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市場調查報告書

商品編碼

1071421

汽車資料分析:市場預測(2022年～2027年)

Automotive Data Analytics Market - Forecasts from 2022 to 2027

出版日期: 2022年03月08日 | 出版商:

Knowledge Sourcing Intelligence | 英文 102 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

全球汽車資料分析的市場規模在2020年估算為10億9,100萬美金，在預測期間內預計將以23.87％的年複合成長率擴大，2027年成為48億8,300萬美元。

本報告提供汽車資料分析的世界市場調查，提供市場規模和預測，市場促進因素及課題，市場趨勢，各市場區隔的市場分析，競爭情形，主要企業的簡介等系統性資訊。

簡介
北美
- 美國
- 加拿大
- 墨西哥
南美
- 巴西
- 阿根廷
- 其他
歐洲
- 德國
- 法國
- 英國
- 義大利
- 其他
中東和非洲
- 沙烏地阿拉伯
- 阿拉伯聯合大公國
- 南非
- 其他
亞太地區
- 中國
- 印度
- 日本
- 韓國
- 台灣
- 泰國
- 印尼
- 其他

第9章競爭環境與分析

主要企業策略分析
新興企業和市場收益性
合併，收購，協定，及合作
供應商競爭力矩陣

第10章企業簡介

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.

簡介目錄

Product Code: KSI061612080

The automotive data analytics market was valued at US$1.091 billion in 2020 and is expected to grow at a CAGR of 23.87% over the forecast period to reach a total market size of US$4.883 billion by 2027.

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 data generated enables stakeholders in the automotive industry 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 and 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 production of electric vehicles in order 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 service 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 COVID-19 in January 2020, with online self-service insurance claims accounting for 40% of the services.

Growth Factors

Advancements in technology:

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 automobiles aids 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 EVs might damage the battery. Predictive analytics combined with artificial intelligence (AI) improves the feedback and monitoring system for batteries in order to reduce unnecessary damage and thus increase battery life.

Restraints:

Concerns regarding data privacy:

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 about 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 concerns about data privacy and security will actually hinder the adoption of automotive data analytics, particularly in the insurance industry.

The Impact of COVID-19 on the Automotive Data Analytics Market:

The COVID-19 pandemic has caused market uncertainty by delaying supply chains, impeding company growth, and raising concerns 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. Automotive analytics market participants are using specific methods to manage operations to overcome the financial slump, such as reduced budgets, longer equipment life cycles, reduced employee numbers, and lower pay.

Key Developments

Epicor expanded its automotive data analytics portfolio in September 2021 through an exclusive partnership with SideKick360, a prominent web-based reporting tool that enables tyre dealers and other similar businesses to generate more profit from each service opportunity.
Ford launched the new "RoadSafe" concept in September 2021, in collaboration with a partnership co-funded by the UK's innovation agency, Innovate the UK, to predict traffic accident locations based on data from connected vehicles, roadside sensors, and traffic collision reports.

Market Segmentation

By Deployment

On-premise

Cloud

By Application

Driver Performance Analysis

Predictive Maintenance

Safety and Security Management

Traffic Management

Others

By End-User

Original Equipment Manufacturers (OEMs)

Insurers

Fleet Owners

Regulatory Bodies

Others

By Geography

North America

USA
Canada
Mexico

South America

Brazil
Argentina
Others

Europe

Germany
France
UK
Italy
Others

Middle East and Africa

Saudi Arabia
UAE
South Africa
Others

Asia Pacific

China
India
Japan
South Korea
Taiwan
Thailand
Indonesia
Others

1. Introduction

1.1. Market Definition
1.2. Market Segmentation

2. Research Methodology

2.1. Research Data
2.2. Assumptions

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

5.1. Introduction
5.2. On-premise
5.3. Cloud

6. Automotive Data Analytics Market Analysis, by Application

6.1. Introduction
6.2. Driver Performance Analysis
6.3. Predictive Maintenance
6.4. Safety and Security Management
6.5. Traffic Management
6.6. Others

7. Automotive Data Analytics Market Analysis, by End-User

7.1. Introduction
7.2. Original Equipment Manufacturers (OEMs)
7.3. Insurers
7.4. Fleet Owners
7.5. Regulatory Bodies
7.6. Others

8. Automotive Data Analytics Market Analysis, by Geography

8.1. Introduction
8.2. North America
- 8.2.1. USA
- 8.2.2. Canada
- 8.2.3. Mexico
8.3. South America
- 8.3.1. Brazil
- 8.3.2. Argentina
- 8.3.3. Others
8.4. Europe
- 8.4.1. Germany
- 8.4.2. France
- 8.4.3. UK
- 8.4.4. Italy
- 8.4.5. Others
8.5. Middle East and Africa
- 8.5.1. Saudi Arabia
- 8.5.2. UAE
- 8.5.3. South Africa
- 8.5.4. Others
8.6. Asia Pacific
- 8.6.1. China
- 8.6.2. India
- 8.6.3. Japan
- 8.6.4. South Korea
- 8.6.5. Taiwan
- 8.6.6. Thailand
- 8.6.7. Indonesia
- 8.6.8. Others