Data-driven analytics have seeped into the fabric of countless businesses worldwide, accelerating operational efficiencies and strategic decision-making.
What makes the ongoing data revolution so powerful is that these insights are greater than the sum of their parts—one industry’s data can easily spark innovations in another, germinating new ideas in unexpected ways.
For example, data accumulated by fitness companies offer crucial insights on public health trends and behaviors that are valuable to healthcare and insurance organizations. The automotive industry is no different.
Modern vehicles are equipped with a slew of sensors and cameras, among many other technologies, that generate huge amounts of data, on and off the road. This data has proven instrumental in transforming the automotive and mobility landscape.
But the impact of automotive big data extends much farther than the industry itself, fueling substantial growth and advances in several other sectors.
Ensure better insurance
The insurance industry is often characterized by long-standing legacy practices, still in need of a technological infusion. Although AI has begun paving the way for faster and more efficient claims processes, there is still an untapped opportunity to create better policies.
This is where big data takes the wheel.
By tapping into on-the-road data insights garnered from real-time sensors in vehicles and infrastructure, car insurance providers can craft highly personalized policies that truly reflect the risk for each individual driver—rather than simply relying on general factors like age, gender, and duration of vehicle ownership.
For instance, drivers who consistently adhere to speed limits and other safe driving practices can be assigned lower premiums, not only saving customers money but also providing an incentive to maintain safe driving habits, reducing the number of claims made.
In addition to boosting customer satisfaction with fair and reflective pricing, big data from the automotive industry can yield a reduction in accidents—a win-win-win for policyholders, insurers, and public safety at large.
Reassess real estate
Real estate is yet another beneficiary of automotive big data, which can help inform property purchasing decisions.
When choosing a location for a new development project, developers can leverage data from smart mobility infrastructure to assess traffic patterns, commute times, or the availability of public transport to find the ideal places for new properties that would appeal to prospective customers. Consider that sales value for residential housing can increase as much as 24% when located in close proximity to public transportation stops.
Data on local driving behaviors, such as the average number of cars regularly driven in an area, can be especially insightful when planning and designing cities. Building parking and driving infrastructure that keenly reflects the true number of cars in a certain area or optimizing traffic flow within residential areas to minimize noise and pollution are effective ways to enhance property value and appeal. For commercial properties like office spaces, developers can use similar data to find optimal building locations that minimize employees’ travel times, upping productivity, cutting congestion, and reducing pollution.
Enhance retail and e-tail
The e-commerce industry relies heavily on logistics and delivery operations. As such, their success is largely dependent on their fleets’ ability to deliver items as efficiently as possible.
Data insights gathered from the automotive industry are critical to maximizing that efficiency.
Access to real-time traffic data allows companies to optimize delivery routes, expedite ETAs, and reroute deliveries in the case of unforeseen delays. In fact, it’s shown that companies using route optimization solutions cut delivery times by 15%, reduce fuel spending by 20%, and slash carbon footprints by 18%, all while increasing the number of deliveries by 25%.
These insights can greatly benefit delivery companies by reducing operational costs such as fuel and vehicle wear and tear—savings that are ultimately passed on to the consumer. By planning the most efficient routes and reducing time on the road, companies can also minimize the stress on engines, brakes, tires, and delivery drivers.
Delivery fleets can also use data on usage patterns, driver performance, road conditions, and more to predict when delivery vehicles need maintenance. By scheduling maintenance proactively, companies can prevent breakdowns and costly delays and improve the lifespan and cost efficiency of their vehicles.
And it’s not just e-commerce deliveries—automotive data can enhance brick-and-mortar retail experiences as well. When choosing store locations, retailers can harness insights into traffic patterns or popular routes to help find optimal locations, ensuring stores are conveniently placed for customers.
Similar to how digital marketers utilize user data to best place online ads, they can do the same with their physical marketing campaigns. By analyzing vehicle movement data, retailers can determine areas their particular customers frequent, allowing them to place effective, targeted outdoor advertising campaigns or strategically placed billboards along popular routes.
Smarter cities
Automotive data is also key for enabling the creation of smart cities and bolstering smart urban mobility.
A city that is able to harness data on transportation patterns can adjust traffic lights dynamically to help alleviate congestion, especially during peak hours. As cars register poor road conditions such as dangerous potholes in a specific corridor of a city, that data could inform the municipality about what sections of road need repaving. Real-time data on road conditions and weather trends can also be used to prioritize maintenance and repairs for drivers themselves, ensuring safer and smoother journeys.
Integrating automotive data with other urban data sources can also enhance public transportation, making it more efficient and reliable. By optimizing routes and schedules based on real-time traffic patterns and commuter needs, cities can reduce wait times and improve coordination between different transit modes. Better, more user-friendly public transit leads to fewer personal vehicles on the road, decreasing congestion and lowering overall fuel consumption and emissions, ultimately leading to a more sustainable urban environment and reducing the city’s carbon footprint.
Reducing congestion is about more than just saving drivers time and stress on the morning commute. Studies have found that cities using intelligent transport systems (ITS) that integrate data like traffic patterns and commuter needs experience a 66% improvement in travel times and efficiency, a 22% reduction in accident rates, and an 11% decrease in fuel consumption.
Drive data forward
Today’s vehicles are already generating a treasure trove of data.
As such, data-driven insights from the automotive industry can completely transform industries far beyond the automotive and mobility sectors. With the ability to harness this information, organizations of countless kinds will unlock new levels of efficiency, personalization, and innovation.
By leveraging data-driven insights, numerous industries can pave the way for smarter, safer, and more sustainable growth, leading toward a future where data truly drives progress.
Yaron Sahgiv is chief marketing officer of UVeye.
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