We extract shoe specifications, pricing signals, size-level stock, and review data from Altra Running. 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 Models objects from altrarunning.com. All fields typed and schema-versioned.
"product_id": "AL0A82C5", "name": "Lone Peak 8", "category": "Trail Running", "gender": "Men", "price": 140.0, "weight_oz": 10.7, "stack_height_mm": 25, "drop_mm": 0, "cushion_level": "Moderate"
| # | product_id | name | category | gender | price | list_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Inventory & Sizes objects from altrarunning.com. All fields typed and schema-versioned.
"sku": "AL0A82C5-000-105", "parent_id": "AL0A82C5", "colourway": "Black / Grey", "size": "10.5", "width": "Regular", "in_stock": true, "stock_quantity": 42, "price": 140.0
| # | sku | parent_id | colourway | size | width | in_stock |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Reviews & Ratings objects from altrarunning.com. All fields typed and schema-versioned.
"review_id": "REV-982341", "product_id": "AL0A82C5", "rating": 5, "title": "Best trail shoe yet", "body": "The grip on the Lone Peak 8 is fantastic.", "date": "2025-08-14", "verified_buyer": true, "fit_rating": "True to size"
| # | review_id | product_id | author | rating | title | body |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Technologies & Specs objects from altrarunning.com. All fields typed and schema-versioned.
"product_id": "AL0A82C5", "midsole_tech": "Altra EGO", "outsole_tech": "MaxTrac", "upper_material": "Ripstop mesh", "footshape_fit": "Original", "cushion_level": "Moderate", "surface": "Trail"
| # | product_id | midsole_tech | outsole_tech | upper_material | footshape_fit | cushion_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from altrarunning.com. All fields typed and schema-versioned.
"sku": "AL0A82C5-000-105", "current_price": 104.95, "original_price": 140.0, "discount_pct": 25, "is_clearance": true, "promo_eligible": false, "currency": "USD"
| # | sku | current_price | original_price | discount_pct | is_clearance | promo_eligible |
|---|---|---|---|---|---|---|
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Our pipeline handles the complex variant structures of footwear eCommerce. We map every size, width, and colourway combination to its real-time price and stock status.
Extract every combination of shoe size, width, and colourway linked to the parent product model.
Capture stack height, drop, weight, FootShape fit type, and midsole technology specific to Altra models.
Monitor stock availability at the SKU level. Know exactly which sizes are selling out.
Track MSRP, current price, and clearance discounts across all colourways and sizes.
Extract customer reviews, star ratings, and specific feedback on fit and comfort.
Collect high-resolution image URLs for every colourway variant.
Scrape localised Altra storefronts to compare pricing and availability across geographies.
Receive only updated records. Track price drops and out-of-stock events as they happen.
Crawl entire categories like Trail, Road, or Hiking to maintain a complete product catalogue.
Brief in. Clean data out.
Provide target categories or specific shoe models. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for altrarunning.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Modern eCommerce sites rely heavily on JavaScript for variant selection. Here is how we ensure accurate extraction.
Footwear sites load pricing and stock data dynamically based on the selected size and colour. We use Playwright to execute these scripts and extract the underlying JSON product data arrays.
We route requests through US residential IPs and manage TLS fingerprints to avoid automated blocks from standard eCommerce protection layers.
Product specifications are often formatted inconsistently. Our pipeline cleans and normalises measurements like weight and stack height into standard numeric fields.
We maintain state across runs. When a specific size goes out of stock or drops in price, we emit a diff record immediately.
We traverse infinite scroll and paginated review sections to capture the entire historical corpus of customer feedback.
Footwear brands track Altra's pricing, discounts, and new model launches to adjust their own market positioning.
Retailers analyse size-level stockout rates to optimise their purchasing decisions for zero-drop footwear.
Brands monitor direct-to-consumer pricing to ensure alignment with wholesale channel agreements.
R&D teams mine review data to identify common fit issues or praise for specific midsole technologies.
Analysts track the growth of specific categories like max-cushion trail shoes over time.
Retailers ingest competitor price drops on clearance models to automatically adjust their own prices.
"Altra's specific technical specifications, like zero drop and FootShape fits, require precise schema extraction to compare against standard footwear brands."
Extracting data from modern eCommerce storefronts requires handling complex variant structures where price and availability change per size and colour. DataFlirt manages the JavaScript execution and proxy rotation so you receive normalised, analytics-ready datasets without maintaining internal scraping infrastructure.
Everything supported by our altrarunning.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 executes JavaScript to hydrate dynamic variant pricing and stock data.
We maintain pools of residential proxies to bypass bot mitigation layers. Rotation happens per request to ensure high success rates.
Pipelines run on AWS infrastructure. 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 altrarunning.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and review data is generally permissible. DataFlirt extracts only public information and does not bypass authentication walls to access personal user data.
We execute the site's JavaScript to map every size and colourway combination to its specific SKU, price, and stock status, delivering a flattened or nested record for each variant.
Pipelines can be configured to run daily or hourly depending on your requirements. We track stock changes at the SKU level.
Yes. We parse the product description and specifications sections to normalise data points like stack height, drop, weight, and FootShape fit type.
Yes. We traverse all review pagination to extract the full text, star rating, verified buyer status, and specific fit feedback.
We deliver data in JSON, CSV, and Parquet formats directly to S3, BigQuery, or via Webhook for real-time ingestion.
We begin tracking price history from the day your pipeline is commissioned. We maintain a time-series record of all price changes and stockouts.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily catalogue sync or hourly inventory monitoring across all SKUs, we build and operate the pipeline. Tell us what you need.
