Introduction to data driven customer experience (CX) within automotive sales and service

The current OEM, dealer and customer ecosystem is characterized by fragmented and siloed processes, applications, and business drivers. Over a series of blogs, we will discuss how these business challenges can be met by putting the customer at the center.

In today’s rapidly evolving automotive industry, automotive businesses face several challenges when it comes to creating data-driven relevant experiences for their customers:

• End-to-end journeys – Transition to online sales and the need for the OEM to take over the end-to-end sales experience.
• EV evolution – Transition to EVs and the additional complexity of the customer journey, combined with intense competition from new entrants to the industry, such as new Chinese brands.
• New channels of engagement – Rise of alternative engagement technologies such as the Metaverse, meaning again a more complex multi-channel buying experience.
• Sustainability – Movement towards sustainability in the industry, again driving the need for better data to understand products, supply chains, customer behaviors, etc.
• Profitability – Squeeze on profitability due to turbulent macro-economic situation, meaning more focus on aftersales as a profit engine.

As well as more data specific challenges:

• Data silos: Multiple disconnected data sources make it challenging to get a holistic view of the customer, impacting service quality and retention.
• Data quality: Incomplete, inconsistent, or inaccurate data hampers the creation of accurate and relevant experiences.
• Generative AI: Uncertainty exists regarding the operational and customer value of generative AI.

Data Driven Customer Experience (DDCX) is a framework that helps businesses use data and analytics to understand more about the trends and behaviors in the market, and help businesses understand more about their customers so they can meet these rising customer expectations.

To overcome these challenges, automotive businesses need to prioritize data strategy and data management, and invest in the right people, processes, and technology. DDCX is a powerful tool that can help automotive businesses improve customer engagement and lifetime value.

Our approach to DDCX

At Capgemini, our Data Driven Customer Experience (DDCX) offering defines the tools and techniques that businesses can use to learn more about the data they are collecting, identify gaps and bring multiple data sources together. By analyzing insights across customers, products, and services, they can activate enhanced marketing, commerce, and customer service strategies.

The DDCX framework organises the following inputs:

• Top-down business strategy – For example, defining a holistic journey across sales and service within the context of new EV experiences and evolving business models.
• Data strategy and collection – Assessing the data available in the business and industry and ensuring the right data is brought together from disparate source systems via faster more real-time connectors to enable relevant experiences.
  • Zero party data – Customers are willing to share more about who they are via self-declared forms, my account, and surveys. E.g., I am interested in looking at a new car, these are my criteria.
  • First-party data:
    • Behavioural and transactional data – Customers are using various digital properties and channels to engage with brands, including self-serve portals, e-commerce websites for browsing and configuring vehicles, calling customer service, using chatbots, and browsing branded content online and mobile apps.
    • Connected car data – Connected car data is transforming the automotive sector. This data caninclude vehicle performance, diagnostics, location, driver behaviour and usage patterns.
  • Second-party data – Businesses are looking to partner with online aggregators such as Auto Trader and CarWow to fill the gap in terms of customer profiles buying their brand and what’s selling well in the marketplace. Creating EV segments for example.
  • Third-party data – Automotive companies can enhance their existing data services by either buying information from providers
• Single customer view – Create a single view of your customer, stitch profiles together across unknown and known and apply a layer of analytics to define who that customer is and what the next best thing to recommend/sell/support them is and should be.
• Omni-channel strategy – Ensure that the recommendation made is enabled across an end-to-end designed and orchestrated experience.
• Data driven activation – Use data to automate and personalize recommendations, plus the next best actions for the customer through a unified and orchestrated UX.
• Measurement and optimization – Ensure that every experience delivered to the customer is measured and tracked so the business can learn and evolve.

Summary

The DDCX framework is designed to enable new data-driven experiences across the industry, unleashing the power of multiple data points to provide a holistic, synchronized, and optimized journey. This is built on the back of a strong data management strategy encompassing technology, people and processes. In our next blog post, we will demonstrate through example automotive use cases how using Capgemini’s DDCX framework in combination with our Salesforce partner technology stack can help your business create better customer experiences and a foundation for innovation.