Unlocking New Revenue Streams Through Automotive Data and Equity Mining
Key Takeaways:
- Huge data volumes in today’s vehicles can be analyzed for new revenue opportunities
- Today’s world of multi-modal, software-driven transportation expands the potential
- Organizations can explore subscription packages, targeted offers and smart maintenance
- Effective technology behind the scenes is key for effective implementation
More and more industries are uncovering ways to generate data, and then create economic value from that data. And given that there could be as many as 900 million connected cars on the world’s roads by 2030, the automotive sector has a golden opportunity to tap into this rich revenue stream.
Every single one of these connected vehicles has the ability to produce as much as 25GB of data every single hour. And through strategies like data services, access sales, and targeted advertising, this data could potentially deliver hundreds of dollars of revenue and cost savings per vehicle per year.
In this blog, we’ll explore how automotive data monetization works in practice, including the vital role that vehicle equity mining has to play.
The Automotive Data Goldmine: Why It’s the Future of Revenue
Data mining is a long-standing practice in the automotive sector, leveraging vast amounts of information within CRM and DMS platforms and applying it to algorithms, so that insights, patterns and trends can be identified.
Vehicle equity mining, on the other hand, focuses those data mining efforts in the context of gaining financial insights specific to individual customers and vehicles.
This is especially useful in an age where more people are buying or leasing cars through finance. For example, a customer who is halfway through paying off a car loan - and therefore has built up positive equity - is a prime candidate to be upsold a trade-in offer, so they can upgrade to a new vehicle with a similar monthly payment. Vehicle equity mining can uncover who those customers are, how much revenue can be gained from them, and the best time to target them with new offers.
Automotive Data and the C.A.S.E. Revolution
The possibilities of automotive and data equity mining are even greater today, thanks to the ongoing ‘C.A.S.E.’ revolution within the sector. This refers to four new trends that are changing the face of vehicles and wider mobility around the world:
Where these four trends converge for the automotive industry is that they are shifting the value of development away from hardware and towards software. Indeed, the global automotive software/electronics market is predicted by McKinsey to reach $462 million by 2030.
Cars are no longer purely mechanical machines, and cases of mechanical unreliability are much less common than they used to be, meaning the value of investing in hardware is now relatively limited. Instead, automakers are focusing heavily on software, as good-quality solutions with in-depth features and unique user interfaces are major selling points in today’s marketplace.
The knock-on benefit of this is that software enables data to be generated and processed, which can therefore generate performance, maintenance and customer insight from where value can be derived.
Strategic Monetization Pathways for Automotive Data
There are several different ways to put all that theory into practice. Some relate to vehicles themselves, some to business processes, while others focus on the technological infrastructure behind the scenes. But all of them, either directly or indirectly, have the ability to generate meaningful value and revenue:
Connected Vehicle Services and Feature Monetization
Subscription models and premium features can generate revenue from customers on a regular basis. These include activating features like heated seats and entertainment packages; tiered connectivity to navigation, streaming, concierge and diagnostic services; and in-vehicle marketplaces where customers can make pay-as-you-go purchases.
Autonomous Vehicle Technology and Feature Upselling
Connected to the previous point, progressive autonomy packages can encourage customers to pay more for the most advanced capability. The same principle can be applied to safety and convenience features like automated parking and obstacle detection.
Electrification-Based Revenue Opportunities
Smart charging services can help customers optimize their charging strategy, whether they want to minimize cost, charge as quickly as possible, or maximize the use of renewable energy. Alongside this, subscriptions to battery health management services can help customers extend vehicle lifespan and maintain good battery performance.
%20Ecosystems.png?width=25&height=25&name=H3_%20Mobility%20as%20a%20Service%20(MaaS)%20Ecosystems.png)
Mobility as a Service (MaaS) Ecosystems
Non-vehicle owners can also be targeted through subscription packages that offer multi-model vehicle access across public transport and micro-mobility. These can also be subject to dynamic pricing models, where the cost of transportation varies according to level of service, time of day, distance involved and consumer demand.
Asset and Data Monetization Beyond Direct Services
Automakers can partner with insurance companies and retailers to sell usage-based policies that encourage better driver behavior in exchange for lower premiums. For the fleet market, subscription packages for vehicle performance analytics can help operators optimize maintenance and vehicle usage in detail.
Integrated Data Architecture: Breaking Down Silos
Unified data platforms can connect systems across vehicle operations, business processes and customer interactions that were previously siloed. Bringing them together can facilitate more holistic insights, and from those, greater opportunities for revenue.
Strategic Partnerships for Enhanced Capabilities
Scalable automotive data solutions that maintain security and compliance standards are ideal for enabling many of the opportunities above. This will require expertise in custom software development, big data analytics, AI implementation and rapid solution deployment.
Edge Computing and Real-Time Analytics
Moving processing power closer to data generation supports real-time data analysis thanks to reduced latency, also supporting time-sensitive applications such as predictive maintenance and autonomous driving.
In Summary: Overcoming Barriers to Automotive Data Monetization
Making all this happen successfully will require careful handling of system implementation, but also of data at a time when consumers are especially wary of how their data is collected and used.
Automakers will need to build consumer trust through transparency and control, with the added benefit that data privacy compliance (especially around AI solutions) will support adherence to key regulations like GDPR. This should be approached alongside a new perspective of technology, where AI and advanced technologies are integrated together, instead of being expensively and inefficiently retrofitted to existing solutions.
The best way to avoid those pitfalls and reap all the rewards of automotive data monetization is to work with an expert automotive technology and AI partner. At Ciklum, we help businesses like yours deploy AI, digital transformation and custom software solutions to thrive amid great change in the automotive sector. With our help, you can unlock the potential of data, automation, connected vehicles and digital ecosystems, and drive a healthier bottom line in a competitive marketplace.
You may also like
Subscribe to receive our exclusive newsletter with the latest news and trends
Subscribe to receive our exclusive newsletter with the latest news and trends
Want to reach out directly to us?
hello@ciklum.com
© Ciklum 2002-2023. All rights reserved