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Global Car Generated Data Market to reach USD XX Million by the end of 2029.

Global Car Generated Data Market Size study & Forecast, by Application (Advance Driver Assisted System (ADAS), Human Machine Interface Data (HMI), Technical Sensor Data, Infotainment Data, Infrastructure Data, Diagnostic Data, and Others), by Type (Descriptive, Predictive, and Prescriptive), by Fuel Type (Battery Electric Vehicle (BEV), Internal Combustion Engine (ICE), and Others (Hybrid Vehicles)), and by Level of Autonomous (Conventional and Semi-Autonomous) and Regional Analysis, 2022-2029

Product Code: ALTST-54020944
Publish Date: 24-04-2023
Page: 200

Global Car Generated Data Market is valued at approximately USD XX Million in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. Car Generated Data refers to the data generated by autonomous and semi-autonomous vehicles. The original equipment manufacturers (OEMs) are incorporating premium connectivity in the vehicles in response to rising safety concerns and rising demand for comfort features. The users may now access cutting-edge capabilities such as online payments, car tracking, vehicle diagnostics, and navigations because the vehicles are now equipped with server/internet connections. The use of these features/applications generates a tonne of data, which OEMs may then utilize to strategically promote their goods/services and keep tabs on consumer driving habits and real-time vehicle monitoring. This data is crucial for the insurance sector, as well as for use in R&D and advertising. The increasing penetration of connected vehicles and growing demand for enhanced user experience are key factors accelerating the market growth.

The rising penetration of connected vehicles is contributing towards the growth of the Global Car Generated Data market. For instance – as per Statista – in 2021, the global market for connected cars was valued at USD 65 billion, up from USD 56 billion in 2020. Further, it is projected to grow to around USD 121 billion by 2025. Also, government regulations pertaining to telematics and the rapid growth of mobility services would create a lucrative growth prospectus for the market over the forecast period. However, the high cost of electric components and concern over data security threats stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to the dominance of leading market players as well as the growing adoption and development of autonomous and semi-autonomous Global Car Generated Data Market vehicles in the region. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as the rising expansion of the automotive industry coupled with the growing penetration of connected vehicles in the region.

Major market player included in this report are:
Drust
Sight Machine
ZenDrive
PitStop
CARFIT
Tourmaline Labs
Clairvoyant India Private Limited
HARMAN International
Zene
Carffeine

Recent Developments in the Market:
Ø In January 2023, Stellantis announced the formation of its new business unit dedicated to turning all that vehicle data into marketable products. This new business unit called Mobilisights is aimed to generate USD 21.74 billion in annual revenue from software-related services by the end of the decade.

Global Car Generated Data Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Application, Type, Fuel Type, Level of Autonomous, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application
Advance Driver Assisted System (ADAS)
Human Machine Interface Data (HMI)
Technical Sensor Data
Infotainment Data
Infrastructure Data
Diagnostic Data
By Type
Descriptive Analytics
Predictive Analytics
Prescriptive Analytics
By Fuel Type
Battery Electric Vehicle (BEV)
Internal Combustion Engine (ICE)
Others (Hybrid Vehicles)
By Level of Autonomous
Conventional
Semi-Autonomous

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Million)
1.2.1. Car Generated Data Market, by Region, 2019-2029 (USD Million)
1.2.2. Car Generated Data Market, by Application, 2019-2029 (USD Million)
1.2.3. Car Generated Data Market, by Type, 2019-2029 (USD Million)
1.2.4. Car Generated Data Market, by Fuel Type, 2019-2029 (USD Million)
1.2.5. Car Generated Data Market, by Level of Autonomous, 2019-2029 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Car Generated Data Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Car Generated Data Market Dynamics
3.1. Car Generated Data Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing penetration of connected vehicles
3.1.1.2. Growing demand for enhanced user experience
3.1.2. Market Challenges
3.1.2.1. High Cost associated with advanced electronic systems.
3.1.2.2. Rise in cyber security threats
3.1.3. Market Opportunities
3.1.3.1. Government regulations pertaining to telematics.
3.1.3.2. Rapid growth of mobility services
Chapter 4. Global Car Generated Data Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Car Generated Data Market, by Application
6.1. Market Snapshot
6.2. Global Car Generated Data Market by Application, Performance – Potential Analysis
6.3. Global Car Generated Data Market Estimates & Forecasts by Application 2019-2029 (USD Million)
6.4. Car Generated Data Market, Sub Segment Analysis
6.4.1. Advance Driver Assisted System (ADAS)
6.4.2. Human Machine Interface Data (HMI)
6.4.3. Technical Sensor Data
6.4.4. Infotainment Data
6.4.5. Infrastructure Data
6.4.6. Diagnostic Data
Chapter 7. Global Car Generated Data Market, by Type
7.1. Market Snapshot
7.2. Global Car Generated Data Market by Type, Performance – Potential Analysis
7.3. Global Car Generated Data Market Estimates & Forecasts by Type 2019-2029 (USD Million)
7.4. Car Generated Data Market, Sub Segment Analysis
7.4.1. Descriptive Analytics
7.4.2. Predictive Analytics
7.4.3. Prescriptive Analytics
Chapter 8. Global Car Generated Data Market, by Fuel Type
8.1. Market Snapshot
8.2. Global Car Generated Data Market by Fuel Type, Performance – Potential Analysis
8.3. Global Car Generated Data Market Estimates & Forecasts by Fuel Type 2019-2029 (USD Million)
8.4. Car Generated Data Market, Sub Segment Analysis
8.4.1. Battery Electric Vehicle (BEV)
8.4.2. Internal Combustion Engine (ICE)
8.4.3. Others (Hybrid Vehicles)
Chapter 9. Global Car Generated Data Market, by Level of Autonomous
9.1. Market Snapshot
9.2. Global Car Generated Data Market by Level of Autonomous, Performance – Potential Analysis
9.3. Global Car Generated Data Market Estimates & Forecasts by Level of Autonomous 2019-2029 (USD Million)
9.4. Car Generated Data Market, Sub Segment Analysis
9.4.1. Conventional
9.4.2. Semi-Autonomous
Chapter 10. Global Car Generated Data Market, Regional Analysis
10.1. Car Generated Data Market, Regional Market Snapshot
10.2. North America Car Generated Data Market
10.2.1. U.S. Car Generated Data Market
10.2.1.1. Application breakdown estimates & forecasts, 2019-2029
10.2.1.2. Type breakdown estimates & forecasts, 2019-2029
10.2.1.3. Fuel Type breakdown estimates & forecasts, 2019-2029
10.2.1.4. Level of Autonomous breakdown estimates & forecasts, 2019-2029
10.2.2. Canada Car Generated Data Market
10.3. Europe Car Generated Data Market Snapshot
10.3.1. U.K. Car Generated Data Market
10.3.2. Germany Car Generated Data Market
10.3.3. France Car Generated Data Market
10.3.4. Spain Car Generated Data Market
10.3.5. Italy Car Generated Data Market
10.3.6. Rest of Europe Car Generated Data Market
10.4. Asia-Pacific Car Generated Data Market Snapshot
10.4.1. China Car Generated Data Market
10.4.2. India Car Generated Data Market
10.4.3. Japan Car Generated Data Market
10.4.4. Australia Car Generated Data Market
10.4.5. South Korea Car Generated Data Market
10.4.6. Rest of Asia Pacific Car Generated Data Market
10.5. Latin America Car Generated Data Market Snapshot
10.5.1. Brazil Car Generated Data Market
10.5.2. Mexico Car Generated Data Market
10.5.3. Rest of Latin America Car Generated Data Market
10.6. Rest of The World Car Generated Data Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Drust
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Product Summary
11.2.1.5. Recent Developments
11.2.2. Sight Machine
11.2.3. ZenDrive
11.2.4. PitStop
11.2.5. CARFIT
11.2.6. Tourmaline Labs
11.2.7. Carvoyant
11.2.8. HARMAN International
11.2.9. Zene
11.2.10. Carffeine
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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