From Dealership to Concierge – Leveraging Vehicle Data to Transform the Car Buying Experience

Analyzing vehicle data should be transforming customer experience in the auto industry. Unfortunately, it is behind many others in terms of delivering individualized experiences based on insight.

Monica McDonnell
Monica McDonnell
2. November 2022 4 min Lesezeit
Leveraging Vehicle Data to Transform the Car Buying Experience

Just like any other digital device, the vehicle you drive can tell a lot about you. Not just the make or model, but your driving style and feature and function preferences. Analysing vehicle data should be transforming customer experience in the automotive industry, and an increasing focus on aftermarket revenue from features, performance or services is driving a personalisation imperative. Every step on the customer journey, from initial enquiry through purchase, to day-to-day use of the vehicle presents opportunities to understand customer preferences and take actions to enhance customer experience with the brand. 

Unfortunately, the automotive industry is behind many others in terms of delivering individualised personal experiences based on insight. But by tapping into the knowledge and experience of other sectors, automotive businesses can rapidly enhance their customers’ purchase journeys. For example, Teradata customers in banking, retail and telecommunications industries are excellent at anticipating customer needs and responding rapidly. They do this by collecting data from every customer interaction to accurately predict individual needs and preferences. 

By identifying triggers and creating highly personalised offers these firms are already delighting customers, delivering experiences that reflect preferences they did not even voice.  In the next few blogs, I’ll look at how automotive companies can, and in some cases, are already using these approaches to transform their customer experience.

Multi-year vehicle ownership periods suggest that less than one per cent of a customer’s total interaction with the brand during an ownership cycle occurs in the showroom or on brand websites. Yet this is the ‘must win’ space if new and existing customers are to be encouraged to purchase your vehicles. Imagine if you could help steer individuals towards their ideal car even if they are unable to fully articulate their preferences. What about having insights that identify the specific features that would interest and encourage an individual to trade-up to a new model? Leveraging data from across the customers’ lifecycle can inform deep insights that transform the showroom experience and maximise chances of putting individual customers into the best vehicle for their budget. 

Roughly ninety per cent of the experience of a modern passenger car is captured by the car itself. Everything from driving styles to use of features, type and frequency of journey to climatic conditions are all captured and stored by the large number of sensors present in the vehicle. For years this data has been collected and curated in after sales departments, normally for specific purposes like warranty analytics. Yet it is gold dust to anyone seeking to understand the humans driving the vehicles. With the appropriate consent, this data can help uncover the preferences individuals fail to articulate for themselves. Ensuring that this data is available and useable by marketing and sales teams is critical to show that brands really do understand their customers. It’s not rocket science; retailers have been doing it for years. 

Teradata is well known in the retail industry for enabling customer analytics at scale leveraging every interaction individual shoppers have with the retailer – both online and in the store. Analogous to vehicle data, this information illustrates in detail precisely how individuals interact with the brand. For example, a US retail pharmacy can clearly see, for each customer, what they buy, where, when and how frequently individual items show up in baskets. In addition, it knows what time, and through which channels they prefer to shop and when are they most receptive to marketing messages. Using this data, this retailer creates predictive models that identify trigger events which initiate tailored marketing outreach at the perfect time in exactly the right channel. In a helpful and non-intrusive way, the brand acts as a concierge, pointing out offers and products that fit perfectly with the individual’s preferences. 

Analysing vehicle data can do the same. Using data gathered from vehicles during service appointments, Teradata has already helped build analytics models for one European car manufacturer to help predict potential new vehicle sales and probability of customer churn. The models prompt customer outreach which has a measurable uplift on new vehicle sales in the markets they were deployed.

Taking this example further, OEMs and their dealer networks can transform their roles to become ‘concierges’ of the customer experience. Web shoppers can have attractive vehicles suggested to them and get automated, but personalised help navigating through extensive, potentially confusing, configurators to the options they would most enjoy. Rather than providing vanilla test drives, dealers can leverage this understanding, as well as further cues from web interactions for example, to set up vehicles with specific features and functions that will please prospective customers. Highlighting and demonstrating options that relate to observed behaviours from vehicle data, even if not requested, can significantly enhance the overall experience and thus improve the chances of a sale. 

Retailers, banks and telcos have far more frequent interactions with their customers than automotive brands, after all most of us do not buy cars every week. That’s why leveraging vehicle data, which does provide frequent behavioural insights, is so important. But the tempo of automotive sales is changing. As more and more functions, performance parameters and options on vehicle are ‘software-defined’, they can be added, upgraded and turned on and off as needed. Automotive brands now have the opportunity, indeed the imperative, to engage constantly with their customers to find new ways to enhance customer experience throughout the lifecycle of a specific vehicle. 

The software-defined vehicle is already starting to transform the way cars are sold and I’ll turn to the implications for data analytics of this shift in the next blog.

In the meantime, if you’d like to hear more about how Teradata can help transform your vehicle sales experience into a high-quality concierge service, please get in touch


Über Monica McDonnell

Monica McDonnell is a highly experienced consultant in the field of enterprise software, digital transformation and analytics. Her career has spanned Africa, the US and Europe with time spent on ERP and supply chain planning before focusing on delivering value from data. Monica advises on how to deliver business value by combining good data governance and advanced analytics technologies. Helping automotive companies understand how to release the full potential of Industry 4.0 technologies, and dramatically improve customer experience management as enabled by the connected vehicle is central to her role. Monica earned a BSc in Industrial Engineering from the University of Witwatersrand, and a MSc in Software Engineering from Oxford University. 

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