How things used to be
Facial expressions, gestures and tone of voice all help to infer nonverbal information communicated along with what someone says out loud during a face-to-face conversation. This allows the people involved to judge the mood of the other more accurately and guide the conversation accordingly. This type of information is often lost in communication channels such as letters, telephone calls, e-mails, online forms, social networks or chatbots. Insurance companies that offer these services are faced with the challenge of assessing their customers’ moods, and have to do so on a large scale, as countless customers use these communication services. The goal is to not just answer customers’ queries reliably, but also to read between the lines, for example to identify an unsatisfied policy holder or recognise when a customer is about to cancel their policy, even if they haven’t explicitly said so.
Then AI came along
An AI-based solution helps insurance companies to do this by using a tool to measure customer satisfaction. The application ‘provides assistance’ automatically in the background. The solution can judge the mood of a text based on the choice of words, expressions and use of punctuation or special characters. A similar solution uses tone of voice and how words are emphasised for phone calls. The system can then assign individual policy holders to groups with a similar degree of customer satisfaction based on these parameters.
Managers can then go beyond simply processing queries and define strategies and measures to improve satisfaction within individual groups. A system supported by AI can also help perform tasks, for example by monitoring measures and measuring success.
The situation today
Thanks to this AI solution, the customer service team can focus its resources on the relevant customer groups and take precautions early. Managers invest in the places where they can influence customer satisfaction in the long term.
Michael Schmal, Manager Business Consulting
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