We extract product listings, pricing signals, fabric composition, size availability, and promotional data from Vero Moda. 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 veromoda.com. All fields typed and schema-versioned.
"sku": "VM-10258492-BLK", "title": "Vero Moda Black High Neck Sweater", "category": "Knitwear", "price": 2499.0, "currency": "INR", "colour_name": "Black", "available_sizes": "['XS', 'S', 'M', 'L']", "style_code": "10258492"
| # | sku | product_id | title | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from veromoda.com. All fields typed and schema-versioned.
"sku": "VM-10258492-BLK", "current_price": 1499.0, "original_price": 2499.0, "discount_pct": 40, "sale_badge": "End of Season Sale", "promo_code_eligible": false, "currency": "INR", "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | current_price | original_price | discount_pct | discount_abs | sale_badge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Sizing objects from veromoda.com. All fields typed and schema-versioned.
"sku": "VM-10258492-BLK", "colour_name": "Black", "colour_hex": "#000000", "size": "M", "in_stock": true, "low_stock_warning": true, "out_of_stock_sizes": "['XL', 'XXL']", "stock_level": 3
| # | sku | colour_name | colour_hex | size | in_stock | stock_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fabric & Sustainability objects from veromoda.com. All fields typed and schema-versioned.
"sku": "VM-10258492-BLK", "material_composition": "80% Viscose, 20% Nylon", "care_instructions": "Machine wash at 30°C. Do not bleach.", "sustainable_flag": true, "aware_collection": true, "origin_country": "Bangladesh", "fit_type": "Regular Fit"
| # | sku | material_composition | lining_material | care_instructions | sustainable_flag | aware_collection |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category & Navigation objects from veromoda.com. All fields typed and schema-versioned.
"category_id": "VM-CAT-042", "category_name": "Sweaters & Cardigans", "parent_category": "Knitwear", "breadcrumb": "Home > Women > Knitwear > Sweaters & Cardigans", "total_products": 284, "gender": "Women", "position": 4, "scraped_at": "2026-05-12T09:14:33Z"
| # | category_id | category_name | parent_category | breadcrumb | position | total_products |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Vero Moda scraper handles dynamic inventory grids, promotional overlays, and region-specific catalogues. We extract clean, structured apparel data bypassing modern anti-bot perimeters.
Title, category, description, fit type, model stats, and high-resolution image URLs — extracted across all apparel categories.
Capture current price, original price, discount percentages, and sale badges timestamped per crawl to track markdown strategies.
Extract size availability arrays, low stock warnings, and out-of-stock indicators per specific colour variant.
Map complex colour and size matrices back to parent style codes, ensuring accurate representation of the product grid.
Extract material composition percentages, care instructions, and AWARE collection sustainability flags.
Scrape veromoda.in, veromoda.com, and European regional sites with localised pricing and inventory data.
Reconstruct navigation hierarchies and breadcrumbs to analyse assortment structure and category depths.
Extract CDN links for primary, alternate, and detail shots for visual AI training or competitor benchmarking.
Run daily catalogue syncs or configure continuous pipelines for high-velocity inventory tracking during sale events.
Brief in. Clean data out.
Provide category URLs, specific regions, or style codes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for veromoda.com.
Schema validation, null-rate checks, price-outlier detection, and variant mapping before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Fashion eCommerce platforms use dynamic frontends and edge protection. Here's how we stay resilient — and why teams choose managed infrastructure over DIY.
eCommerce firewalls block datacenter IPs and headless browsers. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Vero Moda's product grids and dynamic pricing widgets require Javascript execution. We run full Playwright browser sessions to hydrate the DOM and capture sizes and prices that static clients miss.
Apparel data is deeply nested. We map every available size and stock status to its specific colour variant, normalising complex frontend state into flat, queryable database rows.
For large apparel catalogues, we maintain a hash index of last-seen values per SKU. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing size arrays, schema drift, and coverage drops.
Retailers and brands monitor pricing, markdown cadence, and promotional events to optimise their own pricing strategies.
Merchandising teams analyse category depth, colour prevalence, and fabric choices to identify seasonal trends and assortment gaps.
Track end-of-season sales, flash discounts, and coupon eligibility across thousands of SKUs to map competitor promotional calendars.
Monitor size-level stock availability over time to estimate sales velocity and identify high-demand styles.
Extract material compositions and sustainability flags to benchmark the adoption of eco-friendly fabrics in fast fashion.
Computer vision teams ingest high-resolution garment imagery and structured metadata to train apparel recognition and styling models.
"Fast fashion moves on inventory cycles and micro-trends. You cannot benchmark pricing without structured access to the underlying catalogue data."
Extracting apparel data at scale requires navigating complex variant matrices across colours and sizes, handling dynamic pricing widgets, and bypassing modern anti-bot perimeters. DataFlirt manages the extraction infrastructure so your analysts can focus on assortment strategy and margin optimisation.
Everything supported by our veromoda.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 deduplication. Playwright handles JavaScript rendering, cookie sessions, and dynamic DOM interaction.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions where required for consistency.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About veromoda.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Vero Moda is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and inventory data. We do not extract personal data, circumvent authentication walls, or violate GDPR.
We extract the complete variant matrix. Each record represents a unique SKU (style + colour + size combination), ensuring inventory availability and pricing are accurate at the lowest granular level.
We support veromoda.in, veromoda.com, and localised European domains. You specify the target region, and we configure the pipeline to route through appropriate local residential proxies to capture accurate regional pricing.
Full catalogue refreshes typically run daily. For specific high-priority categories or sale events, we can configure pipelines to run at hourly intervals to capture rapid inventory depletion.
Yes. We capture the original list price, current selling price, calculated discount percentage, and any visible sale badges or promotional text applied to the product.
We extract the high-resolution CDN URLs for all product images (primary, alternate, detail). We do not download and store the raw image binaries, keeping payload sizes manageable for warehouse ingestion.
Our smallest packages start at a defined category list with weekly delivery. For full-site daily extraction, we price based on compute volume and delivery frequency. Contact us with your use case for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily catalogue sync or continuous price tracking across 80K SKUs — we scope, build, and operate the pipeline. Tell us what you need.
