Commercial Vehicle Data: Examples, Providers & Best Datasets to Buy

On This Page:
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- FAQ
On This Page:
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- FAQ
What is Commercial Vehicle Data?
Commercial vehicle data refers to structured information about vans, trucks, buses, and other non-personal vehicles that are operated for logistics, transportation, or service delivery. This data is essential for industries like supply chain management, fleet operations, construction, public transit, and freight.
Collected from telematics systems, registration databases, OEMs, insurance records, and government sources, this data provides insight into usage patterns, compliance, maintenance, and more. It can be accessed through APIs or in bulk datasets.
What Are Examples of Commercial Vehicle Data?
Commercial vehicle data enables real-time operations and long-term planning. Key examples include:
- Vehicle Identification Number (VIN)
- Make, model, year, and engine type
- Gross Vehicle Weight Rating (GVWR)
- Odometer readings and mileage
- Commercial usage classification
- Ownership and fleet registration details
- Maintenance history
- Emissions class and fuel type
- Load capacity and axle count
- Route logs and trip-level telematics data
Best Commercial Vehicle Databases & Datasets
Data providers on Datarade offer a wide selection of commercial vehicle datasets covering regional and global markets. These include static datasets (e.g., fleet registry records), dynamic feeds (e.g., telematics or real-time location), and performance-based datasets (e.g., fuel consumption, idle time, and emissions data).

Automotive Data | Commercial Vehicle Data | Car Specs, Equip & Price (Europe)| Updated Monthly | Product Development

PREDIK Data-Driven Trucking Data, Location Data & Commercial Vehicle Data: Custom Datasets for Truck Trips & Stops (Available for USA)

Electric Vehicle Charging Stations Data |99% Data accuracy|App and Market Intelligence

Automotive Data | Commercial Vehicle Data | Car Specs, Equip & Price (LATAM)| Updated Monthly | Product Development

IRIS® by Dataforce - International Vehicle Registration Information System for Automotive Market in Europe

Demographic Data | Australia | Latest Estimates and Projections To Make Informed Business Decisions | GIS Data | Map Data

Trip Data / Aggregated data elements of vehicle trip from ignition on to ignition off.

99finder | Wholesalers, Importers & Distributors Database with 32M Companies | 150+ Countries | Verified Contact Details

Product Data | Commercial Vehicle Data | Car Specs, Equip & Price (Europe)| Updated Monthly | Product & Price Strategy

IRIS® Parc by Dataforce - International Vehicle Registration Information System for Automotive Market in Europe
Why Is Commercial Vehicle Data Important?
Operational Optimization
Fleet managers can use this data to minimize fuel use, identify underutilized assets, and ensure vehicles are compliant with safety regulations. Real-time tracking improves customer experience by providing accurate ETAs and delivery confirmations.
Investment and M&A Research
Before investing in or acquiring logistics, construction, or transportation companies, commercial vehicle data can reveal the scale, condition, and capabilities of a company’s mobile assets. This is especially relevant in due diligence when fleet value is a key driver.
Sustainability and Emissions Compliance
Tracking commercial vehicle emissions and electrification rates helps companies report on ESG performance and prepare for green transition strategies. It also enables route adjustments to minimize carbon output.
How Is Commercial Vehicle Data Collected?
Commercial vehicle data is collected via:
- OEM APIs and on-board vehicle sensors
- GPS and telematics systems
- Government registration databases
- Electronic Logging Devices (ELDs)
- Maintenance and repair shops
- Insurance claims and underwriting systems
On Datarade commercial datasets are anonymized and aggregated to comply with data protection laws.
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Top Commercial Vehicle Data Providers & Companies
Popular Use Cases for Commercial Vehicle Data
Commercial vehicle data supports critical operations across transportation and logistics sectors. The most common applications include:
- Fleet Management: Monitor real-time vehicle status, optimize asset usage, and schedule preventive maintenance.
- Insurance & Risk Assessment: Use driving history, mileage, and vehicle specs for more accurate underwriting and claims validation.
- Route Optimization: Streamline deliveries and reduce fuel consumption using GPS logs and trip data.
- Emissions & ESG Reporting: Track vehicle emissions by class and fuel type for sustainability initiatives.
- Market Intelligence: Analyze registration trends and commercial vehicle density across geographies.
- Regulatory Compliance: Ensure adherence to mandates like ELD (Electronic Logging Devices) and DOT standards.
- Procurement & Investment Research: Understand fleet size and vehicle mix before engaging in partnerships or acquisitions.
Main Attributes of Commercial Vehicle Data
To fully leverage commercial vehicle data, datasets should include the following attributes:
- VIN (Vehicle Identification Number)
- Make / Model / Trim / Engine Type
- Vehicle Class (Light Duty, Heavy Duty, etc.)
- GVWR
- Fuel Type (Diesel, Electric, etc.)
- Odometer & Mileage
- Location (geo-coordinates or route IDs)
- Trailer attachment status
- Maintenance logs or fault codes
These data points allow organizations to model vehicle usage, reduce operational costs, and increase visibility across their transport network.
Attribute | Type | Description | Action |
---|---|---|---|
String | The name of a brand. | View 3 datasets | |
String | The postal code of an address. | View 2 datasets | |
String | The email address of a company or contact. | View 1 datasets | |
String | The Internet Protocol version 4 (IPv4) address of an endpoint. | View 1 datasets | |
Float | The latitude of a point on earth's surface. Commonly abbreviated as "lat". | View 1 datasets | |
String | The phone number of a contact or organization. | View 1 datasets |
Frequently Asked Questions
How is the Quality of Commercial Vehicle Data Maintained?
The quality of Commercial Vehicle Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.
How Frequently is Commercial Vehicle Data Updated?
The update frequency for Commercial Vehicle Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.
Is Commercial Vehicle Data Secure?
The security of Commercial Vehicle Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.
How is Commercial Vehicle Data Delivered?
Commercial Vehicle Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Commercial Vehicle Data.
How Much Does Commercial Vehicle Data Cost?
The cost of Commercial Vehicle Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Commercial Vehicle Data for your needs.
What Are Similar Data Types to Commercial Vehicle Data?
Commercial Vehicle Data is similar to other data types, such as Vehicle Location Data, Traffic Data, Electric Vehicle Charging Stations Data, Car Data, and VIN Data. These related categories are often used together for applications like Tire Condition Analysis and Urban Planning.