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If you belong to the automotive industry and are hustling to bring improvements to your business, then we’ve got some news for you.
The news is that with lots of research, A/B testing, and learning, we’ve come to the conclusion that data science applications are insanely beneficial for the automotive industry..
And in this article, we’re going to uncover all the whys and whats related to how data science has benefited the automotive industry. So, let’s dive right in.
Data-driven decision-making can transform the way you run your automotive business, making it more recognizable and profitable.
By collecting data from new and existing customers, you can learn more about their demands, requirements, and issues to bring improvements and innovations.
In short, data-backed decisions for automotive (or any industry for that matter) enables businesses to improve product development, increase workflow efficiency, enhance customer experience, and offer a competitive advantage.
Too many reasons to invest in data science, no?
You’ll be surprised to learn how beneficial data science has been in improving subscription models and rentals. Let’s discuss this one by one:
Any product or application becomes worth investing in even more when you learn about the success rate of using it. Having said that, using data science applications for subscription models and rentals has been a total hit.
A subscription model refers to a business model where companies offer customers the ability to drive their vehicles in return for a fee. This fee can be paid monthly, bi-monthly, weekly, or however the company decides the arrangement.
Renowned examples of subscription models for cars are Kyte, Hertz My Car, and Sixt+.
Subscription-based car services have offered many benefits to both consumers and businesses. Let’s discuss them one by one;
We know that subscription models have done a great job of offering ease and convenience through subscription-based vehicles. What most people or businesses, for that matter, don’t realize is that service can be improved and personalized even more with the help of data science.
As a whole, data science have enabled automotive businesses to collect customer data and understand their preferences, providing them with the necessary information to work on customers’ needs and demands.
In addition to this, data science also help automakers to provide software updates that update features even after purchase.
Rental services are simply companies that rent out cars or other vehicles for a certain period of time. Usually monthly, weekly, or yearly basis.
Some of the most renowned rental services across the globe are National Car Rental, Alamo Rent a Car, and Thrifty.
Rental services are a sigh of relief for many people as they offer advantages like:
Just like any other business, data science has a positive impact the rental services too.
Car rental services can use AI-based models to predict results through the data collected from clients and customers. This can further help them predict their pricing and optimize their inventory.
In addition to this, car rental analytics enables businesses to understand rates and prices and make better decisions.
Plus, car (or vehicle) rental APIs can help integrate rental functionality into travel services, making it easier for people to book cars and for businesses to manage their inventory.
One of our personal favorite reasons is that online rental software can help companies to answer customer questions quickly and easily. This helps them manage their reservations and make changes as needed, leading to increased customer service and satisfaction.
Needless to say, whatever helps a business come closer to its customers is a hit.
It’s actually hard to understand and believe in the advantages that data science has brought to the automotive industry unless you have seen real-life examples, no? Well, in that case, you must learn that Drivemate and Turo have made remarkable contributions with the help of data science.
Drivemate (a secure software that offers car sharing service by allowing people to borrow a car from the neighborhood) and Turo (a peer-to-peer car rental service) have made profound improvements by enabling the respective businesses to:
Since we’re discussing use cases, one of the best applications or solutions offered by data science in the automotive industry is the introduction of dynamic pricing.
Let’s dig deep into what it is and why you must opt for it.
What if we tell you that now you can make real-time tweaks and alterations to the pricing of your automotive industry and bag more revenue according to the market situation?
Sounds like a dream come true? Well, it has, actually.
Thanks to data science and its applications, all that we once only wished for is actually applicable now. To understand how this works, let’s discuss what dynamic pricing is and what its advantages are.
Dynamic pricing is a strategy where a company or business adjusts the prices of a product or service based on its demand in the market or factors like the availability of resources.
As a business, you’re bound to make decisions based on the advantages it brings. And using dynamic pricing for your automotive business can:
If you’re still skeptical about the advantages of dynamic pricing then you must know that in a research conducted in 2021, Statista revealed that 17% of e-commerce companies have opted for dynamic pricing.
Like we said earlier, it’s hard to believe in the advantages unless one sees them for himself/herself. Having said that market’s finest automotive companies like:
Uber uses a dynamic pricing algorithm that adjust the prices of the rides according to factors like time, distance, route size, etc. And Lyft uses dynamic pricing, to adjust the prices based on the demand for rides and factors considered by Uber.
In addition to the above-mentioned factors, companies also consider triggers like real-time market conditions, political situations, or service availability.
Data science has transformed the way industries and businesses work, and so is the case for the automotive industry. And like other factors, data science have drastically influenced the financial situation
For example, machine learning and artificial intelligence are being used in the automotive industry loans, automakers are using data science for product developments and automotive lifecycles, and lastly, predictive analysis is used for OEMs and dealerships.
If you’re wondering what credit score is and how data science have played a role in changing it, then stick around because we’re about to discuss it all.
Credit score refers to the process of evaluating the creditworthiness of an individual based on their credit history, financial behavior, etc.
The reason why data-driven credit scoring has caught the attention of many businesses is that:
Testimonials and real-life examples influence decision-making processes like insane. We know that for a fact. And when these examples come from the world's best known automotive companies like BMW and Mercedes, the impact has to be doubled.
Speaking of which,
It is using data science applications to improvise its automobile production and boost its business. To specify, it uses virtualization and artificial intelligence to network all aspects of production.
It’s also using data analytics and machine learning to ensure rapid networking, knowledge, and technology. Plus, it’s also leveraging machine learning to predict how traffic regulations can reduce both traffic and gas emissions.
One the other hand . . .
It is relying more on data science with every passing day by leveraging it for autonomous driving, increased adoption of electric vehicles, and more. Moreover, it uses sensors that collect data from race cars, enabling them to learn more about the most efficient race cars and conditions.
Last but not least, data science enable Mercedes to collect real-time data from traffic.
To sum up, both BMW and Mercedes-Benz use data science and AI to boost their automobile production, infotainment systems, and overall business. They are using machine learning models, data analytics, and sensors to collect and analyze data to improve efficiency, sustainability, and user experience.
It’s a given that data science has contributed a great deal to the automotive industry. So if you’re contemplating about the possible use cases of it then read below;
Got an overview of why data science for the automotive industry is totally worth investing for?
Then opt for your business and see for yourself how it can help in product development and optimization of processes.
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