Alesco Data's Automotive records are updated monthly from millions of proprietary sourced vehicle transactions. These incoming transactions are processed through compilation rules and are either added as new, incremental records to our file, or contribute to validating existing records.

Our recent focus is on compiling new vehicle ownership, and the file includes over 14.2 million late model vehicle owners (2020-2025).

We also append our Persistent ID, telephone numbers, and demographics for a complete file that can support your direct mail and email marketing campaigns, lead validation, and identity verification needs. A Persistent ID is assigned to each vehicle record and tracks consumers as they change addresses or phone numbers, and vehicles as they change owners.

The database is not derived from state motor vehicle databases and therefore not subject to the Shelby Act also known as the Driver's Privacy Protection Act (DPPA) of 2000. The data is deterministic and sources include sales and service data, warranty data and notifications, aftermarket repair and maintenance facilities, and scheduled maintenance records.

Fields Included: Make Model Year VIN Data Vehicle Class Code (crossover, SUV, full-size, mid-size, small) Vehicle Fuel Code (gas, flex, hybrid) Vehicle Style Code (sport, pickup, utility, sedan) Mileage Number of Vehicles per Household First seen date Last seen date Email

The fields available include make, model, year, trim, style, fuel type, MSRP, and many more.

We have developed this file to be tied to our Consumer Demographics Database so additional demographics can be applied as needed. Each record is ranked by confidence and only the highest quality data is used. This file contains over 180 million records in addition to over 1 million+ fresh automotive intender records per day.

Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.

BIGDBM Privacy Policy: https://bigdbm.com/privacy.html

France Motor Vehicle Ownership: HH: Main Driver: Women data was reported at 41.900 % in 2015. This records an increase from the previous number of 41.800 % for 2014. France Motor Vehicle Ownership: HH: Main Driver: Women data is updated yearly, averaging 41.250 % from Dec 2002 (Median) to 2015, with 14 observations. The data reached an all-time high of 42.300 % in 2012 and a record low of 40.200 % in 2006. France Motor Vehicle Ownership: HH: Main Driver: Women data remains active status in CEIC and is reported by French Automobile Manufacturers Committee . The data is categorized under Global Database’s France – Table FR.TA004: Motor Vehicle Ownership per Household.

Vehicle Make, Model, and Color Database Market Outlook

According to our latest research, the global Vehicle Make, Model, and Color Database market size reached USD 2.1 billion in 2024. The market is expected to grow at a CAGR of 7.3% during the forecast period, reaching a value of USD 3.9 billion by 2033. This robust growth is driven by the increasing digitization of automotive data, the proliferation of connected vehicles, and the heightened demand for real-time vehicle information across multiple industries. As per our latest research, the integration of advanced analytics and artificial intelligence within vehicle databases is further accelerating market expansion, enabling more precise and actionable insights for end-users globally.

The primary growth factor for the Vehicle Make, Model, and Color Database market is the escalating need for accurate and comprehensive vehicle information across diverse sectors. Automotive dealerships, insurance companies, and law enforcement agencies are increasingly relying on these databases to streamline operations, enhance customer experience, and improve decision-making processes. The rise in vehicle thefts, fraudulent insurance claims, and the need for efficient fleet management solutions have all contributed to a surge in demand for reliable vehicle data. Furthermore, the growing trend toward digital transformation within the automotive industry has led to the adoption of sophisticated database solutions, which offer seamless integration with existing IT infrastructures and ensure data accuracy and security.

Another significant growth driver is the rapid advancement in data collection technologies and the expanding sources of vehicle-related data. The proliferation of IoT-enabled vehicles, telematics, and connected car platforms has resulted in an exponential increase in the volume and variety of vehicle data available for analysis. This has enabled database providers to offer more granular and up-to-date information, catering to the specific requirements of end-users such as automotive manufacturers, government agencies, and transportation companies. The integration of machine learning and big data analytics further enhances the value proposition of these databases, enabling predictive insights and real-time data validation that support critical business functions and regulatory compliance.

The market is also witnessing increased collaboration between original equipment manufacturers (OEMs), aftermarket players, and technology providers to standardize and enrich vehicle data. These partnerships are essential for ensuring data consistency, interoperability, and scalability across different platforms and geographies. The adoption of cloud-based database solutions has further democratized access to vehicle data, allowing small and medium enterprises (SMEs) to leverage sophisticated analytics without significant upfront investments. Additionally, regulatory initiatives aimed at improving road safety and vehicle traceability are fueling the demand for comprehensive and up-to-date vehicle databases, particularly in emerging markets where vehicle ownership is on the rise.

From a regional perspective, North America continues to dominate the Vehicle Make, Model, and Color Database market, accounting for the largest share in 2024. This is attributed to the region's mature automotive ecosystem, high vehicle penetration, and early adoption of advanced data management technologies. Europe follows closely, driven by stringent regulatory requirements and a strong focus on vehicle safety and compliance. The Asia Pacific region is poised for the fastest growth during the forecast period, supported by rapid urbanization, increasing vehicle sales, and significant investments in digital infrastructure. Latin America and the Middle East & Africa are also emerging as promising markets, with growing awareness of the benefits of robust vehicle data management systems and the expansion of automotive and transportation sectors.

Database Type Analysis</h2

.AUTO Whois Database, discover comprehensive ownership details, registration dates, and more for .AUTO TLD with Whois Data Center.

France Motor Vehicle Ownership: HH: Area: Towns: Greater Paris and Paris data was reported at 64.700 % in 2017. This records an increase from the previous number of 59.700 % for 2015. France Motor Vehicle Ownership: HH: Area: Towns: Greater Paris and Paris data is updated yearly, averaging 62.400 % from Dec 2002 (Median) to 2017, with 15 observations. The data reached an all-time high of 64.700 % in 2017 and a record low of 59.700 % in 2015. France Motor Vehicle Ownership: HH: Area: Towns: Greater Paris and Paris data remains active status in CEIC and is reported by French Automobile Manufacturers Committee . The data is categorized under Global Database’s France – Table FR.TA004: Motor Vehicle Ownership per Household.

The AmeriList RV Owners Database is a powerful, up-to-date mailing list comprising over 10.7 million RV owners across the United States. This specialized consumer dataset is built to fuel targeted direct marketing campaigns via postal mail, email, and telemarketing, helping brands, service providers, and marketers reach RV enthusiasts with precision. Whether you’re in outdoor gear, insurance, travel, campground services, RV parts & accessories, or hospitality, this database unlocks access to high-value prospects who live for the open road.

Key Features & Data Quality

• Extensive Universe: 10,774,530 RV owners in the U.S. matched for multiple channels (postal, email, telemarketing).
• Rich segmentation options: You can target by RV type and class (Motorhome Class A, B, C, travel trailers, camper types), RV year; demographics such as age, household income, net worth; geography (state, zip, city, radius etc.); interests, hobbies; presence of children, ethnicity, and more.
• High data integrity: The list is compiled from multiple sources: registration data, point-of‐sale & service, membership & subscription records, surveys and online activity. It is standardized & verified via major data hygiene tools and postal certifications including USPS certified procedures, CASS, LACSLink, NCOALink, and DPV verification.
• Update frequency: Data is refreshed monthly to keep contacts current. Address changes are managed with NCOA (National Change of Address).
• Flexibility in order size & use: Minimum order, usage levels etc., designed to accommodate both large and smaller campaigns.

Typical Profile & Behavior - The average RV owner in the U.S. is about 48 years old and likely to travel multiple times per year in their vehicle. - They tend to seek comfort, quality, adventure, and gear, making them especially responsive to offers for travel services, camping supplies, insurance, outdoor lifestyle brands, RV accessories, maintenance & repair providers.

Ideal Use Cases / Campaign Fit This dataset is especially well suited for marketers and businesses in: - Outdoor recreation & camping gear & supplies - RV parks, campgrounds & travel accommodations - Insurance & extended warranty providers for RVs - Automotive service, RV repair, parts & accessories - Travel brands, restaurateurs, fuel stations along travel corridors - Financial services, lifestyle brands targeting affluent / adventure-minded customers

By combining detailed demographic and RV usage / ownership segmentations, campaigns can be highly tailored, improving response rates, reducing waste, and driving higher ROI.

Technical & Operational Details - Channels delivered: Postal mail, email, telemarketing. - Certifications & Accuracy tools: USPS-certified address and mailing standards; CASS; LACSLink; DPV; NCOALink for address update; regular monthly refreshes. - Minimum order thresholds & pricing: Minimum orders start at 5,000 records. Base rates vary depending on campaign channel, refinement, order size, and segment selections.

Data delivery format & options: Lists can be delivered electronically (e.g. Excel, comma-delimited text), and via postal mailing list services. Suppression, hygiene, de-duplication, and other enhancements are generally available.

Context

Automobile data holds immense importance as it offers insights into the functioning and efficiency of the automotive industry. It provides valuable information about car models, specifications, sales trends, consumer demographics, and preferences, which car manufacturers and dealerships can leverage to optimize their operations and enhance customer experiences. By analyzing data on vehicle reliability, fuel efficiency, safety ratings, and resale values, the automotive industry can identify trends and implement strategies to produce more reliable and environmentally friendly vehicles, improve safety standards, and enhance the overall value of cars for consumers. Moreover, regulatory bodies and policymakers rely on this data to enforce regulations, set emissions standards, and make informed decisions regarding automotive policies and environmental impacts. Researchers and analysts use car purchase data to study market trends, assess the environmental impact of various vehicle types, and develop strategies for sustainable growth within the industry. In essence, car purchase data serves as a foundation for informed decision-making, operational efficiency, and the overall advancement of the automotive sector.

Content

This dataset comprises diverse parameters relating to car purchases and ownership on a global scale. The dataset prominently incorporates fields such as 'First Name', 'Last Name', 'Country', 'Car Brand', 'Car Model', 'Car Color', 'Year of Manufacture', and 'Credit Card Type'. These columns collectively provide comprehensive insights into customer demographics, vehicle details, and payment information. Researchers and industry experts can leverage this dataset to analyze trends in car purchasing behavior, optimize the customer car-buying experience, evaluate the popularity of car brands and models, and understand payment preferences within the automotive industry.

Dataset Glossary (Column-wise)

• First Name - The first name of the car purchaser.
• Last Name - The last name of the car purchaser.
• Country - The country of residence of the car purchaser.
• Car Brand - The brand or manufacturer of the purchased car.
• Car Model - The specific model of the purchased car.
• Car Color - The color of the purchased car.
• Year of Manufacture - The year the car was manufactured.
• Credit Card Type - The type of credit card used for the car purchase.

Structure of the Dataset

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Acknowledgement

The dataset provided here is a simulated example and was generated using the online platform found at Mockaroo. This web-based tool offers a service that enables the creation of customizable mock datasets that closely resemble real data. It is primarily intended for use by developers, testers, and data experts who require sample data for a range of uses, including testing databases, filling applications with demonstration data, and crafting lifelike illustrations for presentations and tutorials. To explore further details, you can visit their website.

Cover Photo by: Freepik

Thumbnail by: Car icons created by Freepik - Flaticon

In this file there are statistics for a number of variables broken down by Malmö’s different areas over time. Sources Unless otherwise stated, the statistics in this database are retrieved from Statistics Sweden’s (SCB) regional database, Skånedatabasen or from Statistics Sweden’s area statistics database (OSDB). The Skåne database and OSDB show data from several different sources that Statistics Sweden has compiled on a geographical level. The statistics only cover persons who are part of the population registered in the population. Therefore, persons without a residence permit, such as asylum seekers, and persons who simply have not registered in the municipality are not included. Statistics Sweden does not provide statistics on which language residents speak, which religion you belong to or what ethnicity or political views you have. Therefore, such data is not available here either. However, the Electoral Authority reports election results per constituency on its website val.se. There are statistics from the last election as well as several previous elections available. Please note, however, that the constituencies do not necessarily follow the division of the city made here. Update The data is updated every spring as Statistics Sweden releases the figures to the municipality. Most variables are available for the year before. However, income and employment data are released with another year’s backlog. Unless otherwise stated, the date of measurement is 31 December of each year. Geographical breakdown Unless otherwise stated, the data is available for Malmö as a whole and broken down into urban areas (5 pieces), districts (10 pieces) and subareas (136 pieces). In addition to these, there is a residual post that contains the people who are not written in a specific place in the municipality, have protected identity and more. These people are also part of the total. In several of the subareas there are no or only a few registered population registers. Therefore, no data are reported for these areas. Examples of such sub-areas are parks such as Pildammsparken and Kroksbäcksparken and industrial areas such as Fosieby Industriområde and Spillepengen. Privacy clearance In order to protect the identity of individuals, the data is confidentially audited. This means that small values are suppressed, i.e. replaced by empty cells. However, the values are included in summaries. In general, the following rules apply: • No statistics are reported for geographical areas with very few housing. No cells with fewer than 5 individuals are reported. For data classified as sensitive (e.g. income and country of birth), larger values can also be suppressed. • In cases where a subcategory (e.g. a training category) is too small to be accounted for, all categories are often suppressed. Please use the numbers, but use “City Office, Malmö City” as the source.

France Motor Vehicle Ownership: HH: Area: Rural Areas data was reported at 93.400 % in 2017. This records an increase from the previous number of 92.900 % for 2015. France Motor Vehicle Ownership: HH: Area: Rural Areas data is updated yearly, averaging 92.700 % from Dec 2002 (Median) to 2017, with 15 observations. The data reached an all-time high of 93.400 % in 2017 and a record low of 91.400 % in 2003. France Motor Vehicle Ownership: HH: Area: Rural Areas data remains active status in CEIC and is reported by French Automobile Manufacturers Committee . The data is categorized under Global Database’s France – Table FR.TA004: Motor Vehicle Ownership per Household.

This table contains values from Compare.com's proprietary database of car insurance quotes about average DynamicTable.dataset.coverage.monthly_cost_total car insurance costs DynamicTable.dataset.source.stateAvgPrices

Number of Cars: Privately Owned: Per 1000 Person: CF: City of Moscow data was reported at 282.272 Unit in 2022. This records a decrease from the previous number of 297.353 Unit for 2021. Number of Cars: Privately Owned: Per 1000 Person: CF: City of Moscow data is updated yearly, averaging 232.100 Unit from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 306.351 Unit in 2017 and a record low of 69.800 Unit in 1990. Number of Cars: Privately Owned: Per 1000 Person: CF: City of Moscow data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.RAD005: Number of Cars Privately Owned per 1000 Persons.

Vehicle Make Model and Color Database Market Outlook

According to our latest research, the global Vehicle Make Model and Color Database market size in 2024 is valued at approximately USD 1.78 billion. The market is poised for robust expansion, exhibiting a compound annual growth rate (CAGR) of 11.2% from 2025 to 2033. By the end of 2033, the market is projected to reach USD 4.73 billion. This growth is primarily driven by the rising need for advanced vehicle identification systems across diverse sectors, including automotive, insurance, and law enforcement, as organizations increasingly prioritize data-driven operations and regulatory compliance.

One of the primary growth factors fueling the Vehicle Make Model and Color Database market is the surge in digitization within the automotive sector. The proliferation of connected vehicles, IoT-enabled fleet management solutions, and the widespread adoption of smart city initiatives have led to a substantial increase in the volume and complexity of vehicular data. Automotive dealerships, insurance providers, and fleet management companies are leveraging these databases to streamline their operations, improve customer service, and enhance security protocols. The ability to quickly and accurately identify vehicles by make, model, and color is becoming indispensable for managing inventories, processing insurance claims, and maintaining regulatory compliance. This digitization trend is expected to intensify as more organizations recognize the value of comprehensive, real-time vehicle data.

Another significant driver is the escalating demand for robust vehicle identification systems by law enforcement agencies and governmental bodies. The rise in vehicle-related crimes, coupled with the need for efficient traffic management, has compelled authorities to invest in advanced database solutions. These databases enable law enforcement agencies to rapidly identify stolen or suspicious vehicles, support automated license plate recognition systems, and contribute to the overall safety and security of urban environments. Furthermore, the integration of artificial intelligence and machine learning algorithms into these databases enhances their accuracy and predictive capabilities, allowing for proactive threat detection and incident response. As public safety concerns continue to mount, the adoption of vehicle make, model, and color databases by the public sector is expected to grow steadily.

The expansion of the global automotive aftermarket also plays a pivotal role in the growth of the Vehicle Make Model and Color Database market. As the average vehicle lifespan increases and the demand for used vehicles rises, accurate and up-to-date vehicle information becomes crucial for dealerships, car rental services, and insurance companies. These organizations rely on comprehensive databases to verify vehicle histories, assess risk profiles, and optimize pricing strategies. Additionally, the increasing popularity of online vehicle marketplaces and digital sales platforms further amplifies the need for reliable and easily accessible vehicle data. This trend is likely to persist as consumers and businesses continue to favor digital channels for vehicle transactions and management.

Regionally, North America currently dominates the Vehicle Make Model and Color Database market, accounting for a significant share of global revenue in 2024. The region’s leadership is attributed to its advanced automotive ecosystem, high penetration of digital technologies, and strong presence of key market players. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, driven by rapid urbanization, increasing vehicle ownership, and government initiatives aimed at modernizing transportation infrastructure. Europe also remains a critical market, benefiting from stringent regulatory standards and a mature automotive industry. Collectively, these regional dynamics underscore the global nature of the market and highlight the diverse opportunities for stakeholders across different geographies.

Database Type Analysis

The Vehicle Make Model and Color Database market is segmented by database type into structured, unstructured, and hybrid databases. Structured databases, which utilize a predefined schema and organized data models, remain the dominant segment due to their reliability, ease of integration, and compatibility with existing enter

France Motor Vehicle Ownership: HH: Tradesmen, Craftsmen, Business Owners data was reported at 90.900 % in 2015. This records an increase from the previous number of 87.200 % for 2014. France Motor Vehicle Ownership: HH: Tradesmen, Craftsmen, Business Owners data is updated yearly, averaging 91.150 % from Dec 2002 (Median) to 2015, with 14 observations. The data reached an all-time high of 97.800 % in 2002 and a record low of 87.200 % in 2014. France Motor Vehicle Ownership: HH: Tradesmen, Craftsmen, Business Owners data remains active status in CEIC and is reported by French Automobile Manufacturers Committee . The data is categorized under Global Database’s France – Table FR.TA004: Motor Vehicle Ownership per Household.

Total vehicle registration counts per month by county

The dataset collects the semi-annual data, for each municipality of the Emilia-Romagna Region, of the changes of ownership, presented to the Public Motor Vehicle Register (PRA), net of mini-voltures (passages of ownership in favor of dealers and resellers art. 56 DL 446/97). The data is sorted according to the type of "vehicle class". The data come from the database of the Public Automobile Register (PRA) and are issued by the Automobile Club of Italy.

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Now featuring the powerful AUTO DETAILS APPEND option, it’s perfect for businesses offering products or services tailored to specific vehicle owners. Ideal for applications in auto dealerships, warranties, insurance, and more, the data complies with the Shelby Act and Drivers Privacy Protection Act, ensuring reliability and legal compliance.

Available for licensing or installation, this fully validated, hygiene-processed file is the ultimate tool for connecting with your target audience in the automotive industry.

France Motor Vehicle Ownership: HH: Middle Management data was reported at 89.100 % in 2017. This records an increase from the previous number of 88.000 % for 2015. France Motor Vehicle Ownership: HH: Middle Management data is updated yearly, averaging 89.100 % from Dec 2002 (Median) to 2017, with 15 observations. The data reached an all-time high of 90.700 % in 2011 and a record low of 87.100 % in 2003. France Motor Vehicle Ownership: HH: Middle Management data remains active status in CEIC and is reported by French Automobile Manufacturers Committee . The data is categorized under Global Database’s France – Table FR.TA004: Motor Vehicle Ownership per Household.