The automotive data analytics market was valued at US$1.221 billion in 2019 and is expected to grow at a CAGR of 21.46% over the forecast period to reach a total market size of US$4.763 billion by 2026.
In the automotive sector, digitization has become a critical driver of innovation. With automobiles generating massive amounts of data in seconds, the chance to provide exceptional customer experiences and business operations is more important than ever. At the moment, automobiles have at least 50 sensors meant to capture more comprehensive data such as speed, emissions, distance, resource utilization, driving behavior, and fuel consumption. The produced data allows stakeholders in the automobile sector to use it for additional research, relationship analysis, and improved usage.
Factors such as an increase in the trend of networking solutions in automotive, an increase in the usage of cloud-based technology for smart fleet management solutions, and an increase in concern for vehicle safety and security are likely to fuel market expansion. However, the high installation costs and security issues associated with data transfer are impeding industry expansion. Market participants forming strategic alliances with OEMs, insurers, and fleet operators to obtain a competitive edge, increasing development in semi-autonomous & autonomous cars, and increased demand from emerging nations are some of the reasons predicted to drive market expansion.
Due to the rising dominance of connected and autonomous cars, Asia-Pacific is the fastest-growing region. Furthermore, the increased penetration of new technology firms finding their way into the automotive sector is projected to give rise to a new era of automotive analytics. China announced a target of at least 30 million autonomous vehicles by 2028, which is likely to boost demand for automobile analytics. The government has been highly active in embracing technology to assist with policy execution. China also intends to relax quotas meant to encourage the manufacture of electric vehicles in an effort to assist automakers in reviving sales.
Ping An Insurance announced in April 2020 that the "Ping An Auto Owner" app has reached 100 million registered users. The app has 25 million monthly active users and is one of the top-ranked automotive servicing applications in China. Ping An Property & Casualty automobile insurance clients account for almost half of the app's users. The app makes use of Ping An's artificial intelligence (AI) and big data analytics technologies on a platform to link automobile owners to dealers and other automotive service providers. The app has served roughly 12.3 million users since the outbreak of the COVID19 in January 2020, with online self-service insurance claims accounting for 40% of the services.
The growth of predictive analytics is a significant element driving the industry. This technology is used as a collision-avoidance system in automobiles by utilizing sophisticated sensors, massive and fast data, and car-to-car connections. The increasing implementation of such technology, particularly with the expansion of the autonomous vehicle industry, will be a significant driver for Automotive Data Analytics. Furthermore, automobile malfunctioning is a major cause of accidents. These malfunctions are frequently caused by human negligence in the timely servicing and maintenance of vehicles. Predictive analytics systems notify the owner of the possible need for maintenance before a malfunction occurs. Data obtained from different sensors installed in automobile aid in the performance of predictive maintenance chores. As the demand for electric cars grows, the market has the potential to expand. Variations in voltages during charging in EV(s) might damage the battery. Predictive analytics combined with artificial intelligence (AI) improves the feedback and monitoring system for batteries to minimize unnecessary damage, therefore increasing battery life.
The most severe challenge with Data Analytics is dealing with the delicate subject of data privacy and security, which most automobile businesses are dealing with. Security and privacy concerns are rising as corporations feed more and more customer and supplier data into powerful, AI-powered algorithms, resulting in the creation of additional sensitive information unknown consumers and workers. This is especially true in the insurance industry, where collecting customer data has been at the forefront of big data challenges. Since a data breach or security failure may be devastating, the insurance industry is controlled by stringent adherence to rules and governance. These data privacy and security concerns will hamper the adoption of automotive data analytics, particularly in the insurance industry.
The COVID-19 pandemic has caused market uncertainty by delaying supply chains, impeding company growth, and raising concern among customers. End users, such as automotive OEMs, dealers, insurers, and fleet operators, are anticipated to prioritize working capital management, with little room for substantial investment in sophisticated technology. However, due to the high installation cost and other infrastructure needs, there is a significant likelihood of sales momentum for automotive analytics technology. To overcome the financial slump, automotive analytics market participants are using specific methods to manage operations, such as lowered budgets, longer equipment lifecycles, reduced employee numbers, and lower pay.
|Market size value in 2019||US$1.221 billion|
|Market size value in 2026||US$4.763 billion|
|Growth Rate||CAGR of 21.46% from 2019 to 2026|
|Forecast Unit (Value)||USD Billion|
|Segments covered||Deployment, Application, End-User, And Geography|
|Regions covered||North America, South America, Europe, Middle East and Africa, Asia Pacific|
|Companies covered||Microsoft, Agnik LLC, Harman International Industries Inc. (Samsung Electronics Co. Ltd), SAP SE, IBM Corporation, Genetec Inc., Teletrac Navman US Ltd., Inquiron Ltd, Cloudmade Ltd, Intelligent Mechatronic Systems Inc.|
|Customization scope||Free report customization with purchase|
Frequently Asked Questions (FAQs)
Q1. What are the growth prospects for the automotive data analytics market?
A1. The automotive data analytics market is expected to grow at a CAGR of 21.46% during the forecast period.
Q2. What will be the automotive data analytics market size by 2026?
A2. The global automotive data analytics market is expected to reach a market size of US$4.763 billion by 2026.
Q3. What is the size of the global automotive data analytics market?
A3. Automotive Data Analytics Market was valued at US$1.221 billion in 2019.
Q4. Which region holds the maximum market share in the automotive data analytics market?
A4. The Asia-Pacific region is projected to dominate the automotive data analytics market due to the rising dominance of connected and autonomous cars.
Q5. What factors are anticipated to drive the automotive data analytics market growth?
A5. The increasing implementation of such technology, particularly with the expansion of the autonomous vehicle industry, will be a significant driver for the automotive data analytics market.
1.1. Market Definition
1.2. Market Segmentation
2. Research Methodology
2.1. Research Data
3. Executive Summary
3.1. Research Highlights
4. Market Dynamics
4.1. Market Drivers
4.2. Market Restraints
4.3. Porters Five Forces Analysis
4.3.1. Bargaining Power of End-Users
4.3.2. Bargaining Power of Buyers
4.3.3. Threat of New Entrants
4.3.4. Threat of Substitutes
4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis
5. Automotive Data Analytics Market Analysis, by Deployment
6. Automotive Data Analytics Market Analysis, by Application
6.2. Driver Performance Analysis
6.3. Predictive Maintenance
6.4. Safety and Security Management
6.5. Traffic Management
7. Automotive Data Analytics Market Analysis, by End-User
7.2. Original Equipment Manufacturers (OEMs)
7.4. Fleet Owners
7.5. Regulatory Bodies
8. Automotive Data Analytics Market Analysis, by Geography
8.2. North America
8.3. South America
8.5. Middle East and Africa
8.5.1. Saudi Arabia
8.5.3. South Africa
8.6. Asia Pacific
8.6.4. South Korea
9. Competitive Environment and Analysis
9.1. Major Players and Strategy Analysis
9.2. Emerging Players and Market Lucrativeness
9.3. Mergers, Acquisitions, Agreements, and Collaborations
9.4. Vendor Competitiveness Matrix
10. Company Profiles
10.2. Agnik LLC
10.3. Harman International Industries Inc. (Samsung Electronics Co. Ltd)
10.4. SAP SE
10.5. IBM Corporation
10.6. Genetec Inc.
10.7. Teletrac Navman US Ltd.
10.8. Inquiron Ltd
10.9. Cloudmade Ltd
10.10. Intelligent Mechatronic Systems Inc.
Harman International Industries Inc. (Samsung Electronics Co. Ltd)
Teletrac Navman US Ltd.
Intelligent Mechatronic Systems Inc.
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