In recent years, data monetization has become a hot topic. Data monetization has become a major value driver as companies become more data-driven.
Data monetization can be broadly divided into two categories. It involves creating new revenue streams from data or insights by making that data available to customers and partners. This is often referred to as ‘external’. And it also includes indirect (optimizing business performance using data-driven insights, improved, data-enriched service, or more generally ‘internal.
Rise and fall for the new savior
However, the field of automakers has evolved in a different way than initially expected. As soon as connected cars were on the road, automakers were the first to attempt to monetize vehicle data. Since then, they have been collecting the ever-growing data sets from individual drivers and their vehicle fleets.
The expectations from the auto industry were high. New revenue streams promised to be created, but they never materialized. The returns and sometimes third-party demand was not what was expected. While some consumers and regions showed initial interest, their efforts to leverage that data have stalled over time. (Limited technical capabilities, limited real-time data need, limited impact, etc.). The model didn’t generate the expected additional revenue. The carmakers’ initial optimism waned.
After a disappointing start, many OEMs are now reconsidering their external data monetization strategies. Some OEMs are stopping data exchange with third parties entirely. They want to harness the data’s value. They are now turning their attention inward to fully utilize the connected vehicle data potential for their new business models such as usage-based, fleet management, and other digital services.
The fact automakers, even more, accelerate this strategic shift will need to move beyond their current business model of moving metal and become holistic providers of mobility and digital services to be differentiated in the future. They will need to take a holistic transformation approach, as they will have to be more focused on data and software than today. With all the new capabilities, agile processes and data operations, they can ensure quality and governance and enable data and analytics democratization throughout the enterprise.
The business potential
What are these new business models? Many OEMs have been considering offering car insurance. This would allow them to create a single-stop shop that covers all aspects of vehicle ownership, including financing and insurance. They now have the data to provide seamless customer service for certain aspects of car insurance. You could offer “pay-as-you-drive” insurance that uses specific driving patterns to determine risk and optimize accident detection and management. This leverages their access to real-time alerts. This could be done in a direct or indirect data monetization model, where the OEM works with backend providers to share costs and revenues. Research shows that usage-based insurance is the most promising, expected to grow from US$31bn worldwide to US$175bn in 2030 (21 percent CAGR).
Fleet management is another high-value area. This involves complex and labor-intensive processes that involve vehicle provision, continuous uptime maintenance, service optimization, customer management, and fit-to-purpose vehicle provision. The OEMs’ initial goals of achieving cost savings and new revenue generation can be realized when vehicles can automatically locate and predict servicing needs. B2B customers can license these digital services without having to manage them. This category is sure to be attractive, with an expected increase of US$18bn to the US $80bn by 2030 worldwide and a CAGR of 18%.
Other interesting growth categories for revenue through connected car services are infotainment, mobility-as-a-service, and in-vehicle payments, and since costs for data capturing, transformation and usage will decline over time, there is a lot of potential to continue deriving additional value from it over the lifetime of each customer and each vehicle. Success is dependent on the customer’s lifetime value.
Tracking data value
How can you connect value and expected investment return to individual data assets? The first step in establishing a clear digital strategy for services is to define key categories (usage-based insurance and fleet management, as well as mobility services). Key regions may be required depending on market preferences, regulations, coverage, etc. ).
It is possible to attribute revenue and assets to data assets by aligning the business strategy with the data strategy. This can be done by analyzing data resources (and other resources) required to deliver priority services. Data access tools, data catalogs. Consider investments in infrastructure, data capturing and storage, processing, and people to manage the systems. These capabilities include data wrangling, analysis, and marketing and promotion. This is similar to connecting revenue and margins to individual customers through the products or services they purchase.
This data strategy helps to enable and inform critical business decisions. It identifies the data with the highest value and provides information for future investment in data.
Guidelines for data monetization success
It doesn’t matter what use case data monetization is used for, i.e., the digital service it powers. It’s important to treat sensitive data carefully and not follow big tech companies’ invasive data collection behavior after years of unregulated user data collection and extraction, the latter face regulatory backlash. A strategy for data monetization should clearly emphasize the added value to customers and the creation and maintenance of trust, particularly as consumers become more mature and aware of their data privacy. These three keystones are essential to achieve this:
Transparency is key to trust-building.
ValueAutomakers should offer customers real value through better customer service, safety, convenience, and cost savings. Customers must know what they are getting to encourage the adoption of connected cars or other data services. The value of data sharing must be greater than the risks and costs.
Control: Customers must have control over the data collected and when it is collected. They also need to be able to share it with others for customers to enjoy a seamless customer experience. This helps to prevent data misuse and builds trust. Toyota recently added the Data Privacy portal to its mobile app. It allows customers to track what data is used by third-party companies, how it is used, and what it adds to the company’s bottom line. They can also learn how to turn off data processing.
Automakers should make it their top priority to earn customer trust and show that they treat customers’ data ethically. This is how they will ensure their long-term success and realize the full potential of data marketing.