I'm always surprised by the range of industries and topics I deal with on a daily basis and how diverse the solutions are that we implement for our customers. Not only do I get to know a lot of interesting people, but I also gain deep insights into many different industries with their specific customer service challenges. Yesterday, for example, we were talking about last-minute bookings via voice portal for a major pay-TV broadcaster. Tomorrow, I'll be talking to a furniture store that wants our voicebot to answer questions regarding product availability in the nearest store or the delivery status. A week later, I'm sitting down with a government agency in Berlin that wants our voicebot to support the universal phone number D115. Or an energy supplier who wants to record meter readings via a VoiceBot and automate fault announcements.
For automation projects in customer service, my expertise as a consultant is almost always in demand, because our clients rely on our many years of experience in this area. The best example is the topic of artificial intelligence: If you believe the AI hype, all you have to do to make customer service work is install a ChatBot or VoiceBot and the AI will answer all your questions independently. Of course, these are pure marketing statements and I have to bring my customers back down to earth. Especially if they are convinced that this is exactly how it works and no other way.
The fact is that an AI first has to be intensively trained before it is able to answer customer inquiries to their satisfaction. To do this, as many real customer conversations as possible should be recorded and analyzed. Our speech-to-text transcription solution and AI-supported text analysis are a great help here. Nevertheless, a good deal of manual work is still required to correctly determine the customer's preferences. Only then does the VoiceBot not only recognize the spoken word, but also interprets it correctly and "understands" the caller's specific request.
Only at first glance. VoiceBots are about natural language input, and chatbots, messenger services or e-mails are about the written word, but in all these communications the processing is ultimately done as text and not as audio. Using speech recognition and natural language processing (NLP), a text can be created from the telephone dialog, which can be responded to in exactly the same way as in a chat.
That's why we urge our clients to bundle their input streams from the various communication channels right from the start of their projects. In this way, all data for customer service, i.e., request recognition, and the response database, originate from a central source. After all, it is not acceptable for customers to receive varying answers in VoiceBot, ChatBot or Messenger and for the downstream processes to differ from one another. The integration of our solutions into existing systems and the connection to backend systems and databases is therefore a crucial part of the work of our project managers and UI and UX designers.
We take a best-of-breed approach to these technologies. We use market-leading technologies from Nuance/Microsoft, Google and Amazon. Together with our clients, we decide which technology is best suited. Of course, in this context we also take into account data protection requirements and the type of use, i.e. as a solution from the cloud or on-premise. When it comes to billing models, customer-friendliness and flexibility are key for us, as we offer a wide range of purchase, rental and pay-per-use models for our end-to-end solutions.