Self-service and automation through AI chatbots: Energy provider TEAG shows how it works (German only)
On-demand webinar (available anytime)
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The live webinar provides exciting practical examples and insights into innovative AI technology from Frederik Schröder (MoINai) and Hendrik Kupfer (TEAG).
Sign up for the webinar:
Speakers in the panel:
Frederik Schröder ist Experte für Chatbots & KI. Seine Mission: Das Potenzial künstlicher Intelligenz für Unternehmen nutzbar machen. Dies tut er in seiner beruflichen Praxis mit Kunden und im Rahmen von Vorträgen & Webinaren, in denen er das Potenzial von KI und Automatisierung anhand von Praxisbeispielen erlebbar und nachvollziehbar macht.
This is what you can expect in the webinar:
The webinar provides exciting practical examples and insights into innovative AI technology from Frederik Schröder (moinAI) and Hendrik Kupfer (TEAG).
You will also learn how to use a self-learning AI chatbot Build customer relationships, the Improve customer experience and the Relieve customer service.
On July 29 at 11 a.m. in 45 minutes (30 min. content + 15 min. Q&A) Using practical examples, explains all steps that lead to a successful implementation of an AI chatbot.
After participating in the webinar, you will know everything you need to know about these topics:
- Why an AI chatbot? The reasons why a direct chat channel and automation are so important for companies — especially in 2021.
- The “3 step” energy template: How a hybrid “agent AI approach” (live chat system Userlike + moinAI) can be successfully implemented in practice.
- TEAG best practice: The webinar shows live how TEAG uses an AI chatbot on its own website.
- Digital self-service solution: Automate recurring customer inquiries and reduce support costs by 25% with a digital assistant.
- AI Deep Dive: How independent learning is possible based on artificial intelligence and can therefore automate more and more inquiries.
- Profitability calculation: How the increase in conversion rates and saved support ticket costs can be calculated before implementation.