We extract complete catalogue details, movement specifications, and dynamic pricing from Hamilton. 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 Watch Models objects from hamiltonwatch.com. All fields typed and schema-versioned.
"reference_number": "H70455733", "collection_name": "Khaki Field", "model_name": "Auto", "price": 645.0, "currency": "USD", "availability": "In Stock", "description": "The Khaki Field Auto is a rugged and reliable timepiece."
| # | reference_number | collection_name | model_name | price | currency | availability |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Movement & Caliber objects from hamiltonwatch.com. All fields typed and schema-versioned.
"reference_number": "H70455733", "caliber_model": "H-10", "movement_type": "Automatic", "power_reserve": "80 hours", "jewels": 25, "frequency": "21,600 bph", "open_case_back": true
| # | reference_number | caliber_model | movement_type | power_reserve | jewels | frequency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Case Specifications objects from hamiltonwatch.com. All fields typed and schema-versioned.
"reference_number": "H70455733", "case_material": "Stainless steel", "case_size_mm": 38.0, "thickness_mm": 11.5, "lug_width_mm": 20.0, "water_resistance": "10 bar (100m)", "crystal_type": "Sapphire"
| # | reference_number | case_material | case_size_mm | thickness_mm | lug_width_mm | water_resistance |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Dial & Strap objects from hamiltonwatch.com. All fields typed and schema-versioned.
"reference_number": "H70455733", "dial_colour": "Black", "numerals": "Arabic", "hands_lume": "Super-LumiNova", "strap_reference": "H6007041041", "strap_material": "Calf leather", "buckle_type": "Pin buckle"
| # | reference_number | dial_colour | numerals | hands_lume | strap_reference | strap_material |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Stock objects from hamiltonwatch.com. All fields typed and schema-versioned.
"reference_number": "H70455733", "region_code": "US", "price": 645.0, "currency": "USD", "stock_status": "Available", "boutique_exclusive": false, "scraped_at": "2026-05-12T09:14:00Z"
| # | reference_number | region_code | price | currency | stock_status | shipping_estimate |
|---|---|---|---|---|---|---|
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Our Hamilton scraper normalises complex specification tables across all collections, capturing movement details, case dimensions, and regional pricing grids with absolute precision.
Extract every unique SKU (e.g., H70455733) across the Khaki Field, Ventura, Jazzmaster, and American Classic collections.
Capture precise movement specifications including caliber codes (e.g., H-10, H-50), power reserve durations, jewel counts, and Nivachron spring presence.
Normalise case size, thickness, and lug width metrics into queryable decimal formats for direct database ingestion.
Extract case materials, crystal types (sapphire vs mineral), and water resistance ratings (bar/meters) for every model.
Track MSRP across different regional subdomains (US, UK, EU, JP) with exact currency mapping.
Monitor inventory status, shipping estimates, and boutique-exclusive flags to gauge supply chain health.
Link watch reference numbers to their default strap references, materials, and buckle specifications.
Extract URLs for primary product images, case-back views, and 360-degree viewer assets.
Run daily pipelines that output only the catalogue changes — new releases, price adjustments, or discontinued models.
Brief in. Clean data out.
Specify target regions, collections, or specific reference numbers. We design the extraction schema together.
We configure Scrapy / Playwright crawlers to navigate Hamilton's specific DOM structure and specification tables.
Schema validation, null-rate checks on critical fields like caliber and case size, and price normalisation.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Watch brand websites rely heavily on dynamic frontend frameworks and complex specification tables. Here is how we ensure data integrity.
Hamilton's product pages use JavaScript to load specification data and 3D assets. We use headless Playwright sessions to ensure all technical data is hydrated in the DOM before extraction.
Watch specification tables frequently change layout between collections (e.g., chronographs have different fields than three-handers). Our parsers use semantic mapping rather than rigid DOM paths to maintain data integrity.
Pricing and availability change based on the visitor's IP. We route requests through region-specific residential proxies to accurately capture local MSRP and stock status without triggering geofencing.
Instead of processing the entire 1,000+ SKU catalogue daily, our pipeline hashes each record and emits only the diffs — instantly highlighting price shifts or new model drops.
We convert raw text like '38 mm' or '10 bar (100m)' into strict numerical types, ensuring your warehouse receives clean integers and floats ready for analysis.
Secondary market dealers correlate official MSRP and stock status with grey market pricing to identify arbitrage opportunities.
Rival watchmaking groups track Hamilton's pricing tiers, caliber upgrades, and release cadences across key categories.
Watch enthusiast platforms and collection management apps ingest structured specifications to keep their reference databases current.
Authorised dealers analyse the full catalogue to optimise their inventory mix between high-turnover models and halo pieces.
Authentication services use precise case dimensions, lug widths, and caliber specifications as baseline truth for verifying timepieces.
Alternative asset funds track retail price inflation on mechanical models over time to model asset appreciation.
"Hamilton's digital catalogue holds precise horological specifications and regional pricing variations — structured extraction turns this into actionable market intelligence."
Extracting luxury watch data requires navigating dynamic specification tables, regional pricing overlays, and JavaScript-heavy viewer pages. DataFlirt handles the infrastructure so your engineers can focus on modelling pricing parity and market trends rather than maintaining parsers.
Everything supported by our hamiltonwatch.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 handles JavaScript rendering and interaction flows for complex specification tables.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request to ensure accurate local pricing data.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About hamiltonwatch.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated catalogue and pricing data. We do not extract personal data or circumvent authentication walls.
We route crawler traffic through geo-specific residential proxies (e.g., US IPs for USD pricing, UK IPs for GBP pricing) to ensure the site serves the correct regional data grid.
Yes. Our parsers are built to extract specific horological metrics like caliber codes, power reserve hours, jewel counts, and frequency, mapping them to a normalised schema.
Pipelines can be configured to run daily or weekly. For a catalogue of Hamilton's size, a full refresh completes in under an hour.
We provide a time-series table per reference number from the date your pipeline starts, allowing you to track MSRP changes over time.
We support full catalogue extractions on a scheduled basis. Contact us to define the specific regions and update frequency you require.
Absolutely. We provide a sample run covering a subset of collections (e.g., Khaki Field) to validate schema fit and data quality before signing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price monitoring — we scope, build, and operate the pipeline. Tell us what you need.
