We extract hardware specifications, subscription pricing, accessory compatibility, and inventory states from whoop.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 Hardware Specs objects from whoop.com. All fields typed and schema-versioned.
"sku": "HW-W4-BLK", "product_name": "Whoop 4.0 Sensor", "generation": "4.0", "battery_life": "Up to 5 days", "water_resistance": "IP68", "weight": "18g"
| # | sku | product_name | generation | sensor_type | battery_life | water_resistance |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Subscription Pricing objects from whoop.com. All fields typed and schema-versioned.
"region": "UK", "currency": "GBP", "monthly_plan_price": 27.0, "annual_plan_price": 229.0, "24_month_plan_price": 384.0, "trial_period_days": 30
| # | region | currency | monthly_plan_price | annual_plan_price | 24_month_plan_price | upfront_cost |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Bands & Accessories objects from whoop.com. All fields typed and schema-versioned.
"sku": "BND-SFT-ONYX", "accessory_name": "SuperKnit Band", "material": "SuperKnit", "colour": "Onyx", "compatibility": "Whoop 4.0", "price": 49.0, "stock_status": "IN_STOCK"
| # | sku | accessory_name | category | material | colour | clasp_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Apparel Data objects from whoop.com. All fields typed and schema-versioned.
"sku": "APP-BXR-BLK-M", "product_name": "Any-Wear Boxers", "garment_type": "Underwear", "gender": "Men", "size_options": "['S', 'M', 'L', 'XL', 'XXL']", "price": 34.0, "stock_status": "LOW_STOCK"
| # | sku | product_name | garment_type | gender | size_options | colour_options |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for International Localisation objects from whoop.com. All fields typed and schema-versioned.
"locale": "en-AU", "country_code": "AU", "currency": "AUD", "base_price": 379.0, "shipping_cost": 0.0, "estimated_delivery": "3-5 business days", "tax_included": true
| # | url | locale | country_code | currency | base_price | shipping_cost |
|---|---|---|---|---|---|---|
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Our Whoop scraper maps the entire product graph: hardware variations, Any-Wear apparel sizing, subscription pricing models, and real-time inventory states.
Extract bands, batteries, apparel, and sensors with complete metadata and variant mapping.
Capture dynamic pricing for monthly, annual, and 24-month commitments across all regions.
Track stock states and backorder shipping estimates for high-demand accessories.
Scrape localised storefronts to map currency conversions and regional price parity.
Map bands and garments to specific Whoop hardware generations.
Extract sensor details, battery capacity, and material compositions.
Track pricing logic for hardware plus subscription bundles.
Identify active discount codes, referral bonuses, and seasonal sales.
Run one-off exports or configure continuous pipelines at hourly cadences.
Normalise unstructured product descriptions into typed JSON fields.
Brief in. Clean data out.
Provide target locales and product categories. We design the extraction schema together.
We configure Scrapy and Playwright crawlers to handle whoop.com frontend rendering.
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 e-commerce sites rely heavily on client-side rendering. Here is how we ensure data accuracy and pipeline stability.
Whoop.com relies heavily on client-side rendering for product configuration. We use Playwright to execute JavaScript and capture the final DOM state.
Subscription costs vary by region. We route requests through residential proxies in specific target countries to capture accurate local pricing and tax structures.
Accessory availability fluctuates rapidly. Our pipelines can run at high frequency to detect restocks and backorder delays.
E-commerce platforms update layouts frequently. We implement fallback chains using CSS, XPath, and JSON-LD to prevent pipeline failure.
For continuous tracking, we hash field values and only deliver records that have changed, reducing downstream processing costs.
Fitness hardware brands monitor Whoop subscription tiers and hardware bundles to adjust their own pricing strategies.
Retailers analyse Whoop regional pricing and shipping estimates to understand geographical market penetration.
Analysts track out-of-stock rates on bands and battery packs to estimate production constraints.
Apparel manufacturers monitor Whoop Any-Wear garment releases and material choices to inform product development.
Marketing teams track seasonal discounts and trial period changes to benchmark customer acquisition offers.
Resellers use official accessory pricing to set baseline values for used Whoop bands and batteries on third-party marketplaces.
"Whoop operates a complex subscription-hardware model. Extracting accurate pricing requires parsing dynamic bundles across dozens of localised storefronts."
Building a reliable scraper for modern e-commerce architectures requires full JavaScript execution and geo-targeted proxies. DataFlirt manages the underlying infrastructure, anti-bot circumvention, and schema maintenance so your data engineering team can focus on downstream analytics rather than pipeline repairs.
Everything supported by our whoop.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 retry logic. Playwright executes JavaScript to render product configurators and dynamic pricing.
Geo-targeted ISP proxies allow us to bypass regional blocks and capture accurate localised pricing for international storefronts.
Pipelines run on AWS Lambda and ECS. Airflow manages scheduling and dependency resolution. State is persisted in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About whoop.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and accessory data is generally permissible. DataFlirt only extracts unauthenticated public data. We do not scrape personal health metrics, user dashboards, or circumvent authentication.
Yes. We monitor the monthly, annual, and 24-month subscription tiers across different regional storefronts to capture pricing adjustments and trial offers.
We route requests through residential proxies located in the target country to ensure the storefront serves the correct local currency and tax structure.
Yes. We scrape the full apparel catalogue, including sizing options, fabric compositions, colour variants, and compatibility with the Whoop sensor.
For high-demand items like battery packs or limited-edition bands, pipelines can be configured to run hourly to detect restocks or backorder delays.
Our managed service includes schema maintenance. If DOM selectors break due to a layout change, our alerting system flags the anomaly, and our engineers update the extraction logic to restore the pipeline.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or continuous tracking of subscription tiers and inventory states. Tell us what you need.
