We extract footwear specifications, activewear catalogues, dynamic inventory, sizing availability, and pricing signals from Asics. Delivered as clean JSON, CSV, or Parquet to your warehouse.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Footwear Specs objects from asics.com. All fields typed and schema-versioned.
"sku": "1011B548-400", "model_name": "GEL-KAYANO 30", "pronation_type": "Overpronation", "heel_drop_mm": 10, "weight_grams": 303, "cushion_level": "Maximum", "technology_tags": "['FF BLAST PLUS ECO', 'PureGEL technology']", "base_price": 160.0
| # | sku | model_name | gender | category | pronation_type | cushion_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Apparel Data objects from asics.com. All fields typed and schema-versioned.
"sku": "2011C345-001", "product_name": "Core Short Sleeve Top", "category": "Shirts", "gender": "Men", "fit_type": "Regular", "material_composition": "100% Polyester", "colour_name": "Performance Black", "price": 25.0
| # | sku | product_name | category | gender | fit_type | material_composition |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from asics.com. All fields typed and schema-versioned.
"sku": "1011B548-400", "size": "10.5", "width": "Standard", "in_stock": true, "stock_level": "High", "base_price": 160.0, "sale_price": 120.0, "oneasics_price": 110.0
| # | sku | variant_id | size | width | in_stock | stock_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from asics.com. All fields typed and schema-versioned.
"review_id": "REV-938471", "sku": "1011B548-400", "rating": 5, "review_title": "Best stability shoe", "verified_buyer": true, "helpful_votes": 14, "fit_rating": "True to size", "review_date": "2026-03-12"
| # | review_id | sku | rating | review_title | review_body | reviewer_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locations objects from asics.com. All fields typed and schema-versioned.
"store_id": "STR-402", "store_name": "Asics Flagship London", "store_type": "Flagship", "city": "London", "zip_code": "W1C 2QA", "latitude": 51.5138, "longitude": -0.1422, "services_offered": "['Run Analysis', 'Click & Collect']"
| # | store_id | store_name | store_type | address_line1 | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Asics scraper handles every layer of the platform: dynamic sizing grids, OneASICS member pricing, specialised footwear specifications, and store locator data.
Extract pronation type, heel drop, weight, cushion level, and surface type for performance running models.
Capture real-time stock availability across all size and width combinations for every SKU variant.
Track base price, sale price, and exclusive OneASICS member pricing across the entire catalogue.
Extract proprietary technology badges like FF BLAST, PureGEL, and GUIDANCE LINE from product descriptions.
Aggregate customer reviews, star ratings, fit feedback, and verified purchase flags for sentiment analysis.
Extract physical retail locations, operating hours, and in-store services offered globally.
Scrape local catalogues and pricing from asics.com, asics.co.uk, asics.co.jp, and other regional domains.
Capture material composition, fit type, and care instructions for activewear and sporting goods.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide category URLs, product lines, or region targets. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for asics.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.
Retail sites deploy aggressive anti-scraping measures during product drops. Here is how we stay resilient.
Retail CDNs block generic data center IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management.
Inventory status by size and width is dynamically rendered. We run full Playwright browser sessions to trigger API calls and capture accurate stock states.
Our selector strategy uses multiple fallback chains per field so a seasonal layout change does not break your data pipeline.
For large catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs.
Every run emits structured logs to our observability stack. We alert on null-rate spikes and schema drift.
Sportswear brands monitor Asics pricing, discount velocity, and seasonal clearance strategies.
Retail analysts track out-of-stock rates across sizes to estimate sales velocity and production issues.
Footwear designers analyse specification trends like heel drop variations and cushion levels across product lines.
Consumer research teams mine review text and fit ratings to understand sizing consistency and material durability.
Brands track third-party retailers against official Asics pricing to identify minimum advertised price violations.
ML teams use structured footwear specifications to train recommendation engines and categorisation models.
"Asics provides the definitive dataset for performance running footwear specifications, but none of it is queryable unless you build the pipeline."
Most teams underestimate the investment required: reliable retail scraping requires residential proxies, full JavaScript rendering for sizing grids, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our asics.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. Playwright handles JavaScript rendering and interaction flows for sizing grids.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About asics.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We capture base prices, standard sale prices, and exclusive OneASICS member pricing tags directly from the product listings.
Our Playwright integration interacts with the sizing grid to hydrate inventory status for every size and width combination, ensuring accurate stock signals.
Yes. We support asics.com, asics.co.uk, asics.co.jp, and other regional domains to provide localized pricing and catalogue data.
Yes. We parse product descriptions and specification tables to extract proprietary technologies like FF BLAST, PureGEL, and AHAR outsole details.
Pipelines can be configured for daily catalogue refreshes or high-frequency hourly checks for critical inventory and pricing signals.
Absolutely. We provide a sample run of up to 500 SKUs to validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off product catalogue dump or a continuous inventory monitoring feed we scope, build, and operate the pipeline. Tell us what you need.
