The automotive industry is facing a new technology adoption cycle. For Jessica Geutner, Chief Customer Officer at Salesforce in Central Europe, manufacturers’ success doesn’t solely depend on whether they use AI. Crucially, it depends on how well they integrate marketing, sales, dealerships, financial services, and after-sales – and how consistently they use customer data for personalized offers.
The way customers search for products in the automotive industry is changing rapidly: In the future, customers will no longer just ask manufacturer websites or dealers, but increasingly LLMs (Logistics Management Platforms) for the right vehicle. This shifts the focus for car manufacturers. They not only need to be discoverable in the new AI systems, but also integrate the customer journey initiated there into their own processes. Jessica Geutner sees this as an opportunity for those brands that bring data and systems together across previous boundaries. Those who continue to think of content, marketing, and sales as separate entities, on the other hand, risk falling behind in the new technology cycle.
Ms. Geutner, you have an overview of several industries. How would you assess these sectors regarding AI readiness? Which are particularly advanced? Which are lagging behind?
Jessica Geutner: I see retail and consumer goods leading the way in terms of AI readiness. Product and innovation cycles are short in these sectors. Companies need to quickly pick up on market signals and translate them into concrete applications. In my view, media and sports marketing follow. The automotive industry is catching up, but is moving more slowly due to longer product cycles and more complex sales structures. Generally speaking, where the B2C share is high and the customer journey is dynamic, the pressure to rapidly implement new technologies also increases. In more B2B-oriented sectors like manufacturing or healthcare and life sciences, communication is usually more specifically tailored to the target group – and technology adoption is correspondingly more traditional.
Jessica Geutner is Vice President of Strategic Customers at Salesforce and supports strategic customers in their digital transformation. She has in-depth expertise in the automotive industry in the EMEA region, with a focus on large dealer groups and OEMs.
This seems to contradict a recent study: According to this study, AI drives more traffic to websites in the B2B sector than in the B2C sector.
For me, this is not a contradiction. Especially in B2B, the website remains the central medium. There, I can check whether the LLM provided me with the right advice, find out more, and prepare for the next step. In B2B, this often involves a concrete offer or a conversation with a sales representative.
Especially in B2B, the website remains the central medium.
In B2C, the situation is different: If, for example, I ask a low-level marketing company (LLM) about the best or most energy-efficient kettle, I expect a direct recommendation and don’t need a pricing consultant. For more complex products like a car, however, a company’s own website remains relevant – but it must take the individual situation of potential customers into account much better than before.
Does this mean that the website is losing importance in the B2C sector?
It depends on the specific strategy. A look at the automotive industry illustrates this. Some manufacturers still have a very strong focus on branding. When they launch a new vehicle, their primary concern is how the car is presented and how the customer perceives it when visiting the website. In these cases, the website content tends to be static; the branding and awareness experience takes center stage.
Others pursue a more sales-oriented approach. These car manufacturers are more focused on high-volume sales and want to determine early on how to tailor interaction to their audience. They tend to follow a retail approach, which is why the website must respond dynamically to the needs of potential customers.
For example, someone who indicates that their lease is about to expire and they are aiming for a monthly payment of around 400 euros should be able to see suitable vehicles and configuration options directly. The goal is to make the next step as easy as possible – instead of leaving the person to simply present a generic brand image.
Do manufacturers with a more centralized distribution model have an advantage over brands that focus heavily on branding in their home market ?
Ideally, there should be no contradiction between OEM and dealer. What happens at the beginning of the journey on the website must lead to an opportunity, a test drive, and ultimately a conversion. The majority of the business still originates with the dealer and significantly less with the OEM. Brands should ensure that the content provided globally on their website and the communication with local dealers follow the same principles. Then it makes no difference to customers whether they arrive via the OEM website or a dealer’s. The only crucial factor is that both paths guide them effectively to the next step. I think this is something successful brands are working on: making global practices applicable to their dealers as well.
This challenge is not new. Why are some manufacturers more successful at implementing it than others?
I’m seeing a positive trend: everyone is improving. The automotive industry is in the midst of a technological adoption cycle. For a long time, transformation projects were primarily viewed as IT projects. This often slowed down implementation. We see with our customers that progress arises where business and IT work together toward a common goal and where employees and customers are involved in the change. That’s where technology can build bridges.
Salesforce helped the Volkswagen Group centralize its customer data. “The Volkswagen Group has already achieved significant improvements in service efficiency, as sales staff now have all relevant data in one place,” says Stefanie Paetow, Business Owner Salesforce ONE.CRM & Customer Care, Volkswagen Group.
The foundation for this is a data infrastructure that consolidates information from various business areas – from marketing, sales, and retail to financial services and after-sales – thus creating a holistic picture. Only when a networked customer profile emerges can AI truly unleash its potential. Now that it’s quickly measurable who is successful and who isn’t, more and more vehicle manufacturers are realizing that looking at things separately is holding them back.
This is also related to the fact that traditional roles no longer fit or need to change. If things remain with the classic ticketing system or with internal IT processing orders, it’s slow and cumbersome.
Absolutely. I believe that more and more decision-makers in the automotive industry are aware of what technology can do today. And this is leading to a real breakthrough and a completely different kind of collaboration when we work with manufacturers. But they are also realizing where they reach their limits.
What role will LLMs play in the future vehicle search?
Everyone agrees: Product searches will be AI-driven. Many are asking themselves, just like in the kettle example: Which car do I want? In the future, people will ask questions like: Which SUV suits me if I have €400 a month to spend? – and turn to systems like ChatGPT or Perplexity for help.
Everyone agrees: Product search will be AI-based.
77 percent of commerce managers expect LLMs to help with product searches in the future. However, what happens next is crucial. Currently, this information isn’t yet being used across marketing, sales, and service because system gaps still exist. Traditional channels like websites, dealer channels, and e-commerce portals are often not yet connected to these new AI-driven entry points into the customer journey.
Are younger companies, for example from China, currently having an easier time?
The current success of Chinese manufacturers is certainly also related to their pricing strategies and market entry. Price is always a quick way to generate attention and demand. However, whether this translates into long-term customer loyalty only becomes apparent over a complete vehicle lifecycle, when the next purchase is due.
I find another question more interesting when we look at established manufacturers in the German market. How do we prevent loyal customers from switching brands? For premium and luxury brands, repurchase rates are sometimes between 50 and 60 percent. Securing this loyalty becomes all the more important as product searches shift towards low-margin liquids.
Crucially, manufacturers need to understand when customers start thinking about a new vehicle. Which channels they use and when they need to present them with a relevant, personalized offer. Are they searching via a lifetime vehicle management system? Are they researching on the website? Or do they expect to receive a suitable offer at the right time in their Mercedes, BMW, or VW app? These kinds of questions will determine customer loyalty in the future.
Does this shift Salesforce’s focus in its collaboration with automotive manufacturers from acquiring new customers to churn prevention?
It’s both – and those two things aren’t mutually exclusive. We work with all the LLMs (Landesreal Estate Media) providers. When acquiring new customers, the question is: How does a potential customer find their way to my brand through an LLM search? And what information do BMW, Mercedes, or VW need to provide so that the brand is visible in these searches and the customer is actually linked to my brand? Are price comparison sites, test portals, YouTube experts, and bloggers reporting on the vehicle the key factors? What are the relevant input variables?
What are the relevant input variables?
However, what companies can control about existing customers is significantly easier. How can information about the entire customer lifecycle be used effectively? And how can churn prevention work from the dealership through headquarters and the national sales company to the financial services partner – in both directions and to the benefit of all involved?
Can AI-powered simulation partially replace the collection of deterministic data?
AI cannot simply replace data. We’ve all had experience with various LLMs: depending on how well you prompt, the results can be better or worse. Especially when it comes to customer retention, companies need reliable, consent-based information: What interests this customer? What kind of communication is desired? Which offers are actually relevant?
Especially when we’re talking about loyalty, two things are extremely important: Firstly, it’s crucial to respect consent. Companies shouldn’t just offer an opt-out option, but rather rely on a conscious opt-in. In my view, that’s a key to success.
Secondly, deterministic data – that is, reliable information from concrete customer interactions, e.g., from the CRM – ensures that offers for direct customers become more precise, relevant, and comprehensible. AI simulation does not replace this data foundation. This is because generative AI works with probabilities. While this is helpful, it can also lead to irrelevant results.
Salesforce is sometimes considered complicated software. Can AI, through platforms like Agentic, make it easier to harness the potential of this powerful machine?
AI makes everything easier, for everyone. That certainly applies to us as well. We have an extremely broad portfolio of solutions. For existing Salesforce customers, AI functions can be integrated directly into established business processes – much like a light switch that you turn on when needed. With our coworker features, users can access appropriate support directly within their respective business processes.
AI makes everything easier, for everyone.
In addition, there are the more customizable Agentforce solutions, which can be individually configured to meet the needs of employees and customers. These are suitable for companies that want to customize roles, permissions, and specific use cases. This requires a bit more IT supervision and expertise.
Agentic AI is a huge accelerator for anyone already using Salesforce, especially when a deterministic foundation—a solid data model—and clear responsibilities are already in place. In such cases, it can transform probabilistic AI elements into reliable, accurate implementation and acceleration of business processes.
Will marketers even find out how effective each advertising medium was? In direct marketing, it’s even more crucial to know which trigger worked.
AI helps to smooth out gaps and make processes seamless – thus guiding both customers and employees more effectively through their journey. Natural language forms the basis for this, and we always operate on the principle of “human in the loop”: Humans remain part of the control and decision-making process. AI is not intended to replace them, but rather to enhance their work.
He no longer has to sift through thousands of irrelevant pieces of information to find the right ones. AI can be a huge help, especially in knowledge management and in selecting the relevant information for each process step.
For example, it becomes easier to identify: Which campaign was effective? Which segment was particularly successful? When these insights are automatically fed back into the processes, it’s more of an improvement for employees than a deterioration, and above all, it contributes to cost optimization.
What do you see as the biggest risk for the automotive market – and where does the greatest potential lie for German manufacturers and dealers?
The biggest risk is leaving consent management as it is today: reactive instead of proactive. I believe that many people are ready to use AI extensively in their purchasing process. Those who are very risk-averse and only use AI selectively will, in my opinion, fall behind. This presents an opportunity for companies that use AI and consistently link their processes: from marketing to sales, from sales to dealers, across financial services and after-sales. Those who drive personalization and use AI to strengthen loyalty will be among the winners.
Finally, on a personal note: Where do you use AI in your daily work?
AI is everywhere, and I mean every kind. I’m using Vibecode, like I think everyone else is right now. Our Slackbot has become my very best friend. I can’t work without it anymore.
Our Slackbot has become my very best friend.
AI also accompanies me beyond my daily work routine. Both privately and professionally, I can hardly imagine working without it. I primarily use it as a sparring partner to test my hypotheses, structure my thoughts, and recognize whether I’ve overlooked a perspective or an important aspect.
