Connected cars will create new business models and provide opportunities for current businesses to greatly improve their service offerings. Areas like targeted marketing, fleet management, event planning, city planning, insurance, and auto repair will benefit immensely from the data that connected cars will provide in the not too distant future.
A glimpse into the future
Let’s assume that 5 to 10 years from now a majority of vehicles on the road will be connected to the Internet. Information such as location, speed, fuel consumption, carbon output, mechanical wear and tear, music selection, distance from home, and various other data points are being captured. Let’s also assume that any mobile devices in use within the car is tied to the car’s unique identifier allowing us to predict the profile of people within the vehicle. Add to this data, location based information about everything that the cars pass including businesses, street signs, road conditions, weather, etc. and you have a gold mine of data just waiting to be utilized in ways never seen before. Let’s explore a few use cases.
Targeted Marketing
The ability to accurately predict consumer behavior is heavily dependent on the amount and quality of data that is available. Traditionally, marketers have mined loyalty cards, credit and debit card usage, and web log activity to predict the demographic makeup and buying patterns of shoppers. Most recently, some marketers have appended location based information gathered from mobile devices and apps to target consumers about messages relative to their physical location. Connected cars will take targeting to a whole new level.
Historically, the problem with targeted marketing has been that we have never had a real unique identifier because most consumers have many different credit cards, debit cards, loyalty cards, etc. Mobile devices have provided marketers with a better way to identify individual shoppers but it is far from perfect. But what if we could determine what the buying behavior and spending potential is based on a consumer’s driving patterns? What if we could tell if this was a trip to work, a typical trip to the grocery store or mall, a trip to an event, or a vacation? And what if we could tie purchase history of those types of events to the trip type? It is easy to send targeted messages to consumers but it is hard to send them when it is meaningful and relevant. Connected car data can help marketers influence buying decisions at the right time, to the right people, and in the context of the trip that the consumer is on. Traditional marketing companies are in for a rude awakening if they don’t get this because there are hungry startups working this angle right now and more will follow.
Consumers are already using apps like Waze to communicate traffic conditions, weather conditions, and the location of things like police. Connected cars could automatically crowd source various location based information as well. Imagine if a billboard company had access to information about the types of consumers that were passing by their advertising signs and could display relevant ads based on this data? Imagine if the information about the amount of traffic, average speed, and buying demographics of the consumers passing through a given area could be used to determine where to build the next billboard, grocery store, or gas station. Another interesting data source would be the traffic profile of people within a given geography. Potential homebuyers, builders, entrepreneurs or developers, can use the profile of people who frequent the desired area to put a value on the land or predict the market value of a potential business or event. The opportunities to leverage the profile are endless.
Improving service delivery with better data
Currently insurance companies create risk profiles in broad categories and place each person into one of those buckets. The rates are high because they account for the worst case scenario. What if they could predict risk at an individual level? Imagine if an insurance company could create an individual risk profile of a driver based on the risk of the traffic routes taken, total miles driven, time of day, actual speed versus speed limit, etc. That would allow them to drastically reduce the cost for most individuals because they can remove the estimated risk from the price. This could allow the insurance company to deliver a better service at a lower price and attract more consumers.
What if event planners could harvest demographic and travel information about their attendees. This would allow the planners to better target advertising dollars at the next event. It should allow them to set pricing tiers for sponsors and advertisers based on the makeup of the audience. For example, A NASCAR event has a stereotypical customer base. But what if NASCAR had more targeted information and found that the buying power and demographics of the fans attending the events has a much greater potential than the stereotype led them to believe. The location of the event can also play a major role. The makeup of consumers who are willing to travel to Daytona may look very different than a race in rural North Carolina. It would be more powerful to be able to quantify that with real data. I would imagine a majority of brands would pay a premium for a more granular view of consumers at a big event like the Daytona 500.
Imagine if your connected car was sending diagnostic information about the wear and tear on tires, breaks, and engine parts. The connected system detects that the front brakes need to be replaced in the next 5,000 miles. A request is sent out over the Internet to a network of service repair companies who compete for your business and send bids and offer to schedule the appointment based on an opening in your calendar. The service model can be turned upside down in the future, with the assistance of connected technologies. Much like how online insurance and mortgage bidding takes place on the web today, a variety of services will move to the bidding model driving down costs for the consumer.
City planners can benefit too
Data from connected cars isn’t just helpful for marketers. City planners can use the information for monitoring and rerouting traffic when necessary. The data can also be used to predict the impact of traffic patterns on road wear and tear, air quality, accident probability, crime rates, effectiveness of signs and traffic lights, emergency response planning and coverage, and much more.
City planners, law enforcement, and emergency units can also crowd source information about road conditions, construction zones and accidents so that travelers in connected cars can be alerted of dangers that lie ahead. Information like alternative routes, drive with caution and estimated time of delay can be relayed to drivers and hopefully reduce the impact of these conditions.
Long hard road ahead
I have barely scratched the surface of use cases that connected cars will create. It will take some time to see these use cases flourish because of privacy concerns. A recent study by McKinsey and Company states that 13% of car buyers would refuse to buy a new car without connectivity and that number will continue to rise. However, 37% said they would never buy a connected car due to security reasons. It will take a few years to be widely adopted, while at the same time many companies are not prepared or technically capable to architect systems that can process data of this size and scope. As the study mentioned, a connected car can process up to 25G of data an hour in the early stages of this technology. I expect that number to grow exponentially over the years.
Summary
While there are big barriers to overcome such as privacy concerns, technology maturity, and lack of technical skills to build these systems, connected cars will create new opportunities like never seen before. It is not a question of if, but rather a question of when this technology will be adopted. In a future article I will address the issue of technical skill and address how IoT will change IT forever. Stay tuned.
