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.
Overall: We are now able to leave our Chat on 24/7, when previously we had limited hours (due to staffing) for the Chat. It is still very much a work in progress to ensure the ChatBot has routed to the correct conversations and can sometimes be frustrating to try and figure out why the ChatBot went to a certain scenario over another. The help topics the company provides can point you in the right direction but they are written at a level above the capabilities of a brand new user to bots in my opinion. Determining whether or not no conversation with a client vs a below average conversation with a client (at times) is worth it, will determine whether we continue to renew our monthly subscription.
Cons: Initial onboarding is wonky and can use UX upgrades. It was difficult understanding how to get started until I watched several videos. I also had issues using this platform on Firefox to connect Facebook messenger. Currently, the workaround is to use Chrome to connect messenger and then you can continue working on Firefox. I don't like having to use a different browser to obtain functionality. The team promised this was a bug that will be ivnestigated
But even though most chatbots can handle moderately sophisticated conversations, like welcome conversations and product discovery interactions, the if/then logic that powers their conversational capabilities can be limiting. For instance, if a customer asks a unique yet pressing question that you didn’t account for when designing your chatbot’s logic, there’s no way it can answer their question, which hangs your customer out to dry and ultimately leaves them dissatisfied with your customer service.
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Created in 1966 as an early natural language processing (NLP) computer program that emulates a Rogerian psychotherapist, a clinical practice that allows clients to take more action and progression in discussions. This is also known as person-centered therapy. Developed by Joseph Weizenbaum, ELIZA, named after a character in the play Pygmalion by George Bernard Shaw, is generally known as the first chatbot.
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?
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