Automotive Data Monetization is the practice of collecting, processing, and selling data generated by vehicles and their occupants for commercial purposes. This data encompasses information like vehicle performance, driver behavior, location, and more. It is collected through connected car technologies and sensors embedded in vehicles, and then analyzed to extract valuable insights. Businesses can monetize this data by selling it to various stakeholders, including insurance companies, advertisers, transportation service providers, and urban planners. It's a growing trend in the automotive industry, offering new revenue streams for manufacturers, service providers, and creating opportunities for personalized services, improved safety, and more efficient transportation systems.
The global automotive data monetization market is estimated to grow with a CAGR of 63.67% during 2020-2030 and reach a market size of $20.34 Billion by the end of 2030. The products in data monetization can take the form of consumable data sets, analysis results, operational applications containing these results, and numerous others. Data can also be monetized as reports, established digital platforms, extensions of digital platforms, provision of new services, or incorporation into new business models. Data products bring tangible benefits such as delivering better insight into customers and improving customer experience. This, in turn, leads to increased customer loyalty. Moreover, data monetization optimizes data usage and helps attain maximum value potential by collecting information about market demand, data’s shelf life, competition, potential customers, and other essential parameters. These advantages result in customer-based product improvements and new revenue sources.
Insurance Segment Dominates Automotive Data Monetization Market
Among the various end users of automotive data monetization market, insurance segment dominated the market in 2019 and is expected to maintain its dominance throughout the forecast period, 2020-2030. Insurance companies globally are engaging with the monetization/data service providers to build new capabilities for flexible next-generation insurance products based on the connected car datasets. Insurance companies use the connected car data for driver behavior monitoring and feedback, accident reconstruction, and new driver education.
Direct Segment Dominates Automotive Data Monetization Market, by Type
Direct monetization involves selling products, features, and services directly to the customer. The segment dominated the automotive data monetization market in 2019 and is expected to maintain its dominance throughout the forecast period. Some of the examples of direct monetization encompasses over-the-air software add-ons, networked parking service, connected navigation service, and theft protection service, among others.
Cloud Segment Dominates Automotive Data Monetization Market, by Deployment Type
Cloud data storage is comparatively cheaper than on premise solutions. Companies can buy a certain amount of storage space based on their requirement needs using the cloud. The ability to access data from anywhere, anywhere is also a benefit of cloud data storage.
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The market research study offers a wide perspective of different types of data monetization and applications they are used for. The report also provides an analysis of the market penetration of these types in different applications and their growth opportunities across different regions as well as countries. The study focuses on the changing landscape of the automotive data monetization market, owing to the significant developments made by the leading players.
North America Foreseen to be the Largest Market in the Automotive Data Monetization Market
North America is expected to lead the automotive data monetization owing to its strong presence of large and small companies coupled with rapid technological innovations occurring in the region. This would eventually benefit both the customer and the company. Europe is expected to follow North America in terms of growth in the forecast period. China, due to the rapid technological advances in the region, is the world leading both manufacturer and buyer of motor vehicles. However, in comparison with the global scenario, the penetration of automotive data monetization is comparatively lower in the region.
Competitive Landscape
The competitive landscape of the automotive data monetization market consists of different strategies undertaken by major players across the entire value chain to gain market presence. Some of the strategies adopted by data monetization providers are product launches, mergers and acquisitions, partnerships, and collaborations.
Among all the strategies adopted, partnerships, collaborations, and contracts have dominated the competitive landscape. Continental AG, IBM, Oracle Corporation, Amazon Web Services, and Harman International Industries are some of the leading players in the automotive data monetization market.Most of the data monetization providers are of different financial capability, and the industry landscape is fairly competitive because of the small number of players in the market.
Therefore, innovation and development have been the key factors for the large-scale growth in this market. To increase their overall global footprint, service providers are expanding their businesses and are also entering strategic partnerships to target a greater audience.
Key Questions Answered by This Report:
- For a new company looking to enter the market, which areas could it focus upon to stay ahead of its competitions?
- How do the existing market players function to improve their market positioning?
- Which are the promising companies that have obtained financial support to develop their service and markets?
- How does the supply chain function in the automotive data monetization market?
- Which companies have been actively involved in innovation through patent applications, and which products have witnessed maximum patent applications during the period 2017-2020?
- Who are the players catering to the demand for different data?
- What were the demand patterns of data providers across the application areas in different regions and countries in 2019, and how is the demand is going to shape up during the period 2019-2030?
