We extract premium activewear listings, pricing signals, colourway availability, stock depth, and customer reviews from Sweaty Betty. 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 sweatybetty.com. All fields typed and schema-versioned.
"sku": "SB12345", "title": "Power Gym Leggings", "category": "Leggings", "price": 85.0, "currency": "GBP", "colour_name": "Black", "fabric_type": "Polyamide Elastane Blend"
| # | sku | title | category | sub_category | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from sweatybetty.com. All fields typed and schema-versioned.
"sku": "SB12345", "base_price": 85.0, "sale_price": 68.0, "currency": "GBP", "discount_pct": 20, "sale_active": true
| # | sku | base_price | sale_price | currency | discount_pct | promo_badge |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Stock & Inventory objects from sweatybetty.com. All fields typed and schema-versioned.
"sku": "SB12345", "colour_id": "BLK01", "size": "M", "in_stock": true, "low_stock_warning": true, "stock_message": "Only 2 left"
| # | sku | colour_id | size | in_stock | low_stock_warning | stock_message |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Fabric & Care objects from sweatybetty.com. All fields typed and schema-versioned.
"sku": "SB12345", "material_primary": "62% Polyamide", "material_secondary": "38% Elastane", "stretch_type": "4-way stretch", "wash_instructions": "Machine wash at 40°C", "sustainability_tags": "['Recycled Materials']"
| # | sku | material_primary | material_secondary | breathability_rating | stretch_type | wash_instructions |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from sweatybetty.com. All fields typed and schema-versioned.
"review_id": "REV-98273", "sku": "SB12345", "rating": 5, "title": "Perfect for running", "verified_buyer": true, "fit_feedback": "True to size", "date": "2026-03-14"
| # | review_id | sku | rating | title | body | author |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Sweaty Betty scraper maps complex parent-child product relationships, capturing prices, stock depths, and fabric compositions across all colourways and sizes.
Title, description, fabric details, care instructions, and image assets scraped across all activewear categories.
Parent-child mapping for every colour and size variant, ensuring complete catalogue coverage.
Size-level inventory checks and low-stock warning detection for demand forecasting.
Track seasonal sales, discount percentages, and promotional badges across the entire site.
Star ratings, text reviews, and specific fit feedback extracted from the customer review sections.
Extract material blends, stretch types, and sustainability claims for product R&D analysis.
Capture all gallery images, model shots, and product close-ups with original resolution URLs.
Systematic crawling of leggings, sports bras, outerwear, and accessories categories.
Run daily diffs for pricing changes or real-time checks for fast-moving inventory.
Brief in. Clean data out.
Provide category URLs, search terms, or SKU lists. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for sweatybetty.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Fashion eCommerce sites use dynamic frontend frameworks. Here is how we extract structured data reliably.
We route requests through ISP-grade residential proxies in the UK and US to prevent IP blocking and rate limiting during high-volume crawls.
Sweaty Betty uses dynamic size and colour selectors. We use Playwright to execute JavaScript and trigger these UI elements, capturing data hidden from standard HTTP clients.
Our selector strategy uses multiple fallback chains per field, including structured data extraction (LD+JSON), so frontend redesigns do not break your pipeline.
We maintain a hash index of last-seen values per SKU. Subsequent runs only push diffs for price drops or stock changes, reducing downstream processing load.
Every run emits structured logs. We alert on null-rate spikes in critical fields like price or stock status, ensuring high data fidelity.
Activewear brands track Sweaty Betty markdowns and promotional events to inform their own pricing strategies.
Retail analysts evaluate colourway breadth and sizing depth to understand category investment and product lifecycle.
Monitor out-of-stock rates across key sizes to estimate sales velocity and demand for specific product lines.
Track new arrivals, category expansion, and seasonal colour introductions to inform future design cycles.
Extract fabric composition and sustainability claims to benchmark material standards against industry peers.
Mine review text and fit feedback to understand common sizing issues and quality perceptions.
"Sweaty Betty's catalogue holds critical signals for premium activewear trends, fabric composition standards, and seasonal pricing strategies."
Extracting apparel data requires handling complex parent-child variant structures where prices and stock levels change per size and colour. DataFlirt manages this complexity with residential proxies, full JavaScript execution for dynamic product pages, and automated schema validation. We deliver clean, structured records so your analysts can focus on market positioning rather than fixing broken crawlers.
Everything supported by our sweatybetty.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 and interaction flows for dynamic product variants.
We maintain pools of residential ISP proxies across UK and US regions. Rotation happens per-request to ensure continuous access to product catalogues.
Pipelines run on AWS Lambda and ECS. 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 sweatybetty.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and review data is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls.
We use Playwright to execute JavaScript and interact with the DOM, ensuring we capture pricing and stock data for every specific colour and size combination, not just the default view.
Yes. We extract material blends, sustainability tags, wash instructions, and fit details directly from the product description sections.
Pipelines can be configured for daily full-catalogue refreshes or high-frequency intra-day checks for specific high-velocity SKUs.
Yes. We capture base price, sale price, discount percentages, and any active promotional badges present on the product listing.
Yes. We provide a sample run of up to 100 SKUs as part of the scoping process so you can validate the schema and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or continuous pricing and stock feeds — we scope, build, and operate the pipeline. Tell us what you need.
