We extract handbag specifications, collection data, pricing signals, and inventory status from Brahmin. 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 Specs objects from brahmin.com. All fields typed and schema-versioned.
"sku": "K4315100001", "name": "Large Duxbury Satchel", "collection": "Melbourne", "style": "Satchel", "price": 345.0, "colour": "Pecan", "material": "Croc-Embossed Leather", "dimensions": "12.5 W x 12.0 H x 5.0 D", "strap_drop": "13.0 inches"
| # | sku | name | collection | style | price | colour |
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Complete list of extractable fields for Inventory & Pricing objects from brahmin.com. All fields typed and schema-versioned.
"sku": "K4315100001", "price": 345.0, "list_price": 345.0, "discount_pct": 0, "in_stock": true, "stock_level": "High", "final_sale": false, "currency": "USD"
| # | sku | price | list_price | discount_pct | in_stock | stock_level |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Collections & Taxonomy objects from brahmin.com. All fields typed and schema-versioned.
"sku": "K4315100001", "primary_category": "Handbags", "sub_category": "Satchels", "collection_name": "Melbourne", "texture": "Croc-Embossed", "season": "Core", "breadcrumbs": "['Home', 'Handbags', 'Satchels', 'Large Duxbury Satchel']"
| # | sku | primary_category | sub_category | collection_name | texture | season |
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Complete list of extractable fields for Reviews objects from brahmin.com. All fields typed and schema-versioned.
"review_id": "REV-849201", "sku": "K4315100001", "rating": 5, "reviewer_name": "Sarah M.", "date": "2023-10-14", "title": "Beautiful everyday bag", "body": "The Pecan Melbourne is classic. Fits everything I need for work.", "verified_buyer": true
| # | review_id | sku | rating | reviewer_name | date | title |
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Complete list of extractable fields for Media & Assets objects from brahmin.com. All fields typed and schema-versioned.
"sku": "K4315100001", "primary_image_url": "https://brahmin.com/media/catalog/product/k/4/k43151_pecan_front.jpg", "gallery_urls": "['https://brahmin.com/media/catalog/product/k/4/k43151_pecan_side.jpg', 'https://brahmin.com/media/catalog/product/k/4/k43151_pecan_back.jpg']", "texture_swatch_url": "https://brahmin.com/media/swatches/pecan_melbourne.jpg", "360_view_available": false, "image_count": 6
| # | sku | primary_image_url | gallery_urls | video_url | texture_swatch_url | alt_text |
|---|---|---|---|---|---|---|
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Our Brahmin scraper navigates complex product hierarchies, capturing specific textures like Melbourne leather, dynamic inventory states, and detailed dimensions without missing a stitch.
Title, dimensions, strap drop, interior pockets, and hardware details scraped directly from the product definition.
Track specific product lines like Melbourne, Pecan, and seasonal releases across categories.
Capture out-of-stock indicators and backorder dates to understand supply chain velocity.
Monitor final sale markers, promotional discounts, and base retail prices.
Extract specific leather types, embossing details, and lining materials for every SKU.
Capture gallery images, texture swatches, and product videos linked to their respective colourways.
Extract star ratings, review text, and verified buyer status across all product pages.
Map frequently bought together items and matching accessories suggested by the platform.
Reconstruct the site taxonomy using breadcrumbs and category tags for accurate product placement.
Brief in. Clean data out.
Provide target categories, collections, or specific Brahmin SKUs. We map the extraction schema.
We configure Scrapy crawlers, proxy rotation, and session management for brahmin.com.
Schema validation, null-rate checks, and data typing before full launch.
JSON / CSV / Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Retail sites deploy aggressive caching and dynamic inventory loading. We manage the infrastructure so you get clean data.
Brahmin loads inventory status dynamically via frontend APIs. We intercept these network requests to capture accurate stock indicators rather than relying on cached HTML.
Luxury handbags feature complex variant structures. We map every colour and texture swatch to its parent SKU, ensuring images and prices align perfectly.
We route traffic through US residential IPs to bypass rate limits and prevent IP bans during full catalogue scrapes.
We maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs. We alert on null-rate spikes or schema drift caused by site updates, and respond before your data flow breaks.
Luxury retailers monitor price points, discount frequencies, and final sale items to optimise their own pricing strategies.
Analysts track trends in leather textures, colours, and bag silhouettes to identify shifts in consumer preference.
Track stock depletion rates across the Melbourne collection to model supply chain velocity.
Merchandisers compare category depth and product mixes against competitors to identify portfolio gaps.
Brand protection teams audit third-party listings against authoritative catalogue specifications.
Computer vision models trained on high-resolution handbag silhouettes and specific leather embossings.
"Brahmin's catalogue represents a highly structured ontology of textures, materials, and silhouettes. Accessing this requires a pipeline built for retail precision."
Extracting data from luxury retail sites requires handling complex variant structures, dynamic swatch loading, and strict rate limits. DataFlirt manages the proxies, renders the JavaScript, and parses the nested JSON so your engineering team can focus on integrating the data rather than fixing broken selectors.
Everything supported by our brahmin.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, dynamic content loading, and interaction flows.
We maintain pools of residential proxies to bypass retail rate limits. Rotation happens per-request to ensure high success rates.
Pipelines run on scalable infrastructure. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About brahmin.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Brahmin 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 map every colourway, texture, and size to its parent SKU. Each variant is extracted as a distinct record with its specific price, imagery, and stock status.
Yes. We extract the collection taxonomy directly from the product metadata, allowing you to filter and analyse specific lines like Melbourne or Pecan.
We can configure pipelines to run at daily or hourly cadences depending on your requirements, ensuring stock signals are accurate for forecasting.
Yes. We capture the highest resolution image URLs available in the gallery, alongside specific texture swatch images.
We recommend starting with a full catalogue scrape delivered weekly. For higher frequency tracking on specific categories, we adjust the pipeline scope accordingly.
20-minute scoping call. Pilot dataset within the week. Production within two. Get structured catalogue, pricing, and inventory data delivered directly to your warehouse. Tell us your requirements.
