We extract machinery listings, dealer inventories, pricing signals, and operating hours from Equipment Trader. 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 Equipment Listings objects from equipmenttrader.com. All fields typed and schema-versioned.
"listing_id": "5028194432", "make": "Caterpillar", "model": "320F L", "year": 2018, "price": 125000.0, "hours": 4250, "condition": "Used", "location": "Dallas, TX"
| # | listing_id | title | make | model | year | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Dealer Data objects from equipmenttrader.com. All fields typed and schema-versioned.
"dealer_id": "DLR-89321", "name": "Texas Heavy Equipment Sales", "type": "Commercial Dealer", "city": "Houston", "state": "TX", "active_listings": 142, "inventory_url": "https://www.equipmenttrader.com/dealers/detail/DLR-89321"
| # | dealer_id | name | type | address | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Valuation objects from equipmenttrader.com. All fields typed and schema-versioned.
"listing_id": "5028194432", "price": 125000.0, "msrp": "None", "currency": "USD", "price_type": "Fixed", "negotiable": true, "price_timestamp": "2026-08-14T10:22:00Z"
| # | listing_id | price | msrp | currency | price_type | negotiable |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Machine Specs objects from equipmenttrader.com. All fields typed and schema-versioned.
"listing_id": "5028194432", "engine_make": "Cat C4.4 ACERT", "horsepower": "161 hp", "drive_type": "Track", "fuel_type": "Diesel", "operating_weight": "49200 lbs", "attachments": "['Bucket', 'Thumb']"
| # | listing_id | engine_make | horsepower | drive_type | fuel_type | capacity |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Search Results objects from equipmenttrader.com. All fields typed and schema-versioned.
"keyword": "excavator", "location": "75001", "position": 3, "listing_id": "5028194432", "price": 125000.0, "dealer_name": "Texas Heavy Equipment Sales", "promoted_badge": true
| # | keyword | category | location | position | listing_id | title |
|---|---|---|---|---|---|---|
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Our Equipment Trader scraper captures critical valuation metrics: operating hours, condition, serial numbers, and dealer inventory data — bypassing bot mitigation to deliver clean datasets.
Title, make, model, year, condition, operating hours, and detailed specifications extracted directly from listing pages.
Extract entire dealership catalogues, mapping individual machines to dealer profiles and tracking inventory turnover.
Monitor asking prices, MSRP comparisons, and price drops across machinery categories to spot market trends.
Parse structured data for engine horsepower, lift capacity, drive type, operating weight, and included attachments.
Capture precise geographical data for freight estimation, transport routing, and regional supply analysis.
Extract high-resolution image URLs and video walkaround links for remote condition assessment and cataloguing.
Track visibility and promoted placements for specific equipment categories and regions across the platform.
Extract serial numbers and VINs for provenance tracking, theft database checks, and precise valuation modelling.
Run daily inventory diffs to identify new listings and sold equipment without processing the entire catalogue.
Brief in. Clean data out.
Provide equipment categories, makes, dealer URLs, or zip codes. We map the extraction schema.
We configure Scrapy crawlers, proxy rotation, and CAPTCHA handling for equipmenttrader.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Equipment Trader protects its inventory data with commercial bot mitigation and deep pagination constraints. Here is how we maintain reliable extraction.
Equipment Trader uses commercial bot mitigation to block datacenter IPs. We route requests through US-based residential ISP proxies with realistic browser fingerprints and HTTP headers to ensure uninterrupted access.
Many technical specifications and dealer contact details load dynamically via XHR. We run full browser sessions to execute JavaScript and capture fields that headless HTTP clients miss.
Search results cap at a fixed number of pages, hiding deep inventory. We segment crawls by granular zip codes, categories, and price tiers to extract the full database without hitting pagination walls.
Dealer inventory pages vary heavily in DOM structure based on subscription tiers. Our fallback chains ensure data normalisation across custom dealer layouts and changing site architectures.
For massive national inventories, we maintain a hash index of listing IDs and only push diffs when prices drop or listings are removed, reducing your downstream processing load.
Lenders and insurers model depreciation curves based on make, model, year, and operating hours.
Dealerships monitor competitor pricing, inventory aging, and regional supply gaps.
Construction and agricultural firms track specific machinery availability across multiple states.
Manufacturers analyze secondary market volume to forecast new equipment demand.
Brokers identify underpriced machinery in specific geographies for cross-state arbitrage.
Transport companies map heavy machinery clusters to optimize flatbed routing and backhauls.
"Equipment Trader holds the definitive pulse on heavy machinery supply, but extracting clean, normalised specs from thousands of disparate dealer listings requires serious infrastructure."
Scraping heavy equipment data involves navigating commercial bot protection, deep pagination limits, and highly variable dealer page templates. DataFlirt absorbs that complexity, handling the residential proxies, JavaScript rendering, and schema normalisation so your analysts can focus on market valuation — not pipeline maintenance.
Everything supported by our equipmenttrader.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About equipmenttrader.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Equipment Trader is generally permissible under applicable law. DataFlirt targets only public, non-authenticated machinery listings and dealer data. We do not extract personal data or circumvent authentication walls. Clients should review platform terms and consult legal counsel for specific use cases.
We use US-based residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and request timing modelled on human behaviour to bypass commercial bot mitigation.
Yes. You can provide a list of specific dealership URLs, and we will extract their entire active inventory, mapping machines directly to the dealer profile.
We can configure pipelines to run daily for large-scale market analysis, or at higher frequencies for specific dealer tracking to capture intra-day price drops.
Yes. We parse the structured specification tables to extract horsepower, drive type, lift capacity, operating weight, and fuel type for accurate valuation modelling.
Yes. Operating hours and price are extracted as core fields for every listing, providing the necessary data for depreciation curve modelling.
Our smallest packages start at a defined set of categories or zip codes (typically 5,000+ listings) with weekly delivery. For national coverage, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of excavators or a complete dump of national dealer inventories — we scope, build, and operate the pipeline. Tell us what you need.
