We extract footwear variants, sizing availability, colourways, technical specifications, and user reviews from Hoka. 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 Footwear Products objects from hoka.com. All fields typed and schema-versioned.
"sku": "1123157", "product_name": "Clifton 9", "category": "Men's Road Running", "price": 145.0, "currency": "USD", "available_colours": "['Black / White', 'Ceramic / Evening Primrose']", "heel_to_toe_drop_mm": 5.0, "weight_g": 248
| # | sku | product_name | category | sub_category | price | currency |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Inventory & Sizing objects from hoka.com. All fields typed and schema-versioned.
"sku": "1123157", "colour_id": "BBLC", "size": "10.5", "width": "Wide", "in_stock": true, "stock_level": "low_stock", "price": 145.0, "last_checked": "2024-02-28T14:22:10Z"
| # | sku | colour_id | size | width | in_stock | stock_level |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Technical Specifications objects from hoka.com. All fields typed and schema-versioned.
"sku": "1123157", "best_for": "['Everyday Run', 'Walking']", "midsole_compound": "CMEVA", "vegan": true, "heel_to_toe_drop_mm": 5.0, "stack_height_heel_mm": 32.0, "stack_height_forefoot_mm": 27.0
| # | sku | best_for | features | upper_material | midsole_compound | outsole_type |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews & Ratings objects from hoka.com. All fields typed and schema-versioned.
"review_id": "REV-98213", "sku": "1123157", "rating": 5, "title": "Like walking on clouds", "fit_rating": "True to size", "comfort_rating": 5, "recommended": true
| # | review_id | sku | reviewer_name | rating | title | body |
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Complete list of extractable fields for Apparel & Accessories objects from hoka.com. All fields typed and schema-versioned.
"sku": "1123712", "product_name": "Glide Short Sleeve", "category": "Men's Apparel", "price": 45.0, "currency": "USD", "fit_type": "Slim", "materials": "['100% Recycled Polyester']"
| # | sku | product_name | category | gender | price | currency |
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Our Hoka scraper handles the entire product taxonomy: footwear listings, apparel variants, technical specifications, dynamic inventory states, and user reviews.
Extract product titles, descriptions, categories, pricing, and image URLs mapped perfectly to specific colourways.
Capture heel-to-toe drop, weight, stack height, stability ratings, and cushion types directly from the product data.
Monitor size-level and width-level inventory states. Identify stockouts and backorder dates instantly.
Link specific SKUs and product images to their respective colour IDs and marketing names.
Extract full text reviews, star ratings, helpful votes, and specific metrics like fit and comfort ratings.
Scrape clothing and accessory metadata, including materials, care instructions, and fit types.
Support for localised Hoka storefronts including US, UK, EU, and AU regions with native currency pricing.
Bypass strict Datadome protections using residential IP rotation and sophisticated TLS fingerprinting.
Configure continuous pipelines that only emit changed records for pricing and stock updates.
Brief in. Clean data out.
Provide target categories, regional storefronts, and update frequency requirements.
We configure Playwright crawlers, Datadome bypass mechanisms, and residential proxy rotation.
Schema validation, variant mapping checks, and null-rate monitoring before full launch.
Structured data pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Footwear sites use aggressive rate-limiting and Datadome to block inventory scraping. Here is how our infrastructure handles it.
Hoka employs Datadome to prevent automated access. We bypass this using ISP-grade residential proxies, perfect TLS fingerprinting, and natural request timing patterns.
Size and colour combinations are heavily JavaScript-rendered. We use full Playwright browser sessions to trigger lazy-loads and hydrate dynamic inventory widgets.
We route requests through geographically specific residential proxies to extract accurate, localised pricing and stock levels for different international storefronts.
Our extraction logic relies on multiple fallback chains including CSS selectors, XPath, and JSON-LD data to ensure pipeline stability during site updates.
We compute hashes for inventory records, pushing only the differences to your warehouse. This reduces compute overhead and downstream processing load.
Track Hoka pricing against competing brands like Brooks and On Running to optimise your own pricing strategy.
Monitor stock depth by size and width to understand production volumes and inventory allocation.
Audit unauthorised discounting on primary SKUs by cross-referencing official catalogue pricing.
Analyse technical specifications and review sentiment to inform future footwear design and material choices.
Track category placement, new arrivals, and promotional banners to understand digital merchandising tactics.
Correlate specific colourway stockouts with broader market demand to forecast upcoming fashion trends.
"Hoka's technical specifications and size-level stock data offer critical market intelligence, provided you can bypass their aggressive anti-scraping layers."
Extracting data from modern footwear brands requires more than simple HTTP requests. Hoka relies heavily on JavaScript for variant rendering and Datadome for bot mitigation. DataFlirt manages the residential proxies, browser fingerprinting, and dynamic DOM parsing required to deliver clean, structured catalogue data directly to your warehouse.
Everything supported by our hoka.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.
We use Playwright to execute JavaScript and hydrate dynamic inventory widgets, paired with advanced TLS fingerprint spoofing to bypass bot detection.
Requests are routed through ISP-grade residential proxies. Rotation happens per-request to prevent IP bans and maintain access to localised pricing.
Pipelines run on AWS Lambda and ECS. Apache Airflow handles scheduling and dependency management, ensuring reliable data delivery.
Data delivered to where your team already works — no new tooling required.
About hoka.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We utilise ISP-grade residential proxies, realistic browser fingerprinting via Playwright, and natural request timing patterns to bypass Datadome and maintain continuous access.
We support multiple regional storefronts including hoka.com/en/us, /en/gb, /en/eu, and /en/au, capturing localised pricing and inventory data.
We can configure daily full-catalogue refreshes or high-frequency polling (sub-60 minutes) for a targeted list of high-priority SKUs.
Yes. Our pipeline systematically iterates through all available colour, size, and width combinations to capture accurate stock status for every variant.
We typically start with a defined category or SKU list. Pricing scales based on extraction volume, frequency, and custom schema requirements.
Yes. We provide a sample extraction of up to 100 SKUs during the scoping phase to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Need a one-time catalogue dump or continuous stock monitoring? We build and operate the pipeline. Tell us your requirements.
