Natural-Language-Understanding (NLU) Chatbots, i.e. those with an understanding of natural language, offer even broader possibilities for interaction. They can analyze the texts written by users and thus recognize their concerns, so-called entities (names, times, customer numbers, etc.) or even mood. This allows the chatbot to be more flexible in responding to users and also to design processes accordingly.
For example, if a user writes: "I am now looking for a train connection from Munich to Vienna", the chatbot deduces that the user wants to book a train with departure point Munich, arrival point Vienna and the whole thing at the current time. Now the chatbot checks which information is still missing to complete the booking (e.g. the booking class) and asks for it afterwards. This procedure is also called "slot filling". A simple scriptbot, on the other hand, asks for each piece of information individually and one after the other - regardless of whether it was already mentioned in the user's initial message.
In addition, the mood of the customer can be detected dynamically. This offers the opportunity to treat each customer differently and increase their satisfaction. An upset customer is specifically passed on to a human call center agent, while the chatbot attends to the relaxed prospect looking for offers. This allows the company's resources to be deployed in a more targeted manner, reducing the churn rate and increasing customer satisfaction.