We extract beauty product listings, fashion sizing charts, pricing signals, brand catalogues, and reviews from YesStyle. 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 Beauty Products objects from yesstyle.com. All fields typed and schema-versioned.
"sku": "1090011501", "title": "Advanced Snail 96 Mucin Power Essence", "brand": "COSRX", "price": 18.5, "currency": "USD", "rating": 4.8, "in_stock": true
| # | sku | title | brand | category | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Fashion Apparel objects from yesstyle.com. All fields typed and schema-versioned.
"sku": "1112345678", "title": "Pleated Mini Skirt", "brand": "Chuu", "price": 24.9, "size_options": "['S', 'M', 'L']", "colour_options": "['Black', 'Grey', 'Navy']", "stock_status": "In Stock"
| # | sku | title | brand | category | size_options | colour_options |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Promos objects from yesstyle.com. All fields typed and schema-versioned.
"sku": "1090011501", "base_price": 25.0, "sale_price": 18.5, "discount_pct": 26, "currency": "USD", "promo_tags": "['Bestseller', 'Sale']", "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | base_price | sale_price | discount_pct | currency | promo_tags |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews & Ratings objects from yesstyle.com. All fields typed and schema-versioned.
"review_id": "RVW987654321", "sku": "1090011501", "rating": 5, "skin_type": "Combination", "skin_tone": "Warm", "helpful_votes": 42
| # | review_id | sku | author | rating | date | skin_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Brands & Categories objects from yesstyle.com. All fields typed and schema-versioned.
"brand_id": "BRD10293", "brand_name": "COSRX", "category": "Skincare", "product_count": 145, "is_cruelty_free": true, "country_of_origin": "South Korea"
| # | brand_id | brand_name | category | product_count | brand_url | top_seller_sku |
|---|---|---|---|---|---|---|
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Our YesStyle scraper handles every layer of the platform: K-beauty ingredient lists, complex fashion sizing tables, geo-targeted pricing, and review metadata with skin type attributes.
Extract full ingredient lists, cruelty-free flags, skin concern tags, and volume metrics for skincare and cosmetics.
Parse complex HTML sizing charts into structured JSON arrays, mapping measurements to specific size variants.
Capture pricing, currency, and availability based on specific shipping destinations using localised proxy sessions.
Extract review text, star ratings, and highly specific user attributes like skin type, skin tone, and age group.
Monitor brand-level assortments, new product drops, and category saturation across thousands of Asian brands.
Track daily flash sales, discount percentages, and countdown timers to optimise competitive pricing strategies.
Monitor stock status, low stock warnings, and estimated shipping delays per SKU and variant combination.
Extract high-resolution product image URLs, variant-specific colour swatches, and user-generated review photos.
Run continuous pipelines with hash-based diffing to emit only records that have changed since the last execution.
Brief in. Clean data out.
Provide category URLs, brand names, or specific SKUs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and CAPTCHA handling for yesstyle.com.
Schema validation, null-rate checks, price-outlier detection, and sample data review before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting structured data from highly variable fashion and beauty catalogues requires handling dynamic rendering and complex DOM structures. Here is how we build resilience.
YesStyle alters pricing, currency, and availability based on the user's IP and session cookies. We maintain strict geo-targeted proxy pools and explicit session headers to ensure you receive accurate pricing for your target market.
Fashion sizing tables on YesStyle vary wildly between brands. We deploy heuristic parsing logic that normalises unstructured HTML tables into clean, queryable JSON arrays mapping specific measurements to size variants.
Aggressive scraping triggers CAPTCHAs and IP bans. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and automated CAPTCHA solving to maintain continuous throughput.
Many product variants, stock statuses, and flash sale timers are loaded via client-side JavaScript. We utilise Playwright to render the full DOM, ensuring dynamic state is captured accurately.
DOM structures change frequently. Our selector strategy uses multiple fallback chains per field, combining CSS selectors, XPath, and JSON-LD extraction to prevent pipeline failures when layouts update.
Retailers analyse brand catalogues and category depth to identify trending K-beauty brands and gaps in their own inventory.
Beauty and fashion marketplaces monitor YesStyle pricing, flash sales, and discount depth to optimise their own pricing algorithms.
Cosmetic formulators and researchers scrape ingredient lists to identify trending active compounds in Asian skincare.
Fashion analysts track new arrivals and review velocity across apparel categories to predict upcoming seasonal trends.
Agencies correlate review sentiment with specific skin types and concerns to build detailed consumer personas.
Machine learning teams use structured product descriptions, images, and sizing data to train fashion recommendation engines.
"YesStyle aggregates the fragmentation of Asian beauty and fashion into a single catalogue, but parsing complex sizing charts and ingredient lists requires dedicated infrastructure."
Most teams underestimate the investment required: reliable YesStyle scraping requires residential proxies, geo-targeted sessions, JavaScript rendering for dynamic pricing, and complex table parsing for fashion sizing. DataFlirt absorbs that complexity so your engineers can focus on analysis.
Everything supported by our yesstyle.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 pools of residential ISP proxies across multiple regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
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 yesstyle.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from YesStyle is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
YesStyle displays different prices based on user location. We use region-specific residential proxies and configure explicit session headers to ensure the data matches your target market accurately.
Yes. YesStyle sizing charts are notoriously unstructured. We use heuristic parsing algorithms to extract these HTML tables and normalise them into structured JSON arrays mapping measurements to sizes.
Yes. We extract complete ingredient lists, cruelty-free certifications, and specific skin concern tags from beauty product pages.
We support daily, weekly, or custom cadences. For flash sales and dynamic pricing, we can configure high-frequency monitoring on specific SKU sets.
Yes. Review records include the standard text and rating, plus user-specific metadata like skin type, skin tone, and age group when provided.
Absolutely. We provide a sample run of up to 500 SKUs as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or a continuous pricing feed across 300K SKUs, we scope, build, and operate the pipeline. Tell us what you need.
