The road to profitability: Why automotive data monetization is the next big thing

automotive data monetization

With the advent of advanced technologies and the emergence of connected vehicles, the amount of data generated by vehicles has increased manifold. To leverage this data, various industry players are developing the mechanism and infrastructure for automotive data monetization, with the intent of providing better products and services to their customers and developing a competitive advantage in the market for themselves. 

Vehicle-generated data is increasing exponentially. It is estimated that there will be around 470 million connected vehicles on highways around the world by 2025 and each of these connected vehicles will produce roughly 25 gigabytes of data per hour. The market value associated with a vehicle is no more restricted to just its mechanical characteristics such as maximum speed, gears, or engine, but also to the vehicle’s connectivity and electronic functionalities.

Although the potential of connecting services and data monetization is noteworthy, monetizing car data at a larger scale remains a big challenge. Players in the ecosystem are continuously striving to develop the infrastructure and expertise to overcome these challenges by formulating a comprehensive data monetization strategy.

Related reading: 5G Monetization – a future reality check

Automotive data monetization ecosystem

Connected vehicles provide a unique customer experience while simultaneously delivering cost and revenue benefits to mobility companies including OEMs, suppliers, dealers, insurers, fleets, tech players and beyond. Here’s a depiction of the entire ecosystem:


Macro categories of value creation models

Industry players focus on 3 main macro-categories of value creation models. Here’s a quick snapshot:


Notably, comprehensive data monetization efforts are utilized for various purposes across a company’s business to develop a competitive advantage in the market while providing value-added services to its customers in the form of personalized services and better offerings.

Market overview

  1. Market size
    The global automotive data monetization market is projected to grow from USD 123.3 million in 2019 to over USD 20 billion in 2030, at a CAGR of approximately 58.82%, according to Statista.     

2. Key market drivers

  • Increased application and development of advanced analytics and big data in automotive applications to provide extra features and services in cars, lower operating costs, and investment, and efforts to improve driver and passenger safety are major factors driving the global automotive data monetization market.
  • Insurance companies: Various insurance companies are providing lucrative and profitable deals to customers after analyzing the car data.
  • Pay-as-you-drive (PAYD) and pay-how-you-drive (PYHD) are two other widely popular usage-based insurance concepts. PAYD automobile insurance is a cost-effective option for drivers who don’t drive frequently while PYHD insurance policies consider the moving ability when determining premiums.
  • Clients who agree to receive in-car advertising and exchange information with insurers may be able to save money at the moment of sale and on their insurance rates.
  • Predictive maintenance segment: Thorough analysis of the data about vehicle health provides useful insights related to the vehicle maintenance which can be leveraged for providing value-added services to the customers.
  • Predictive maintenance is used by businesses with high-value assets, such as fleet management companies, to assist in controlling the rising costs of maintaining their equipment. Predictive maintenance software collects data and monitors the condition and performance of in-service equipment, such as a fleet of vehicles, to reduce the risk of failure. Fleet managers may readily predict impending breakdowns by analyzing data from various sensors present on the fleet vehicles.
  • Car data can reduce breakdown risk/downtime with predictive maintenance, concierge services can make regular tasks (such as car washing and refueling) very simple, and networked infotainment can give easy-to-access entertainment.

Key initiatives by the players in the ecosystem

The global automotive data monetization market is highly fragmented, with a limited number of companies accounting for the majority of market share and revenues. Below are a few key initiatives:

initiatives for data monetization

Challenges in automotive data monetization

Vehicle data monetization is not gaining traction as fast as expected. According to a Capgemini report the challenges can be understood from the perspectives of end customers, automotive OEMs, and service providers.


End customers’ perspective 

  • Hesitancy to share personal data: Many end customers are hesitant to share data as they are not aware of the benefits associated with data sharing and at the same time, they are concerned about their data security.
  • Lack of awareness amongst customers: There is not enough awareness about the purpose of data sharing. About 80% are not aware of the kind of data their vehicle is transmitting. Thus, a lack of understanding towards the technology is a major barrier to realizing the full potential of the technology.
  • Need for incentive to share the data: Many customers are willing to share the data if they are provided with incentives and discounts which increases the cost for the automakers.

Automotive OEMs’ perspective

  • Hesitancy to share their data asset: One of the major roadblocks in an expansion of the data monetization market is the reluctancy exhibited by the automotive OEMs towards data service providers as they perceive them as their competitors rather than enablers for accepting the technology and as a result end up being merely reservoirs of data. 
  • Lack of industry standards: Market uncertainty hinders the growth of the market on one hand and lack of technical standards and rules and regulations around data use guidelines is hampering the progress on the other hand. The lack of common data and platform standards is another major inhibitor. 
  • Lack of infrastructure: Setting up a user-friendly platform infrastructure is tedious. OEMs lack a universal data collector strategy due to which they are left daunted by the tremendous amount of data generated by their connected vehicles.
  • Lack of skills and technological development: Most of the traditional automotive OEMs lack IT infrastructure, skills, and capacities for leveraging the data so generated.

Service providers’ perspective

  • Increasing cost and risk associated with data sharing: The investment required for the infrastructure, for sharing the data between OEMs and service providers is massive. And as automotive OEMs fail to provide data via standardized APIs, service providers feel that obtaining necessary vehicle data sometimes entails undue cost and additional technical skills.
  • Need for more comprehensive data from customers: Another issue mentioned by suppliers is the lack of historical data. Service providers are therefore considering additional data collection methods using telematic data from the customer’s phone and other smart devices.
  • Restricted data sharing by OEMs: Automotive OEMs withhold their customer data intentionally due to concerns about data protection as they feel that the onus to protect their customer data lies with them. Automotive OEMs also want to safeguard their aftersales market by not revealing crucial customer data.

Actions for facilitating data monetization

To overcome these obstacles, the following actions are recommended:


BMW’s approach towards data monetization

Data forms an essential part of developing innovative services and new features and enhancing efficiency, quality, and safety. The BMW Group processes data for specific purposes that benefit the customer and society and drive future developments – from local hazard warnings and on-street parking information to the personalization of digital services. The BMW Group regards security and privacy as the most important aspect. BMW provides customers with transparency and control over private data. Fleet data is processed in a manner such that the anonymity is maintained i.e. without any sort of mention to the customer. The company also provides protection from unauthorized access by third parties.

BMW data strategy

Data collection strategy:

  • BMW and MINI customers can request a data archive of their car data  with the help of  BMW ConnectedDrive or MINI Connected customer portal, to access their telematics data stored at the time of the request.
  • Customers can also utilize their car data to hand them over to various service providers, such as insurance companies or workshops, to access numerous personalized services.
  • Personal vehicle data is stored in BMW and MINI car data on BMW Group servers, where it can be accessed at any time by the customers. The customer has the upper hand to control and decide whether they want to share their data or not.

Maintaining the anonymity of data:

  • Vehicle data is anonymized internally before being processed and all the information pertaining to the customer is eliminated from the data set, and only information required for specific service purposes may be used for processing. 
  • The extracted information narrows down to, for example, “DSC activated, GPS position, time, temperature,” but no information related to the vehicle that registered the event is disclosed.
  • From this data set, they then determine the service required but do not disclose the identity of the vehicle. 

Assessing the service requirement and contacting the customer:

  • To identify and rectify the loopholes and defects in individual vehicles or a model series, it is required that the partners and suppliers obtain data related to a particular vehicle.
  • References to persons are concealed using a pseudonym to hide personal information, such as the vehicle identification number which means that the business partners and service providers will not be able to identify the vehicle identification number or the owner of the vehicle.
  • On analysis of the data, if it is found that safety-related services are needed, the BMW Group then decrypts the pseudonym to contact the vehicle owner.

Thus, in this way, it can be observed that BMW, through its data strategy, is providing safety and transparency of data to its customers on the one hand and personalized services on the other hand.

Automotive data monetization is the next big thing in today’s digital economy. However, its implementation and success depend upon several crucial factors like level of execution, leadership, data strategy of various players in the ecosystem, and many more. Recent advances in technology and tools for data analysis are propelling the growth of the market but without a proper and systematic approach toward execution, the end results of data monetization will be jeopardized.

 Further, the growth of the market is bolstered by the companies in the expanded ecosystem (such as insurance companies, fleet owners, automotive dealers, telco operators, etc. who are striving to leverage the data from the automotive sector to expand their product offerings and services in the market for the customers.

With the increase in the number of connected services and associated data, the nature of business is being modified with new aspirations and demands from customers. The companies in the ecosystem are resorting to organic and inorganic strategies like partnerships, and collaborations to develop and explore the data monetization market.

However, this huge amount of data generated has its own threats and challenges that need to be steered to develop a competitive edge in the market. Thorough use of insights from market interactions can be utilized for growth and development across industries in the economy. Netscribes supports businesses in achieving excellence through custom data and insights services. To know more contact us.

Based on insights by Kanika Shukla, Senior Analyst, Netscribes

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