emitting only net-new SKUs and price changes to reduce storage bloat and downstream processing load.
Monitor luxury pricing parity across global markets to optimise regional strategies and margin.
Analyse Fendi's category mix, colour distribution, and seasonal material choices to inform merchandising.
Correlate retail pricing with resale platforms to calculate luxury asset depreciation and market demand.
Train visual AI models using official high-resolution imagery and authentic product metadata.
Identify arbitrage opportunities by comparing localised pricing, tax structures, and currency fluctuations.
Track runway-to-retail timelines and the adoption of specific materials across seasonal collections.
"Luxury fashion data is highly fragmented across regions. Fendi's catalogue requires precise geo-targeting to map global pricing parity accurately."
Extracting data from luxury brands requires navigating heavy client-side rendering and aggressive geo-routing. DataFlirt handles the localised proxy rotation and dynamic DOM hydration, delivering a normalised schema across all global markets so your team can focus on merchandising intelligence.
Everything supported by our fendi.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 orchestration and deduplication. Playwright handles SPA rendering, infinite scroll, and interaction flows.
Residential ISP proxies across target markets to bypass geo-routing and capture accurate local pricing.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About fendi.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product data is generally permissible under applicable law. DataFlirt targets only public, non-authenticated catalogue and pricing data. We do not extract personal data or circumvent authentication walls.
We use localised residential proxies to access specific regional sites, preventing automatic redirects and ensuring we capture the exact pricing and availability for that specific market.
Yes, we capture the underlying CDN URLs for all gallery and zoom images, bypassing lazy-loading mechanisms to provide the highest quality assets.
Every colour, size, and material combination is extracted as a distinct record and mapped back to the parent product ID for relational querying.
We can run daily or weekly pipelines to track price adjustments, currency shifts, and seasonal markdowns across all monitored regions.
Yes, we extract stock indicators for specific boutique locations based on the provided product URLs and target regions.
Our pipelines start at a defined category or regional scope with weekly delivery cadences. Contact us with your specific requirements for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous regional price monitoring across global markets, we scope, build, and operate the pipeline. Tell us what you need.
