Scaling customer loyalty with Agentic AI and self-service

How do you build customer service that keeps pace with growth – without sacrificing quality? Eliot shows how AI, Agentic AI, and Self-Service accelerate service processes, take pressure off teams, and strengthen loyalty. In an interview with Matthias Bös (Portfolio Manager CX at valantic), Eliot COO Michaela Schmidke-Puchtinger explains which building blocks make scalable service possible, how use cases deliver impact immediately, and why AI does one thing above all: It helps service teams perform better.

Matthias: Michaela, you have significantly evolved customer service at Eliot over the past few years. Why has service become such a critical success factor for you?

Michaela: Because service determines loyalty today. Studies show that 75 percent of consumers switch brands after just one negative experience – whether it’s a delivery delay or unclear returns handling.

Poor service severely undermines trust, repeat purchase intent, and referral rates. Conversely, it’s one of the strongest drivers of long-term customer loyalty. That’s exactly why we at Eliot invest deliberately in customer service – not just as a “support function,” but as a core differentiator.

Matthias: Many companies hit their limits as they grow because they don’t factor service in early enough. Where were your biggest challenges?

Michaela: Clearly, scaling. As the business grows, ticket volume rises too – according to Zendesk CX Trends, by almost 38 percent since 2022. Simply hiring more people is neither efficient nor sustainable. So we had to find ways to handle more requests at the same level of quality without overloading our team. Our key learning: Scaling only works if you improve three areas at the same time: technology, processes, and people.

Matthias: Let’s go deeper: Which pillars support your service today?

Michaela: We talk about three pillars:

1. The right software – scalable, integrated, and AI-ready.
2. The right partner – a sparring partner who doesn’t just implement but thinks things through with us.
3. The right community – exchanging ideas with others to quickly adopt best practices and learnings.

And as the connecting element: our “Eli(b)ot.” It handles repetitive tasks, answers standard questions, and gives our team more space for complex cases where human empathy really matters.

Matthias: How exactly do you use AI in practice? Can you give a concrete example?

Michaela: A classic use case is order status. Customers ask, “Where is my package?”, and in the past, an agent had to look it up, gather the details, and reply. Today, a combination of Self-Service and Agent Assist handles it: The AI automatically asks for the order number, searches our system in real time, and returns the current status (“Shipped yesterday – arriving the day after tomorrow”). The agent receives a suggested reply and can use it as is or adjust it.

If the request is more complex, it can be handed over seamlessly to a human – with full context, so customers don’t have to explain everything twice. The result: much faster response times, less manual work, and consistently high service quality.

Matthias: How do you make sure the personal touch isn’t lost despite automation?

Michaela: We always give customers a choice: chatbot, self-service, or direct contact with real people. Especially for sensitive topics, that’s important. For us, AI isn’t a replacement – it’s an assistant system that makes our team better. It prioritizes, suggests responses, summarizes context, and ensures people can focus on what they do best: helping with empathy and strengthening relationships.

Matthias: What impact are you already seeing from AI, Agentic AI, and Self-Service?

Michaela: Several things. We have a significantly higher first-contact resolution rate because answers come faster and more precisely. The team works more efficiently and with less stress because routine questions are handled automatically. And we gain valuable insights: By analyzing user behavior in self-service, we can see where customers regularly get stuck – and address those issues proactively before a ticket is even created. All of this makes our service feel noticeably better, for customers and employees alike.

Matthias: What would you recommend to CX and service leaders who are just getting started?

Michaela: My advice: start small – start now. Begin with one or two clearly defined use cases, for example, “Where is my order?” or “How do returns work?” Measure before and after to see how resolution times and customer satisfaction change. Also: introduce Agentic AI first. That way, you can boost productivity immediately without triggering major change processes. And don’t forget content. AI is only as good as the knowledge base it runs on. Invest in clean, up-to-date help articles and FAQs.

Matthias: And finally: Where do you see customer service heading?

Michaela: Away from reactive support and towards proactive service. AI is getting better at anticipating problems – for example, when users repeatedly fail at a specific step. Then we can proactively show guidance or offer automated help. We’re also seeing industry-specific playbooks that help companies get started faster. The service of tomorrow will learn continuously – and improve with every interaction.

Make your service future-ready!

Customer service is no longer just a “support channel”. It is a key driver of loyalty, revenue, and brand affinity. But growth can only be managed with new approaches: Chatbots, Agentic AI, and Self-Service are not goals in themselves, but force multipliers for people and processes.

Want to find out how AI-driven customer service can make your company more efficient, scalable, and customer-friendly? valantic supports you from analyzing your top use cases and launching a fast agentic AI pilot to building a sustainable scaling strategy. Contact us and learn how you can use AI tools, Self-Service, and Agentic AI to take your service quality to the next level. Turn support into real customer loyalty and a modern customer experience!