We extract orthotic footwear catalogues, Medicare A5500 compliance flags, multi-width sizing matrices, and inventory levels from Propet USA. 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 Info objects from propetusa.com. All fields typed and schema-versioned.
"sku": "WCA049M", "title": "Tour Walker Strap", "price": 94.95, "medicare_a5500_approved": true, "orthotic_friendly": true, "machine_washable": false, "closure_type": "Hook and Loop", "material": "Full grain leather"
| # | sku | title | price | category | medicare_a5500_approved | orthotic_friendly |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sizing & Widths objects from propetusa.com. All fields typed and schema-versioned.
"sku": "WCA049M-8W", "base_sku": "WCA049M", "size": "8", "width_label": "Wide", "width_code": "D", "inventory_status": "in_stock", "stock_quantity": 42
| # | sku | base_sku | size | width_label | width_code | inventory_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variants & Colours objects from propetusa.com. All fields typed and schema-versioned.
"sku": "WCA049M-BLK", "colour_name": "Black", "hex_code": "#000000", "image_urls": "['https://example.com/img1.jpg', 'https://example.com/img2.jpg']", "available_sizes": "['6', '6.5', '7', '7.5', '8']", "available_widths": "['Narrow', 'Medium', 'Wide', 'X-Wide', 'XX-Wide']"
| # | sku | colour_name | hex_code | image_urls | swatch_url | available_sizes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from propetusa.com. All fields typed and schema-versioned.
"review_id": "REV-98231", "sku": "WCA049M", "rating": 5, "reviewer_name": "Jane D.", "review_date": "2023-11-14", "verified_buyer": true, "fit_rating": "True to size", "comfort_rating": 5
| # | review_id | sku | rating | reviewer_name | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Categories & Collections objects from propetusa.com. All fields typed and schema-versioned.
"category_name": "Walking Shoes", "sub_category": "Strap Sneakers", "collection_name": "Tour Walker", "gender": "Women", "activity_type": "Walking", "product_count": 24, "breadcrumbs": "['Home', 'Women', 'Walking Shoes']"
| # | category_name | sub_category | collection_name | url | product_count | breadcrumbs |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Propet USA catalogues feature highly dimensional sizing matrices and specific medical compliance flags. Our pipeline normalises this structure into flat, queryable tables.
Extract inventory and pricing arrays across all 5 width profiles: Narrow (AA), Medium (B), Wide (D), X-Wide (2E), and XX-Wide (4E).
Capture therapeutic compliance data, identifying SKUs approved for diabetic footwear reimbursement under Medicare code A5500.
Extract features like double insoles, removable footbeds, and orthotic-friendly indicators for every shoe model.
Map base SKUs to all colour options, capturing specific swatch images, hex codes, and colour-specific inventory states.
Monitor stock availability across the entire size and width matrix to detect out-of-stock patterns and restock velocities.
Track MSRP, current retail price, clearance flags, and promotional discounts across the entire catalogue.
Extract textual reviews, star ratings, and specific fit feedback (e.g., runs small, true to width) to analyse product reception.
Parse unstructured descriptions into structured fields for upper materials, sole types, closure mechanisms, and washability.
Run pipelines daily or weekly to maintain an updated mirror of Propet USA's catalogue and inventory state.
Brief in. Clean data out.
Specify target categories, collections, or the entire catalogue. We map the required attributes and sizing dimensions.
We configure crawlers to handle dynamic inventory loading, multi-dimensional size selectors, and proxy rotation.
We test the extraction against edge cases, ensuring all 5 width dimensions and Medicare flags are accurately captured.
Data is formatted into normalised JSON, CSV, or Parquet and pushed to your data warehouse or S3 bucket.
Extracting therapeutic footwear data is complex due to the sheer number of SKU variations. Here is how we ensure complete data capture.
A single Propet shoe style can have over 60 variations (12 lengths multiplied by 5 widths). Our pipeline iterates through every UI combination, extracting the specific SKU, barcode, and inventory state for each permutation, outputting a flattened, queryable table.
Stock levels and variant-specific prices load dynamically via frontend JavaScript. We use Playwright to execute these scripts, ensuring we capture the true availability state rather than static placeholder HTML.
Critical data like Medicare A5500 approval and double-insole construction often lives in unstructured description blocks or icon tooltips. We use regex and DOM parsing to extract these attributes into distinct boolean fields.
To extract thousands of variants without triggering anti-bot protections, we distribute requests across US residential proxies, inserting randomised delays to mimic standard browsing behaviour.
For daily inventory tracking, our pipeline compares current stock states against the previous run, emitting only the changed records. This reduces bandwidth and processing costs for downstream systems.
Competing therapeutic brands monitor Propet's pricing, width offerings, and Medicare-approved product lines to benchmark their own catalogues.
Retailers and distributors track stockout velocities across specific size and width combinations to optimise their wholesale purchasing models.
Brands track retail pricing across the site to ensure alignment with Minimum Advertised Price policies and promotional calendars.
Footwear designers analyse customer reviews and fit ratings to identify sizing inconsistencies and comfort issues in orthotic designs.
Healthcare analysts track the expansion of Medicare A5500 approved footwear lines to gauge market demand for diabetic care products.
Merchandisers analyse the distribution of available widths (Narrow to XX-Wide) to inform inclusivity strategies in their own product lines.
"Propet USA's catalogue represents the industry standard for therapeutic footwear sizing matrices, complex data requiring precise extraction."
Extracting orthotic footwear data requires handling multi-dimensional sizing arrays (length multiplied by up to five widths per SKU), Medicare compliance flags, and dynamic inventory states. DataFlirt manages the proxy rotation, JavaScript hydration, and schema normalisation so your engineers receive clean, structured tables.
Everything supported by our propetusa.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 the broad crawl orchestration while Playwright executes JavaScript to hydrate the multi-dimensional sizing matrices and inventory states.
Requests are routed through US-based residential IPs to prevent rate limiting and ensure access to accurate regional pricing and stock data.
Pipelines run on AWS infrastructure, managed by Apache Airflow for strict scheduling, dependency resolution, and SLA adherence.
Data delivered to where your team already works — no new tooling required.
About propetusa.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our pipeline iterates through the frontend matrix, extracting specific SKU codes, inventory levels, and prices for Narrow, Medium, Wide, X-Wide, and XX-Wide variations for every available length.
We parse product badges, specification lists, and description text to reliably extract the Medicare A5500 compliance flag, outputting it as a clean boolean field in the final dataset.
Pipelines can be scheduled daily, weekly, or at custom intervals. For inventory tracking, we recommend daily runs to capture stockout velocities and restock events accurately.
Yes. We paginate through the review sections, extracting textual feedback, star ratings, and structured fit data indicating if a shoe runs small, large, narrow, or wide.
Absolutely. While the native data is highly nested, we normalise it into flat CSV or Parquet files where each row represents a distinct size/width variant, ready for immediate analysis.
No. Wholesale pricing on Propet USA requires authenticated access to the dealer portal. We only extract publicly available retail pricing and MSRP data.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete catalogue export or daily inventory tracking across complex sizing matrices, we build and maintain the infrastructure. Tell us your requirements.
