We extract sneaker drops, apparel catalogues, sizing availability, and pricing signals from newbalance.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 Catalogue objects from newbalance.com. All fields typed and schema-versioned.
"sku": "M990GL6", "style_code": "M990V6-412", "product_name": "MADE in USA 990v6", "category": "Shoes", "gender": "Men", "price": 199.99, "currency": "USD", "colour": "Grey with silver", "materials": "Pigskin/mesh"
| # | sku | style_code | product_name | category | sub_category | gender |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Inventory & Sizing objects from newbalance.com. All fields typed and schema-versioned.
"sku": "M990GL6", "size": "10.5", "width": "Standard (D)", "in_stock": true, "stock_level": 14, "low_stock_warning": false, "updated_at": "2026-10-24T08:12:00Z"
| # | sku | size | width | in_stock | stock_level | backorder_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Fit Data objects from newbalance.com. All fields typed and schema-versioned.
"review_id": "RV-884921", "sku": "M990GL6", "rating": 5, "title": "Classic comfort", "body": "Best iteration of the 990 yet. Excellent arch support.", "fit_rating": "True to size", "date_posted": "2026-09-14"
| # | review_id | sku | reviewer_name | rating | title | body |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our New Balance scraper handles the complexities of footwear retail: dynamic stock matrices, aggressive anti-bot layers, and high-frequency drop monitoring.
Extract footwear, apparel, and accessories across all gender and age categories. Mapped with internal SKUs and style codes.
Track stock depth across complex sizing matrices — including half sizes and specific widths from Narrow to X-Wide.
High-frequency scraping for limited edition releases and collaborations. Capture launch times, queue status, and immediate sell-outs.
Link parent models to all available colourways, extracting specific style codes and associated high-resolution image galleries.
Monitor base pricing, seasonal discounts, and clearance markdowns across global New Balance storefronts.
Extract user-submitted reviews, overall ratings, and aggregate fit indices to understand sizing accuracy.
Brief in. Clean data out.
Provide target categories, style codes, or geographic regions. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for newbalance.com.
Schema validation, null-rate checks, inventory-outlier detection, and sample payloads before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Sneaker sites deploy aggressive anti-bot measures to stop scalpers. We bypass these to deliver clean commercial data.
Sneaker retailers use strict bot protection. Our residential proxies and TLS fingerprint spoofing bypass these protections without triggering IP blocklists or CAPTCHA loops.
Stock levels for specific size/width combinations load via asynchronous API calls. Playwright intercepts these XHR requests to capture true availability rather than cached HTML.
During limited releases, caching layers obscure live stock. We route requests through un-cached endpoints to capture real-time sell-outs and queue statuses.
New Balance alters pricing and catalogue availability based on IP location. We use region-specific residential nodes to extract localised data for the US, UK, EU, and Asian markets.
Frontend frameworks change during major sales events. Our selectors use multi-layer fallbacks — CSS, XPath, and internal JSON state extraction — ensuring continuous data flow.
Apparel brands track New Balance's pricing strategies, clearance cadences, and discount depths across product lines.
Retail analysts monitor stock depth and sell-through rates on core models to gauge manufacturing output and demand.
Secondary market platforms correlate retail stock levels and drop sell-out times with secondary market premiums.
Fashion researchers analyse the proliferation of specific colour palettes and material choices across the seasonal catalogue.
Product teams mine review data for fit indices and width complaints to inform their own footwear manufacturing.
Distributors verify that third-party retailers maintain minimum advertised pricing relative to the official New Balance D2C site.
"Sneaker inventory data is highly volatile and heavily guarded. Extracting it reliably requires enterprise-grade proxy infrastructure, not just a simple HTTP client."
Most teams underestimate the friction of scraping footwear brands. Aggressive anti-bot layers, complex size-width matrices, and dynamic API responses break standard crawlers. DataFlirt absorbs that complexity, delivering structured catalogue data so your engineers can focus on analysis rather than unblocking IPs.
Everything supported by our newbalance.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.
Orchestration via Scrapy. Playwright handles JavaScript rendering, XHR interception for inventory APIs, and interaction flows to bypass bot checks.
ISP-grade residential IPs bypass Datadome and Akamai protections. Rotation occurs per-request with sticky sessions for localized pricing.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. State is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About newbalance.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available catalogue, pricing, and inventory information is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and request timing modelled on human behaviour to bypass Datadome and Akamai protections.
Yes. We configure high-frequency polling on specific style codes during release windows, bypassing edge caches to capture real-time sell-out data.
Yes. New Balance is known for extensive width options. We extract availability matrices covering all sizes and widths (Narrow, Standard, Wide, X-Wide) for every SKU.
Yes. We route requests through geographically appropriate residential proxies to extract localized pricing, currency, and stock availability for US, UK, EU, and Asian markets.
Our packages start at defined category extractions (e.g., all men's running shoes) with daily delivery. For full global catalogue tracking, we price based on volume and frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full apparel catalogue dump or continuous stock monitoring for footwear drops — we scope, build, and operate the pipeline. Tell us what you need.
