We extract sneaker catalogs, activewear pricing, size-level stock depth, and marketplace seller intelligence from Netshoes. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 Listings objects from netshoes.com.br. All fields typed and schema-versioned.
"sku": "D12-3456-006", "title": "Tênis Nike Revolution 6 Next Nature Masculino", "brand": "Nike", "category": "Running", "gender": "Masculino", "colour": "Preto+Branco", "material": "Mesh", "warranty": "Contra defeito de fabricação"
| # | sku | title | brand | category | department | gender |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Sizes objects from netshoes.com.br. All fields typed and schema-versioned.
"sku": "D12-3456-006", "base_price": 399.99, "discount_price": 299.99, "pix_price": 269.99, "ncard_price": 259.99, "discount_pct": 25, "available_sizes": "['39', '40', '41', '42']", "out_of_stock_sizes": "['38', '43', '44']"
| # | sku | base_price | discount_price | pix_price | ncard_price | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from netshoes.com.br. All fields typed and schema-versioned.
"review_id": "REV-982736", "sku": "D12-3456-006", "rating": 5, "title": "Excelente custo benefício", "body": "Tênis muito leve e confortável para corridas curtas.", "date": "2026-03-14", "recommended": true, "helpful_votes": 42
| # | review_id | sku | rating | title | body | date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Seller Data objects from netshoes.com.br. All fields typed and schema-versioned.
"sku": "D12-3456-006", "sold_by": "Netshoes", "delivered_by": "Netshoes", "seller_rating": 4.8, "is_official_store": true, "shipping_estimate_days": 3, "return_policy": "30 days free return"
| # | sku | sold_by | delivered_by | seller_rating | seller_id | is_official_store |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Search Results objects from netshoes.com.br. All fields typed and schema-versioned.
"keyword": "chuteira futsal", "position": 1, "sku": "H23-9876-012", "sponsored": false, "brand": "Penalty", "price": 149.9, "pix_price": 134.91, "rating": 4.6
| # | keyword | position | sku | title | brand | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Netshoes scraper maps the entire sporting goods catalog, handling complex variant matrices, dynamic Pix pricing, and third-party marketplace sellers with full anti-bot circumvention.
Extract titles, descriptions, materials, categories, and high-resolution image URLs across all sporting goods and apparel departments.
Map complex parent-child relationships to capture exact stock availability for every colourway and shoe size combination.
Capture standard list prices alongside conditional discounts like Pix payments and N Card exclusive pricing tiers.
Differentiate between items sold directly by Netshoes and third-party sellers. Extract seller names, ratings, and fulfillment methods.
Paginate through user reviews to extract star ratings, written feedback, recommendation flags, and helpful vote counts.
Monitor entire brand landing pages or category structures to track new product launches and assortment changes.
Track organic and sponsored search positions for high-value keywords like 'tênis de corrida' or 'camisa do flamengo'.
Monitor size-level stock depth to understand depletion rates and identify fast-moving inventory.
Configure pipelines to run daily, weekly, or hourly. Receive clean data directly in your warehouse.
Brief in. Clean data out.
Provide target categories, brand URLs, or search keywords. We design the extraction schema to match your requirements.
We configure Playwright crawlers, Brazilian residential proxy rotation, and session management for netshoes.com.br.
Schema validation, null-rate checks, and variant mapping verification before launching the full production run.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or via Webhook on the agreed schedule.
Brazilian eCommerce platforms deploy strict rate limits and regional blocking. Here is how our infrastructure maintains continuous extraction.
Netshoes restricts access from non-LATAM data centers. We route all requests through high-reputation Brazilian residential ISP proxies, ensuring our crawlers appear as legitimate local shoppers.
Pricing and size availability on Netshoes load dynamically via JavaScript. We use Playwright to execute page scripts, wait for network idle states, and capture the fully hydrated DOM.
A single sneaker model can have dozens of size and colour combinations. Our parsers map these nested JSON payloads into flat, queryable database rows for every distinct SKU.
For massive catalog monitoring, we maintain state across runs. Our system only outputs records where prices, stock, or seller details have changed, drastically reducing your storage costs.
We monitor pipeline health 24/7. If Netshoes deploys a layout change, our alerting stack flags the schema drift and our engineers deploy a fix before your next scheduled delivery.
Sporting goods retailers track Netshoes base prices, Pix discounts, and N Card promotions to adjust their own pricing strategies.
Global sportswear brands audit Netshoes marketplace sellers to ensure minimum advertised price compliance and identify unauthorized distributors.
Resellers monitor stock levels for limited-edition sneaker drops across specific sizes to identify purchasing opportunities.
Analysts track review velocity and size-level stock depletion rates to model consumer demand for specific apparel categories.
Agencies monitor third-party seller performance, shipping estimates, and buybox ownership to optimize client positioning.
Retail buyers scrape category structures to identify trending brands and missing product lines in their own catalogs.
"Netshoes holds the definitive dataset for Brazilian sporting goods pricing, but accessing size-level stock depth requires infrastructure built for scale."
Extracting data from Netshoes involves navigating complex single-page application hydration, regional IP blocking, and deeply nested size and colour variant matrices. DataFlirt manages these technical hurdles natively. Your engineering team receives clean, normalised JSON rather than spending cycles maintaining fragile DOM selectors and proxy pools.
Everything supported by our netshoes.com.br 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 manages crawl orchestration and retry logic, while Playwright handles JavaScript execution to load Netshoes pricing widgets and variant matrices.
We maintain dedicated pools of Brazilian residential IPs to bypass region-based blocking and rate limits imposed by local CDNs.
Pipelines execute on AWS infrastructure with Airflow handling scheduling dependencies. All pipeline state is stored in managed PostgreSQL clusters.
Data delivered to where your team already works — no new tooling required.
About netshoes.com.br scraping, legality, and pipeline operations.
Ask us directly →Yes. Our parsers capture the base list price alongside all conditional pricing tiers, including Pix discounts and Netshoes Card exclusive offers.
We map the entire variant matrix for each product. The output explicitly lists available sizes and out-of-stock sizes as distinct arrays within the SKU record.
Yes. Every record includes 'sold_by' and 'delivered_by' fields, allowing you to filter for first-party inventory versus marketplace sellers.
Yes. We route all extraction requests through localized Brazilian residential proxies to ensure uninterrupted access and accurate localized pricing.
Pipelines can be configured to run daily, hourly, or continuously depending on your requirements and the size of the target catalog.
We begin tracking historical changes from the moment your pipeline is commissioned. Every run is timestamped, allowing you to build time-series pricing models.
Yes. We run a sample extraction of up to 500 SKUs or specific category pages to validate schema alignment before you commit to a production pipeline.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily sweep of the running shoe category or continuous price monitoring across 500K SKUs, we scope, build, and operate the pipeline. Tell us your requirements.
