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A recent study found that today’s vehicles create, process and exchange approximately 50 GB of data per day on their internal network. And given the global demand for automotive data, this represents a huge opportunity for revenue generation. Namely, through automotive data monetization.
In this article, we’ll look at the sources of automotive data, reasons for the monetization boom, how to sell automotive data, guidelines for an effective data monetization strategy, and example companies that are running an effective automotive data business.
1. Sources of Automotive Data
There are several sources or generators of automotive data:
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Let’s have a closer look at each of them.
Original Equipment Manufacturers
Original Equipment Manufacturers (OEMs) are a primary source of automotive data. Modern vehicles are equipped with sensors that continuously collect data on various parameters such as vehicle performance, diagnostics, and driver behavior. OEMs leverage this data for numerous purposes, including improving product design, enhancing safety features, and providing aftermarket services such as predictive maintenance.
Global Positioning System (GPS)
Global Positioning System (GPS) technology plays a pivotal role in generating automotive data, particularly for location-based services. GPS-enabled devices, such as navigation systems and smartphone apps, track vehicle movement in real-time, providing valuable insights into travel patterns, route optimization, and traffic congestion. Satellite Navigation (SATNAV) systems, in particular, offer precise location tracking capabilities and vehicle position data.
Infrastructure Providers
Infrastructure providers, including local authorities and city governments, also contribute to the pool of automotive data through the management of roads, traffic signals, and parking facilities. By deploying sensors, cameras, and other monitoring devices, these entities collect data on traffic flow, road conditions, and parking availability, which are precisely the kind of insights that can be sold with an effective automotive data monetization strategy.
Third-party sources
Google and other third-party providers of automotive data play a crucial role in the industry ecosystem by offering extensive datasets, analytics tools, and APIs. Leveraging their vast resources and expertise in data management, these providers aggregate and analyze automotive data from various sources, including connected vehicles, GPS systems, and traffic sensors. They offer valuable insights into traffic patterns, navigation routes, and driver behavior.
2. Reasons Why Car Data Monetization is Booming
The automotive industry is booming, and so is the data monetization industry it’s spawned. Indeed, between 2024 and 2029, the car data monetization market is set to see a CAGR of 39.21%.
There are several reasons for this boom.
There are more connected cars on the road
Recent estimates state there’ll be around 470 million connected vehicles on highways around the world by 2025. ****The rise of connected cars has led to an exponential increase in automotive data monetization. Vehicles equipped with sensors, IoT devices, and connectivity features generate vast amounts of valuable data on vehicle performance, driver behavior, and environmental conditions.
From this data, stakeholders can extract insights, offer personalized services, and optimize operations. So connected cars are fueling data monetization strategies, driving revenue growth and fostering innovation in the automotive industry.
Customers expect personalized experiences
Today's consumers crave personalized experiences in every aspect of their lives, and the automotive industry is no exception. From customized infotainment systems to tailored maintenance schedules, car manufacturers and service providers are investing in and collecting data to deliver personalized experiences that cater to individual preferences and needs.
For example, the BMW ConnectedDrive and MINI Connected customer portals enable customers to access their telematics data. Car data also enables insurance companies to personalize their services, and so more insurance companies are buying automotive data to improve their customer engagement. This increased demand means there’s more data being monetized.
Manufacturing processes need to be more efficient
Another reason for the boom in car data monetization is the pressing need for more efficient manufacturing processes. As competition intensifies and consumer demand for customization grows, car manufacturers are under increasing pressure to streamline production, reduce costs, and minimize waste.
Data from IoT sensors, machine learning algorithms, and predictive analytics, manufacturers can help optimize every aspect of the production process. From predictive maintenance of machinery to real-time monitoring of inventory levels and supply chain logistics, data-driven insights enable manufacturers to identify bottlenecks, improve productivity, and enhance overall efficiency.
Training vehicles autonomous driving
Autonomous driving technologies has also been a catalyst for car data monetization. As manufacturers race to develop fully autonomous vehicles, the need for high-quality training data has never been greater. Training autonomous vehicles requires vast amounts of real-world data on driving scenarios, traffic patterns, and environmental conditions.
By collecting data from sensors, cameras, and radar systems installed in test vehicles, car companies can generate rich datasets that serve as the foundation for training and refining autonomous driving algorithms.
In addition to gathering data from their own test fleets, automakers can also monetize car data by collaborating with third-party partners, such as ride-hailing companies and delivery services. By sharing anonymized data on driving routes, traffic conditions, and vehicle performance, automakers can generate additional revenue streams while developing more reliable autonomous vehicles.
3. Guidelines for Successful Automotive Data Monetization
To monetize automotive data successfully, there are several crucial steps to follow. We’ll break them down so that your end-to-end data monetization strategy is completely operational.
Understanding Automotive Data Assets
Begin by comprehensively understanding the various types of automotive data assets available. This includes vehicle diagnostics, telemetry data, driving behavior data, GPS data, and more. Recognize the potential value of each type of data and how you can leverage it for monetization.
Identifying Target Markets and Stakeholders
Conduct market research to identify potential target markets and stakeholders interested in automotive data. This may include automotive manufacturers, insurance companies, fleet operators, smart cities planners, advertisers, and more.
Value Proposition Development
Define clear value propositions for potential clients based on the insights derived from automotive data. Highlight the benefits of leveraging this data, such as improved operational efficiency, risk mitigation, cost savings, and revenue generation opportunities. Tailor your value propositions to address the specific needs and pain points of each target market.
Monetization Models
Explore various monetization models for automotive data, such as Data-as-a-Service (DaaS), subscription-based models, pay-per-use models, and partnership agreements. Evaluate the pros and cons of each model in relation to your target markets and choose the most suitable approach for your business objectives.
Partnership Development
Forge strategic partnerships with key stakeholders in the automotive industry, including automakers, OEMs, insurance companies, and technology providers like data marketplaces. Collaborate with them to access valuable data sources, develop innovative solutions, reach more data buyers, and create new revenue streams. Leverage these partnerships to enhance your credibility, reach, and market presence.
Data Analytics and Insights
Invest in advanced data analytics capabilities to derive actionable insights from the automotive data you’re monetizing. Utilize machine learning algorithms, predictive analytics, and data visualization techniques to uncover hidden patterns, trends, and correlations. Package these insights into meaningful reports, dashboards, and APIs that add value to your clients' decision-making processes.
Ethical and Legal Considerations
Prioritize ethical and legal considerations in all aspects of automotive data monetization. Respect user privacy rights, adhere to data protection regulations like GDPR and CCPA, and implement stringent security measures to safeguard sensitive data. Build trust and transparency with clients by clearly communicating your data usage policies and practices.
Measuring Success and ROI
Establish key performance indicators (KPIs) to measure the success and return on investment (ROI) of your automotive data monetization efforts. Track metrics such as revenue generated, client acquisition and retention rates, customer satisfaction scores, and the impact of your data-driven insights on clients' business outcomes. Use these insights to refine your strategies and optimize your monetization efforts over time.
By following these guidelines, you’re set to effectively monetize automotive data and unlock new revenue opportunities while delivering value to clients and stakeholders across the automotive ecosystem.
4. Examples Companies that Monetize Automotive Data Successfully
In our final section, we hope to inspire your car data monetization endeavours by looking at some household names that have monetized data effectively.
INRIX
INRIX is a prime example of successful automotive data monetization through its provision of traffic and mobility analytics solutions. They collect real-time traffic data from various sources, including connected vehicles, GPS devices, and mobile apps, to provide insights into traffic flow, congestion, and travel times. INRIX monetizes this data by offering subscription-based services to businesses, governments, and transportation agencies, enabling them to optimize route planning, reduce congestion, and improve overall traffic management.
Peugeot
Peugeot has embraced automotive data monetization through its "Connected Services" offering. By equipping its vehicles with IoT sensors and connectivity features, Peugeot collects data on vehicle performance, driving behavior, and usage patterns. They leverage this data to provide value-added services to customers, such as remote diagnostics, predictive maintenance alerts, and personalized driving recommendations. Peugeot monetizes these connected services through subscription-based models and upselling additional features to enhance the overall driving experience.
Continental AG
Continental AG is a leading automotive supplier that has successfully monetized automotive data through its "Continental Automotive Cloud" platform. This platform aggregates data from connected vehicles, sensors, and other sources to provide a wide range of services, including predictive maintenance, fleet management, and over-the-air software updates. Continental monetizes this data by offering subscription-based access to its cloud-based services to automotive manufacturers, fleet operators, and other stakeholders in the automotive ecosystem.
IBM Corporation
IBM Corporation demonstrates successful automotive data monetization through its "IBM Watson IoT" platform. By integrating IoT devices, sensors, and analytics capabilities, IBM helps automotive companies harness the power of data to improve vehicle performance, enhance driver safety, and optimize operational efficiency. IBM monetizes automotive data by offering customized IoT solutions, consulting services, and cloud-based analytics platforms to automotive manufacturers, suppliers, and other industry players.
Tesla
Tesla exemplifies successful automotive data monetization through its extensive use of over-the-air software updates and vehicle telemetry data. Tesla vehicles are equipped with advanced sensors and connectivity features that collect data on vehicle performance, battery health, and driver behavior. Tesla monetizes this data by offering subscription-based access to premium features, such as Autopilot upgrades, advanced driver assistance systems, and infotainment services. Additionally, Tesla leverages this data to improve its products, develop new features, and inform future vehicle designs.
Caruso GmbH
Caruso GmbH is a data marketplace that facilitates the exchange of automotive data between various stakeholders in the automotive industry. By connecting data providers, such as automotive manufacturers and suppliers, with data consumers, such as repair shops, insurers, and fleet operators, Caruso monetizes automotive data through data licensing agreements and transaction fees. Caruso enables its partners to unlock the value of their data assets by providing access to a wide range of automotive data, including vehicle diagnostics, parts catalogs, and maintenance records.
Tech Mahindra Limited
Tech Mahindra Limited is a global IT services and consulting company that helps automotive companies monetize data through digital transformation initiatives and analytics solutions. Tech Mahindra leverages its expertise in data management, cloud computing, and artificial intelligence to help automotive clients unlock the value of their data assets. This includes developing customized data monetization strategies, implementing IoT solutions, and leveraging predictive analytics to optimize business operations and create new revenue streams.
These companies demonstrate diverse approaches to automotive data monetization, ranging from providing subscription-based services and connected vehicle features to developing data platforms and marketplaces.
Sources
https://www.linkedin.com/pulse/automotive-data-monetization-industry-promising-arek-skuza/
https://www.fka.de/images/publikationen/2017/data-as-product-SE17.pdf
https://www.mordorintelligence.com/industry-reports/automotive-data-monetization-market
