While generative AI is all the talk, there are other AI tools companies are investing in to spur better customer experiences – especially when it comes to IT and self-service.
Growing in popularity, conversational AI chatbots are a great alternative to the often-clunky traditional chatbot experience. In fact, a study from TeamDynamix and CIO.com found that when conversational AI chatbots are used, more than 61 percent of users could effectively resolve their issues without having to put in a ticket or contact support – that’s vs. only a 35 percent resolution rate when traditional chat is used.
So, what is the difference between conversational AI chatbots and traditional chatbots? Traditional chatbots aren’t inherently smart. They lack the “brain” or natural language processing (NLP) that conversational AI chatbots have.
Instead of understanding a person’s intent when a question is asked – a traditional chatbot is programmed to follow a very linear path and any deviation from that path (usually due to the inputs from an end-user or customer) can cause that chatbot to fail. And when a chatbot fails it’s often a frustrating experience and adds to the ticket volume of your IT service desk.
According to that same market study, few companies are satisfied with their current chatbots. The study found that traditional chatbots have a Net Promoter Score (NPS) of negative eight—far from a ringing endorsement—and 65 percent of those surveyed said their solution is not widely adopted by their customers. The addition of conversational AI, however, makes a huge difference— using a conversational AI chatbot increased the adoption rate of the overall chat solution from 16 percent to 50 percent.
When you combine automation, self-service and conversational AI – you can have a positive impact on IT resource drain and improve the experience of your customers and end-users.
Conversational AI chatbots are intelligent software applications that can simulate human conversations and perform tasks such as answering questions, providing information and performing transactions.
Conversational AI leverages natural language processing and understands intent. While they do need to be trained, with conversational AI you can facilitate more complex conversations and resolve issues through actions vs. the traditional chatbot’s question/answer limited dialog path.
Because conversational AI chatbots understand intent, they are much more effective when it comes to assisting customers and end-users. For example, when using traditional chat if you say “My password broke” it would likely respond with something like “I’m sorry, I don’t understand that. Please type your issue again,” and continue down that path with a final response that might give you links to 3-5 FAQ articles that it thinks might help resolve the issue – leaving it to the customer to further seek out a solution to the password problem.
When you have conversational AI, if you were to say “My password is broken” it can infer your intent and know that what you mean is your password isn’t working and needs to be reset. The response from the chatbot is then something like, “I can see you’re having issues with your password. I’ve sent a reset password link to the email on file.”
On the backend, the chatbot can pull the email address needed from the system where it’s stored and automatically send a password reset email – resolving the issue within the conversation in seconds versus sending the customer links and having them do the work to request the link.
Want to learn more about conversational AI and all it can offer versus traditional chat? Check out our market study: State of Chatbots and Conversational AI.