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AI in customer service: Chatbots deliver fast answers

Chatbot Lizzy in use on a smartphone Adjusting a motor vehicle contract in three minutes: With the help of the digital assistant Lizzy, HDI customers can, for example, easily add an additional driver to their insurance policy online. This improves the customer experience.

In this article you will read about,

  • how e-bot7's artificial intelligence (AI)-based chatbot automates customer communication,
  • how algorithms can be trained easily and quickly in the public cloud,
  • and why the protection of personal data is particularly important.

By how many minutes is my train delayed? Where do I make an insurance claim? Does this jacket also come in blue? In the first six weeks of 2021 alone, the AI-based chatbot from e-bot7 answered around five million such queries in the customer service of companies such as Deutsche Bahn, the insurance group HDI, and the outdoor specialist Vaude.

Since it was founded in 2016, e-bot7 has pursued the goal of automating customer communication and improving the customer experience (CX). To this end, the young entrepreneurs from Munich have developed their own chatbot based on an AI platform. The software robot automatically answers queries from various communication channels. These include company apps and websites, messaging services such as WhatsApp, and social media such as Facebook and Twitter.

More time for individual customer contact

In order to support the customer journey in the best possible way, the bot works hand in hand with the service teams. "No employee has to fear for their job in the process," says Simon Huber, Head of Partnerships at e-bot7. "Rather, the bot supports users in their daily work by answering simple or recurring queries in an automated, fast, and targeted manner."

Daily contact also reduces any anxieties about using artificial intelligence. Employees learn to appreciate the support provided by the bots, as they are relieved of mundane tasks. This gives them more time to devote to more complex questions or to deal with individual concerns more intensively. "With our chatbot, companies are making their customer service more efficient and improving customer satisfaction in the long term," says Huber. One example: at Deutsche Bahn, the chatbot has automated almost 70 percent of all incoming support requests and reduced the duration of dialogs by 90 percent.

Your own bot within 30 minutes

To lower the barrier to entry for artificial intelligence in companies, e-bot7 makes it as easy as possible for those responsible: With the software-as-a-service solution (SaaS), business units can configure their own AI bot within 30 minutes – without any special frameworks, data scientists, or programmers.

The bot can also be operated and further developed without the need for admins or support from the IT department. This is made possible by the SaaS solution’s intuitive user interface and the secure backend. Public cloud resources from the Open Telekom Cloud ensure the high-performance operation of the AI platform. This also ensures high availability and data security. And when it comes to data protection, e-bot7 and the start-up's customers are also on the safe side: all data is stored in the European high-security data centers of the Open Telekom Cloud – something that is particularly important for compliance with the General Data Protection Regulation (GDPR) and the protection of personal data.

Answers from the neural network

But how does the bot know what to answer during a chat? And when do the service employees come into play? "Companies can determine that themselves. They configure how long the bot answers and at what point the employee takes over the communication," says Huber. The customer sets a so-called confidence level that the bot must reach for each question in order to answer entirely without human assistance. This ensures that no incorrect answers are sent.

The bot learns independently and continuously in order to be able to provide increasingly better answers. To do this, the algorithms are trained using various sources. Firstly, with internal information such as FAQs, manuals, or product catalogs. Secondly, the AI platform processes all questions asked and answered by end customers, even if the service employee – and not the bot – chats with them.

Technologies such as natural language processing (NLP), machine learning, and corresponding AI frameworks provide for autonomous learning. In the Open Telekom Cloud, such requirements can be mapped with the ModelArts framework. On this platform, customers can develop and train their own AI models in a protected environment.

In general, the more data chatbots collect and evaluate, the more intelligent they become. Scalability therefore plays a major role in every chatbot project. In order to be able to answer all queries with the same high quality, bots require more and more IT capacity. One advantage of cloud computing: the Open Telekom Cloud provides flexibly scalable resources for computing and storage.

Find out more about e-bot7 and the Open Telekom Cloud.


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