The automotive industry faces many impactful issues, most notably:

• Increased competition;
• Need for sustainable mobility;
• Digital Transformation;
• Power of manufacturers;
• New distribution policies;
• Data management regulations.

The magnitude of these issues is undoubtedly significant and greatly affects the processes, strategic and operational choices of every professional involved.

These issues can only be addressed by defining specific objectives:

• Maintaining competitiveness;
• Understand customer needs;
• Make data-driven decisions;
• Maintaining control of their own information;
• Maintain contact with the customer;
• Maximize opportunities for immediate conversion.

All of these goals can be achieved with a series of activities that have one common denominator: systematic data collection.

By collecting data and using it proactively, the following expected results can be achieved:

• Maintained competitiveness;
• Customized solutions;
• Sound decisions;
• Control maintained;
• Continuous customer contact;
• Increased conversions.

Big Data presents a huge new opportunity for both automakers and all distribution and service operators.

The main purpose is to be able to be responsive to specific customer needs in order to increase the perceived value of both the product and service and the company that offers it directly or indirectly.

The collection of such data takes place primarily through sales and marketing activities but, thanks to technology, can take place, with great increase in quality and quantity, directly from vehicles thanks to the connection potential of the vehicles themselves or drivers’ smartphones.

The ability to systematically collect data produced by the vehicles themselves with minimal collaborative interaction from the driver is undoubtedly the first step toward Big Data.

An auto manufacturer or distribution network operator can benefit in real time from telemetry information comparable to what we are used to considering in Formula One.

Without bothering motorsport, we know that access to information regarding the vehicle is not a novelty since, for years, there have been workshop diagnostic tools that, connected to the ECU, allow the retrieval of “historical” information.

What is changing is the continuous systematicity of detection thanks to the intelligent use of sensors and connectivity solutions integrated during production but also other Internet-connected devices such as, for example, the driver’s smartphone.

Cars with direct (autonomously) or indirect (via the driver’s smartphone) connectivity capabilities can provide a regular stream of data involving the vehicle, engine, fuel consumption, driving style, emissions, and environmental conditions.

The ability to capture such massive amounts of data of various types, generated in real time combined with machine learning and artificial intelligence systems represent assets that can revolutionize the customer relationship and the level of understanding of overall mobility needs.

A great additional inherent benefit is the ability to offer timely repair services and part promotions, improving product sales and after-sales services of the service network.

In fact, in addition to collecting statistical and utilization information, it is possible to provide personalized assistance services to motorists by generating alerts or providing guidance on how to minimize fuel consumption.

In addition, such a system can facilitate collaboration with other companies: the provision of integrated data could be particularly attractive to insurance companies and roadside assistance operators.

With the availability of Big Data from each individual vehicle, it is possible to implement preventive maintenance schedules based on the actual use of the car rather than on deadlines, predefined intervals, or presumptions of the need to service or replace parts. 

In the traditional approach, a part might be scheduled for replacement after a certain time interval regardless of how the car is used; in contrast, a condition-based maintenance program focuses on the condition of the equipment and its operation, rather than on a predefined time interval or schedule.

The collection of historical data, the implementation of machine learning and artificial intelligence solutions combined with the ability to detect certain vehicle usage metrics in real time enable timely and more relevant action.

Thus, by integrating Big Data into a CRM solution, it is possible to predict customer behavior, intervene in a timely manner, avoid “false alarms,” improve customer service, and more accurately manage investments up to and including fully automating discussions between prospects and advisors.

The SmartCar solution is the ultimate expression of systematic data collection in the automotive industry and in its reading and interpretation.