Today, most of customer service calls to companies still meet a digital voice system or a request to narrow down the reason of the call. And only then you are redirected to a service agent.
In our modern times, analog telephone systems are nearly gone and increasingly replaced by state-of-the-art voice-controlled switching systems.
As more and more companies use conversational interfaces support service agents, rudimentary chat conversations between humans will soon be outdated.
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They will provide clients with professional, efficient and highly personalized answers.
The most modern version of this customer service is called digital chatbot. They are controlled by a highly complex and powerful AI (Artificial Intelligence).
They learn semi-independently each time they interact with a customer. By doing so, they increase the possible response base for future inquiries.
In addition, they also analyze semantic parameters and can better understand complex relationships.
Above all, call centers will soon be able to make major changes as more and more companies consider chatting as the most natural way of interacting with customers.
Only when the customer inquiry or the conversation becomes too complex and intransparent, the chatbot will hand over the conversation to a human employee.
Requirements for a chatbot
To handle such a complex task, a chatbot must have a sophisticated approach and a powerful AI. The chatbot must also be able to access a large data and knowledge base in order to be able to form a semantic logical answer to the customer at any time.
Through appropriate networking and neural algorithms, chatbots are also able to quickly analyze complex dialogue scenarios and provide logical answers. The only natural barrier to an AI is the fact that it is only as powerful as the database it can access.
According to a study by Nielsen, 56% of consumers said they preferred having their service issues resolved by an automated chatbot. The neutral digital service employee plays a huge role here.
Probably the biggest requirement for a digital service agent will be the correct application of the respective national language. What works very well in English-speaking countries, could for example lead to different voice output in German-speaking countries.
On the one hand, this is because of the different umlauts and consonants and on the other hand tue to German grammar and different sentence positions.
However, simple customer and service inquiries can answered without any problems using well-defined questions and answers.
During the conversation with a customer the chatbot learns with every word, sentence and customer problem. Therefore, the existing knowledge base can be expanded and refined quickly.
Self-learning chatbots can compensate for the still existing language problems very elegantly and might in the near future even completely overcome them.
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Advantages and disadvantages of a chatbot
Companies that rely on a customer service chatbot can leverage many of the benefits of this new technology.
One of the key benefits is likely to be the 24/7 availability for enterprise customers. They can message at any time and will be helped competently.
Another advantage is the high learning abilitiy of the chatbot, which is very important to optimize the customer experience. Simple problems such as operator errors on the customer side are usually resolved immediately and in a quick dialogue.
Time-consuming and cost-intensive customer queries such as name, address and contact options are handled elegantly and quickly by automated chatbots. The direct interface to the knowledge database allows immediate linking and evaluation in order to recognize the problem of the customer.
When the chatbot has reached its limits or the customer requests for a human employee the conversation can be taken overs eamlessly by a human service agent. Some problems are still to be solved but with increasing technological progress that should happen in the near future.
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The future for chatbots and AI systems looks bright. Rapid technological advances and efficient natural language processing (NLP) ensure ever-faster and high quality system adjustments.
Large companies such as Facebook and Google already use corresponding chatbot-systems to ensure optimal customer experience for services such as news, chats or in search queries.
This time the biggest difficulty is the fact that the computing power required for a powerful chatbot is currently immense.
In fact, without sufficient data and self-learning algorithms, a chatbot cannot engage in serious interaction with a human counterpart.
Once these problems are solved, chatbots could play a much bigger role in our daily lives than they do today.
In the course of time we’ll get a better picture of where this will lead and which areas will be affected.
Are you ready to take your customer communication to the next level? Check out our chatbot solutions.
Read more about chatbots:
- 7 Reasons Why You Should Invest In Chatbots In 2018
- Industry Influencers’ Predictions For Chatbots In 2018