Detecting emotions in a chatbot conversation
A sentiment & emotion analysis tool can detect the polarity of an exchange as well as the possible emotions present. It is a key tool for giving value to the information coming from customer interactions, especially when these exchanges take place with a chatbot.
What does your customer really think?
The digitization of customer relations implies replacing certain interactions between the customer and an advisor or a salesperson by exchanges with conversational agents or chatbots. This tool, when well-adapted to the company's activity and to the customer's needs, can accelerate and facilitate most of the processes. For the company that implements it, the chatbot saves time, increasing the efficiency of the teams of advisors who can generally concentrate on tasks with higher added value. It allows advisors, whether in pre-sales or in after-sales service, to limit their interactions with the customer to priority or complex subjects. However, this use of chatbots carries the risk of missing key information about the customer. Worse still, automation runs the risk of missing out on a customer's dissatisfaction with, for example, their telephone subscription, their annoyance due to repeated power cuts, their exasperation at not being able to find the information they want on their online banking application, etc.
Some human-machine interactions cannot be automated because they require empathy from a customer service department, an attentive ear and, above all, speed in processing requests. Unfortunately, sales and after-sales teams lack the resources and time to make use of this information in a timely manner. And very often this frustration with the chatbot can increase the risk of attrition (churn rate).