1. The chatbot never sleeps: Customer service is all about convenience, which includes 24/7 customer support. A cost-efficient, yet powerful way to provide basic support is through the never-sleeping chatbot. Devine shared an excellent example of this. In the banking industry, Workfusion’s chatbots are trained by using historical conversations and can perform some of the same tasks as a live support center rep such as correcting an invoice, answering basic questions about account balances and more. Customers receive the same level of service they would get from the support rep. The chatbot can recognize human emotions such as anger, confusion, fear and joy. And, as mentioned above, if the chatbot detects that the customer is angry, upset or frustrated, it will seamlessly transfer the interaction to a human to take over and finish assisting the customer.
These are just the basic versions of intelligent chatbots. There are many more intelligent chatbots out there which provide a much more smarter approach to responding to queries. Since the process of making a intelligent chatbot is not a big task, most of us can achieve it with the most basic technical knowledge. Many of which will be very extremely helpful in the service industry and also help provide a better customer experience.
Rulai also integrates with most messaging channels, customer service software, enterprise business software, and cloud storage platforms. You can either build a Ruali chatbot from scratch with its drag-and-drop design console and let its AI adapt to your customers or you can implement a pre-trained chatbot that has been fed data from your specific industry.
ChatBot provides the best bot platform for designing, building and deploying conversational chat bots to talk to customers and to provide information to users. With support for one-click integration process with Facebook Messenger and a range of other services, you can run powerful and intelligent bots in no time. ChatBot allows using entities, creating conversational scenarios, and it leverages Natural Learning Processing and Machine Learning to develop a human-like experience for customers.
Typically, customer service chatbots answer questions based on key words. The most basic systems are actually document retrieval systems. Sometimes this is frustrating. Think of the times you may have asked Siri or Alexa a question and received the wrong answer. The computer recognizes key words but may not recognize the context in which they are being used. In other words, the computer doesn’t recognize the way people naturally speak. This causes the customer great frustration. However, these systems (including Siri and Alexa) have come a long way and continue to improve.
Cons: Botengine has reduced the workload on the helpdesk department . However ,I fear we may come one day have an advanced Botengine ,years down the line ; which is able to respond to the current complex queries we respond to and thus when that day comes , why would my employer keep me at the job ,when a Bot can do a better job ,without ever getting tired?