Connected cars are slow but steady in winning a significant share of the automotive market. Through a multitude of sensors and other connected IoT devices, cars generate volumes of data on how they are used, who is using them, where they are and what surrounds them. With an increasing interest in shared mobility and advanced vehicle autonomy, the amount of data connected cars produce will grow exponentially. The question is, who can use this car-generated data and how? Also, should automotive market players even bother looking into vehicle data monetization? Together with automotive experts from Intellias, we will explore the answers to each question.
In this article, you’ll discover:
- The market predictions and trends for collected data monetization
- What challenges OEMs experience when creating business models for data monetization
- How automakers are approaching the opportunity to monetize personal and car data
- The role of IT vendors in overcoming the challenges of personal data monetization
Market predictions and trends for collected data monetization
Connected vehicles produce massive amounts of information via in-car microphones, cameras and sensors. Not only do these IoT devices provide valuable insight into the driver’s behavior and preferences, but they also observe passengers and bystanders. This allows for collecting a lot of non-critical data along the way.
Big data is vital for ensuring an autonomous car sees, hears and reacts to the environment. It also serves as a resource for multiple use cases expanding beyond the automotive field into retail, finances, entertainment and more.
Participants of global data monetization market
Source: Markets and Markets
McKinsey discovered the overall revenue pool from car data monetization, at a global scale, could total $450 – $750 billion by 2030.
One thing that remains stable, however, is the customer being the center of everything.
The differentiator of success for enterprises will be the ability to offer high-quality products and services earlier than competitors. But, will the customers be willing to share their personal data in exchange for advanced data-driven solutions? The level of willingness significantly varies across use cases. Customers are more ready to share information when they understand the benefits and are confident their data is protected. Regulations of data usage and the ability to provide advanced security for personal information, are vital. One cannot merely sell gathered data to third parties. Instead, it is possible to build partnerships with service providers and create solutions that will enable consumers to live more comfortably.
To capitalize on the potential of vehicle data monetization, OEMs and Tier 1 companies must build new business models and partnerships around these global trends:
- connectivity and autonomy
Higher efficiency of ADAS and new features for drivers are transforming cars into smart platforms. These features allow users to utilize their driving time by fulfilling routine tasks. New functionalities will open the doors to a plethora of use cases for self-driving car data monetization.
The number of hybrid and electric vehicles is increasing on the roadways, becoming both producers and consumers of big data. Vehicle data monetization use cases will offer multiple facets of exploration: developing smart charging algorithms, policies for charging stations siting, solving energy efficiency issues, power distribution systems and so on.
By 2030, McKinsey estimates one out of ten cars could be a shared vehicle. This trend can fuel mobility solutions which will create personalized experiences in shared vehicles, encouraging consumers to optimize their driving time without giving up their usual comforts.
The ecosystem of OEM partnerships, with enterprises from other industries, has the potential to rip benefits from connected vehicles and bring the promise of personal data monetization into reality. Market players who manage to build and maintain trust among customers, will be the first to profit from personal data monetization. Still, there are quite a few challenges on the horizon for OEMs and their partners.
Challenges in creating business models for data monetization
Barriers to personal data monetization depend on customers, in one way or another, as well as the companies’ ability to win their trust. Vehicle data monetization comes with legal, social and technical issues which OEMs and their partners are currently working through.
Legal challenges of personal data monetization
Existing data privacy laws significantly reduce the anticipated impact of autonomous car data. To be specific, there are many privacy rights that dictate what data is collected and how it can be used:
- GDPR and CCPA
Under these laws, individuals have the right to insist on deleting specific personal data, restrict its disclosure and processing, or sell it. More than fifteen states in the US are considering similar privacy laws. This means OEMs and Tier 1 companies that want to leverage non-essential data, must first approve it with their customers.
- Biometric laws
Autonomous vehicles will heavily rely on biometric data to identify a driver or passenger without inconveniencing them. With technology being increasingly popular across industries, there are many legislative debates on the restriction of biometric data usage and improved security obligations. For example, BIPA presupposes that companies are obliged to transparently use biometrics and take advanced measures to protect data. In this way, data monetization use cases are limited and the cost for compliance increases.
- Children’s privacy rights
Since vehicles are also collecting the personal data of passengers, OEMs and Tier 1 companies must face one of the strictest data privacy laws – children’s rights protection. GDPR, for instance, requires consent for using a child’s personal information. This is challenging, as it can be difficult to separate the vehicle data of adult passengers from the children. If a child is on board, a company cannot use the data from this particular ride without getting consent from the parents.
Social challenges of self-driving car data monetization
The first task for all companies that want to capitalize on vehicle data is to communicate the advantages of using this information to their customers. 84% of executives state communicating the value proposition to users is a highly relevant approach for car data monetization.
Customers should understand how data-driven features and solutions can improve their lives. They should also be sure their personal information is well-protected and used responsibly. This leaves OEMs and their partners the task of offering an equipollent exchange of data for advanced services or features. While frequent travelers and young drivers show interest in data-enabled, in-car solutions, engaging the remaining audience will be more of a challenge for partnering companies rather than OEMs.
Technological challenges of vehicle data monetization
Organization of business processes and advanced levels of data protection are key issues in data monetization. Volumes of collected data must be adequately processed, analyzed and visualized before being monetized. This forces the adoption of new connected services and agile partnerships.
Critical components for data monetization
The development of data-enabled solutions is outside the scope of any single player, leaving collaboration as the only option. OEMs, Tier 1 companies, various Tier 2 enterprises, vendors and product owners, must cooperate to successfully establish vehicle data monetization.
Outside of organizational challenges, automotive leaders are faced with ensuring data protection. This is a separate, but paramount issue that is being met by leveraging blockchain.
Role of blockchain in data monetization
IBM found that 62% of customers prefer car brands with better security and privacy.
In 2014, the Alliance of Automotive Manufacturers issued a set of guidelines called “Consumer Privacy Protection Principles for Vehicle Technologies and Services.” The guidelines specify OEMs must use the data transparently, allow a choice in data usage, respect the context, and provide security, integrity, access and accountability of the data. Blockchain is key in solving some of these privacy issues such as transparency, security, integrity and access.
Blockchain’s decentralization and powerful cryptography offers one of the most effective solutions to the challenges of vehicle data cybersecurity. Porsсhe is already investing in blockchain startups. Prototypes include parking payments, remote access to cars, vehicle history validation and more. With the current mobility trend, blockchain is essential for ensuring personal experiences in shared cars and inventing new, convenient ways to access the vehicle.
Acknowledging the importance of blockchain in the industry allows automakers and Tier 1 companies to work on various solutions such as decentralized registries, machine-to-machine transfers of data and secure platforms for data transmission. At the end of the day, blockchain is one of the main tools to effective vehicle data monetization. OEMs will apply decentralized ledgers to secure the access of exclusive data, resell and reuse it:
- to protect exclusive information from competitors
- to sell or trade data on blockchain-based marketplaces
- to incorporate gathered vehicle data into improved and personalized product offerings
For autonomous and connected vehicles, revealing the full potential of blockchain is urgent. In fact, associations of OEMs and blockchain startups are already researching and implementing solutions to complement IoT technology and provide new ways for monetizing car data: Uber with VLB, Volkswagen with IOTA, Porsche with XAIN and others.
How OEMs approach the opportunity to monetize personal and car data
Connected cars generate various categories of data: essential and non-essential for driving, more or less sensitive and personalized, focused on the driver specifically, car data, surroundings, etc. This allows various use cases of vehicle data monetization to emerge. Here are the specific categories of such use cases:
- environment and road condition: real-time maps, advanced car adaptation, live reports on road conditions
- car status: vehicle diagnostics, emergency calls, predictive and remote maintenance, service appointments
- driver behavior: personalized insurance plans, automatic road payments, reduced engineering costs, personalized product offerings
- personal preferences: customized vehicle settings, e-commerce, personalized ads
- in-car communication: voice control, voice-enabled functions, virtual assistants
The primary data monetization models for automotive market players are data-driven products and services for customers, personalized advertising, sale of data to third parties, reduction of costs through more efficient R&D, use of data to enhance safety and security for drivers and vehicles.
Taking these models into account, companies wanting to benefit from vehicle data monetization should first adopt a particular role within the new automotive data market.
Roles to adopt within the automotive data market
A unique market, based on vehicle data, is set to create new cash flows. This will not only benefit OEMs and Tier 1 companies, but also businesses across different industries: from insurance and e-commerce, to providers of specific equipment or high-end software. However, it should be noted that everything must be customer-centered, for only customers can define the level to which their personal data will be used.
How IT vendors can help OEMs overcome the challenges of personal data monetization
While OEMs are capable of collecting customer information via car IoT devices, they lack the resources, processes and systems to organize this information into actionable form. Partnering with data analytics experts provides an excellent opportunity to compensate for the lack of infrastructure and talent, while accelerating the development of innovative data-driven products.
To succeed in car data monetization, OEMs should establish partnerships with the companies that show
- innovative capabilities
- working agile methodologies
- expertise in the automotive domain
Being one of the leading Tier 2 partners for automotive companies, Intellias possesses great knowledge in data analytics, machine learning algorithms, IoT, cloud computing and other technologies, which are all necessary for creating connected and autonomous vehicle solutions. Find out more about Intellias’ automotive domain experience by contacting one of our experts.
Summing it up
Connected and autonomous cars create new business opportunities for personal data monetization. However, organizational, technological, social and regulatory issues make strategic partnerships critical for OEMs. Players in the car data monetization market are collaborating with multiple entities such as high-tech suppliers, public institutions and, more importantly, their own customers. Communicating the value of shared personal data to customers is the first step in data monetization success. When this happens, automotive market players are forced to adopt the following rules as a basis for car data monetization:
- never use data against your customers’ wishes
- ensure transparency in data usage and in the “terms and conditions” acceptance
- invest in data security and refrain from misusing the information provided
- provide customers with the choice of what is shared and state the purposes clearly
- provide the option of revising and changing data sharing parameters
- make gathered data available to customers
Winning customers’ trust will be vital for further progress in leveraging car information. Any advancements towards self-driving car data monetization should be based on customer-centered principles, and the idea of creating a more comfortable and safe environment for drivers.