We extract technical footwear specifications, inventory depths, pricing signals, and product reviews from inov-8.com. 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 Specs objects from inov-8.com. All fields typed and schema-versioned.
"product_id": "MUDCLAW-300", "name": "MUDCLAW 300", "drop_mm": 6, "lug_depth_mm": 8, "weight_g": 300, "fit_scale": 2, "outsole_material": "G-GRIP Graphene"
| # | product_id | name | product_type | drop_mm | lug_depth_mm | weight_g |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Inventory & Pricing objects from inov-8.com. All fields typed and schema-versioned.
"sku": "000976-BKRD-S-01", "colour": "Black / Red", "size_uk": "9.5", "price": 130.0, "list_price": 140.0, "currency": "GBP", "in_stock": true
| # | product_id | sku | colour | size_uk | size_us | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Customer Reviews objects from inov-8.com. All fields typed and schema-versioned.
"review_id": "REV-892144", "product_id": "TRAILFLY-G-270", "rating": 5, "review_title": "Excellent grip on wet rock", "review_date": "2026-03-14", "verified_buyer": true, "helpful_votes": 12
| # | review_id | product_id | author_name | rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Apparel Specs objects from inov-8.com. All fields typed and schema-versioned.
"product_id": "STORMSHELL-FZ", "name": "STORMSHELL WATERPROOF JACKET", "category": "Jackets", "waterproof_rating": "20,000 HH", "breathability_rating": "20,000 B-1", "weight_g": 174, "fit_type": "Athletic"
| # | product_id | name | category | material_composition | fit_type | breathability_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Categories objects from inov-8.com. All fields typed and schema-versioned.
"category_id": "CAT-TRAIL-RUNNING", "name": "Trail Running Shoes", "url_slug": "/mens/trail-running-shoes", "parent_category": "Mens Footwear", "product_count": 42, "active_status": true, "meta_title": "Men's Trail Running Shoes | Inov-8"
| # | category_id | name | url_slug | parent_category | product_count | description |
|---|---|---|---|---|---|---|
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Our Inov-8 scraper handles every layer of the platform. We extract technical specifications, size and colour matrices, and inventory levels with full JavaScript rendering and session management.
Capture drop metrics, lug depth, weight, and the proprietary 1-5 fit scale directly from product description blocks.
Identify models featuring G-Grip outsoles and G-Fly midsoles to map material usage across the catalogue.
Extract stock availability across complex size and colour matrices to track depletion rates at the SKU level.
Monitor base prices, sale discounts, and clearance markdowns across multiple regional storefronts.
Compile customer feedback, star ratings, and verified purchase status to analyse product durability and performance.
Scrape localised pricing and inventory from the UK, US, and EU subdomains using region specific IP proxies.
Extract hydrostatic head ratings, breathability scores, and fabric composition for jackets, shorts, and base layers.
Run continuous pipelines at daily cadences with change detection diffing to capture only new inventory states.
Collect high resolution product images, 360 degree views, and technical diagrams for every colourway.
Brief in. Clean data out.
Provide target categories, product lists, or regional domains. We design the extraction schema together.
We configure Playwright crawlers, proxy rotation, and session management to handle dynamic size matrices.
Schema validation, null-rate checks, and sample data review before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting technical sportswear data requires managing dynamic state. Here is how we build resilient pipelines.
Stock availability for specific size and colour combinations loads dynamically based on user interaction. We run full Playwright browser sessions to trigger state changes and capture exact inventory status for every SKU variant.
Inov-8 routes users to regional subdomains based on geolocation. We use residential ISP proxies in the UK, US, and EU to bypass redirects and capture accurate localised pricing and stock pools.
Technical specifications like drop and lug depth are often nested in unstructured description blocks. We use regular expressions and structured data extraction to normalise these metrics into consistent database columns.
We maintain a hash index of last seen inventory states per SKU. Subsequent runs only push diffs, reducing compute cost and downstream processing load. You receive a clean changelog of stock movements.
Every run emits structured logs to our observability stack. We alert on null-rate spikes or missing technical fields and respond before the data reaches your warehouse.
Footwear brands monitor pricing, discount strategies, and technical specification trends in the trail running market.
Retailers track stock depletion rates across specific sizes and colours to optimise their own purchasing decisions.
Analysts aggregate technical metrics like average lug depth and weight to identify shifts in consumer preferences for minimalist footwear.
Merchandisers analyse category depth and product lifecycle duration to inform their seasonal assortment strategies.
Brands track pricing across official and third party channels to enforce minimum advertised price policies.
Product teams aggregate customer reviews to identify durability issues or praise for specific materials like G-Grip.
"Inov-8 publishes some of the most detailed technical footwear specifications in the industry. Parsing G-Grip and lug depth metrics into a relational database requires a managed pipeline."
Extracting technical sportswear data requires more than simple HTTP GET requests. Colour and size matrices load dynamically, region specific pricing requires localised IP addresses, and stock levels change by the minute. DataFlirt handles the proxy rotation and JavaScript rendering so your engineering team can focus on data modelling.
Everything supported by our inov-8.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 and deduplication. Playwright handles JavaScript rendering for dynamic inventory matrices. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across UK and US regions. Rotation happens per request to ensure accurate regional pricing and avoid rate limits.
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 inov-8.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from inov-8.com is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and technical data. We do not extract personal data or circumvent authentication walls.
We use full Playwright browser sessions to interact with the page, triggering the JavaScript required to load stock availability for specific size and colour combinations.
We support the UK, US, and EU subdomains. We use region specific residential proxies to ensure we capture the correct localised pricing and inventory pools.
Full catalogue refreshes at daily cadence complete within a 2-4 hour window. We can configure more frequent runs for specific high priority SKUs if required.
We extract all available metrics including drop (mm), lug depth (mm), weight (g), the 1-5 fit scale, midsole materials, and outsole technologies like G-Grip.
Our packages start at full catalogue extraction with weekly delivery. We price based on delivery frequency and schema complexity. Contact us for a scoped quote.
Yes. We provide a sample run of up to 100 products 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 product catalogue dump or a continuous inventory monitoring feed, we scope, build, and operate the pipeline. Tell us what you need.
