What does ideal customer service look like in the digital age? Do most customers still value personal contact? No. This is the conclusion reached by various studies, such as Capgemini's “IT Trends 2019 – Intelligent Technologies”. As a result, customer demand for fast, uncomplicated digital service is growing across industry boundaries.
In view of this situation, much evidence suggests to automate customer service with chatbots. A chatbot is a dialogue system with natural language capabilities being issued either as text or audio. With Natural Language Processing (NLP), the chatbot can process written text, spoken language, and visual communication without having previously defined specific programming commands. The basis for this technology is artificial intelligence.
The advantages of chatbots are obvious: they ensure 24/7 availability. Waiting times are a thing of the past, the customer receives immediate feedback on his request and ideally a direct solution to his problem. The unpleasant situation that the customer has to contact several people before he gets the help he wants is also a thing of the past. The requirements and tasks the chatbot takes on are 100% scalable.
By answering standard queries, a bot relieves the service staff, who can now deal more extensively with the more complicated and thus more complex queries. As employees spend more time with these customers, the overall quality of service increases, resulting in greater customer satisfaction. This creates a win-win situation for the service area and for the customer.
In addition to customer service, chatbots are also suitable as an interactive version of FAQs (Frequently Asked Questions). They independently search for solutions, give the customer an answer directly or refer to the detailed FAQs in text form for further information. The use of chatbots is particularly worthwhile if they are connected to the CRM system. This enables them to extract the relevant information from the system based on the customer number and take it into account when making suggestions for solving the problem.
Chatbots – in combination with the CRM system – open up the possibility of personalized and interactive marketing, increasing the efficiency of marketing measures and exploiting cross-selling potential. They also act as digital assistants or virtual helpers, for example by giving step-by-step instructions on how to use a product.
AI systems differ from traditional computer systems because they are able to absorb information, store it as knowledge and apply it flexibly and in accordance with the situation. Thanks to artificial intelligence, chatbots are able to deal independently with customers' questions and problems. Based on the information received, chatbots make rule-based decisions.
The AI system learns continuously. With increasing experience and an ever more comprehensive data basis, the speed with which the chatbot delivers suitable answers also increases. In addition, through extensive learning the chatbot even registers differences in the formulations and recognizes if the customer addresses him in a friendly or an angry tone.
From a technical point of view, the training of the bots, i.e. the creation of as large a data basis as possible, is decisive for their skills. First, the intentions and goals to be achieved with the chatbot are defined. Then it is necessary to store skills so that the bot can perform the desired action in response to a request.
As already mentioned, connecting the chatbot to the company’s CRM system also improves the service process, because the available data is used directly for the solution of the problem and enables personalized interaction. The chatbot has access to relevant information such as the available service staff, the customer’s order and service history and their profile. This allows services to be seamlessly controlled and tracked. The opening of a ticket is automated thanks to AI support, and it goes directly to the responsible employee. The result: an optimized service experience for the customer.
If the chatbot does not understand a customer request, the service process remains under control thanks to so-called fallbacks: the bot simply jumps back to a previous position in the request. At the end of the customer contact it makes sense to have the customer evaluate the support quality of the virtual helper. This provides valuable insights into the acceptance of automated service by the customers. It allows companies to make the most of this competitive advantage.