We extract runway analyses, colour palettes, textile intelligence, and CAD flats from WGSN. 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 Trend Reports objects from wgsn.com. All fields typed and schema-versioned.
"report_id": "RPT-99482", "title": "A/W 26/27 Macro Trends", "category": "Macro Forecasting", "published_date": "2025-10-14", "author": "WGSN Intelligence", "macro_trend": "Digital Realities", "images_count": 42, "tags": "['A/W 26/27', 'Womenswear', 'Youth']"
| # | report_id | title | category | published_date | author | summary |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Colour Palettes objects from wgsn.com. All fields typed and schema-versioned.
"palette_id": "PAL-4410", "season": "S/S 26", "theme": "Bioluminescence", "colour_name": "Digital Orchid", "hex_code": "#B84C9F", "pantone_ref": "17-2435 TCX", "rgb_value": "184, 76, 159", "usage_notes": "Key accent colour for activewear"
| # | palette_id | season | theme | colour_name | hex_code | pantone_ref |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Textile & Fabric objects from wgsn.com. All fields typed and schema-versioned.
"fabric_id": "TEX-88219", "fabric_name": "Recycled Tech Twill", "blend_composition": "65% Recycled Polyester, 35% Organic Cotton", "weight": "180gsm", "weave_type": "Twill 2/1", "supplier_name": "EcoTextiles Ltd", "sustainability_cert": "GRS, GOTS", "application_category": "Outerwear"
| # | fabric_id | fabric_name | blend_composition | weight | weave_type | supplier_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Runway Analytics objects from wgsn.com. All fields typed and schema-versioned.
"show_id": "RWY-2025-AW-PAR-04", "designer": "Balenciaga", "season": "A/W 25", "city": "Paris", "look_number": 12, "primary_colour": "Onyx Black", "key_item": "Oversized Trench", "fabric_detail": "Heavyweight Gabardine"
| # | show_id | designer | season | city | look_number | primary_colour |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for CAD Flats objects from wgsn.com. All fields typed and schema-versioned.
"cad_id": "CAD-10934", "category": "Womenswear", "sub_category": "Tops", "garment_type": "Asymmetric Blouse", "season": "S/S 26", "format_available": "['AI', 'EPS', 'PDF']", "front_view_url": "https://media.wgsn.com/cad/10934_front.jpg", "download_link": "https://api.wgsn.com/assets/cad/10934.ai"
| # | cad_id | category | sub_category | garment_type | season | format_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our WGSN scraper handles every layer of the platform: macro trends, colour intelligence, runway analytics, and CAD flat libraries, with full session management and asset downloading built in.
Title, summary, tags, macro trend mapping, and embedded images scraped from highly structured WGSN intelligence reports.
Capture seasonal palettes, hex codes, Pantone references, and CMYK values, timestamped and mapped to specific demographics.
Extract vector format availability, garment metadata, and download links for thousands of technical flats across categories.
Designer, season, city, look number, primary colour, and key item tags extracted from WGSN runway coverage.
Supplier names, blend compositions, weave types, and sustainability certifications extracted from the textile database.
Demographic shifts, purchasing behaviour predictions, and sentiment analysis text extracted from macro reports.
Vector download links, motif categories, and scale metadata for seasonal print and graphic forecasts.
Pricing architecture, category mix, and markdown analysis extracted from WGSN retail intelligence modules.
Run one-off bulk exports or configure continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide target categories, seasons, or report types. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for wgsn.com.
Schema validation, null-rate checks, asset download verification, and sample reports before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
WGSN relies heavily on complex authentication states and dynamic single page application rendering. Here is how we maintain stable extraction.
WGSN is a gated platform. We build secure credential rotation and session cookie management into the pipeline, ensuring your licensed access is utilised efficiently without triggering concurrent login blocks.
WGSN interfaces are heavy single page applications. We run full Playwright browser sessions with JavaScript execution, lazy-load triggering, and dynamic content hydration, capturing data that headless HTTP clients miss entirely.
Trend forecasting requires visual data. Our pipeline manages the asynchronous downloading of high-resolution images, PDF reports, and vector CAD files directly to your cloud storage, linking the object URIs back to the structured metadata.
Platform updates change DOM structures frequently. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and text-pattern matching, so a layout change does not break your data pipeline overnight.
Every run emits structured logs to our observability stack. We alert on session timeouts, null-rate spikes, and coverage drops, responding before you notice. SLA uptime is contractual, not aspirational.
Merchandising teams map WGSN colour and silhouette forecasts directly into their PLM systems to guide seasonal buys.
Design teams ingest CAD flats and print graphics into internal asset libraries, accelerating the technical design process.
Sourcing managers track fabric and material trends to negotiate early with suppliers for upcoming high-demand textiles.
Brand strategists analyse macro consumer insights and demographic shifts to align marketing campaigns with cultural trends.
Machine learning teams use historical WGSN data to train predictive models for retail demand forecasting.
Retail analysts track assortment data and pricing architecture to identify whitespace and category saturation.
"WGSN dictates global fashion and retail cycles, but accessing that intelligence programmatically requires navigating heavy client side rendering and strict session limits."
Extracting intelligence from WGSN requires maintaining complex authenticated sessions, executing heavy JavaScript applications, and managing high volume asset downloads. DataFlirt handles the infrastructure so your design and analytics teams can focus on product strategy, not web scraping.
Everything supported by our wgsn.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain encrypted credential stores and manage session cookies precisely to avoid concurrent login limits while maximising extraction throughput.
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 wgsn.com scraping, legality, and pipeline operations.
Ask us directly →Yes. WGSN is a strictly gated platform. DataFlirt builds the extraction pipeline, but you must provide valid authentication credentials corresponding to your enterprise license.
Our pipelines are configured to respect WGSN session limits. We serialise extraction tasks or utilise multiple provided seats to scale throughput without triggering account blocks.
Yes. We can extract the metadata and programmatically download the associated AI, EPS, or PDF vector files, delivering them directly to your cloud storage.
Pipelines can be configured to run daily or weekly to capture new trend reports and runway coverage as soon as they are published on the platform.
Yes, provided your account has access to the Barometer module. We can extract the retail assortment data, pricing architecture, and markdown analytics.
Our packages start at a defined scope of categories or report types with weekly delivery. We price based on the complexity of the rendering and the volume of asset downloads. 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 continuous runway analytics or a structured database of seasonal colour palettes, we scope, build, and operate the pipeline. Tell us what you need.
