Chatbots

Use of chatbots to automate customer communication

Chatbots are dialog systems with which you can communicate via text input or voice. They are often combined with Avatars and enable websites or instant messaging systems to automatically process inquiries from (potential) customers. In the long term, customer communication can be fully automated.

Prototypes and demonstrators available
Cross-industry deployment
Suitable for SMEs?

The current status

Until around 2016, Chatbots were mostly reserved for large companies, but they can now be found in small and medium-sized enterprises.

The challenge that Chatbots are currently facing is user acceptance. Many customers still prefer to be advised by a real person. But, this is changing as the technology becomes more widespread and reliable. According to to a survey conducted by Bitkom (German Association for Information Technology, Telecommunications and New Media) at the beginning of 2017, one in four Germans already could imagine using Chatbots.

Technology and use

Technology description

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Possible application scenarios

Chatbots provide services in various areas of the company. On the one hand, in direct contact with customers, i.e. in sales or e-commerce (smart & personal search function, assistance services such as sales promotion advice, instant service to answer questions, personalised customer care).

Another field of application is recruitment: chatbots facilitate communication with applicants and take the pressure off employees. In addition to communication tasks, the use of Chatbots is therefore common for organizational tasks such as scheduling or other routine tasks.

Step-by-step introduction

STEP1 Capture knowledge in a structured way

Similar to other self-service tools, the structured recording and categorisation of knowledge is of great importance. In particular, the following distinction must be made:

— Should it be possible for the Chatbot to answer questions about knowledge retrieval directly?

— Is it necessary to clarify by asking questions?

— is direct contact with a human consultant indispensable?

Step 2: Incorporated knowledge based on rules

Initial training of the chatbot

The knowledge database forms the basis for every information. This is where the actual information is stored in a structured manner. This is often done in the form of simple tables that contains question-answer pairs line by line.

Thanks to artificial intelligence, however, this does not necessarily have to be done manually, but can be automated on the basis of existing files or even existing structured websites.

Step 3: Mechanisms for refining detailed requests

Continuous training of the chatbot

Within the knowledge database, the artificial intelligence is inferred to recognise further formulation variants based on questions that have already been asked. The voice assistant always looks at how the questions are and calculates a degree of similarity for each user input. IF an automatic assignment is not possible because the match is too low, the Chatbot will ask for clarification.

Step 4: Self-learning improvement of answer options through AI

By dealing with customers, new word combinations are added to the knowledge database, which increases the precision with which questions are answered. In the case of completely new questions, new knowledge can therefore be generated for the chat bot by transferring individual questions to employees. During the entire learning process, it is important that the operators are always given the opportunity to monitor the new content in order to prevent incorrect learning progress.

Opportunities for SMEs

Facilitation customer communication

More efficient design of service processes

Relief from routine tasks

Cost savings

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