Wednesday, January 18, 2017

Fujitsu launches technology analysis of customer satisfaction – Magazine BIT, computers for all.

The Fujitsu Laboratories want to incorporate the technological innovation in the Human Centric AI Zinrai, the area of artificial intelligence company, and to offer it as a product for assessments of customer service and in training staff in companies that emphasize communication, from banks to retail stores. The plans of the company are to market the novelty from march of this year to the call centers and at the end of 2019 for all other areas of the market.

According to the company, the technology aims to solve a common problem in the customer support service, which can be in a call center or in a box of a bank. In the past there have been made numerous efforts to convert conversations with clients to written text – with the voice-recognition technology – with the goal of understanding the feeling of satisfaction. Only that there are situations in which the same words may convey satisfaction or dissatisfaction, depending on the intonation of the voice. Therefore, it was impossible to fully understand the feeling of the client.

To solve the problem, the technology of Fujitsu takes into account not only the tone of the voice and its degree of variation, but also the changes in voice that span multiple words – either at the beginning or at the end of a conversation. So, he managed a quantification of highly accurate of the joy of voice. In addition, it is possible to use machine learning along with the evaluations of service delivery to the client. The novelty of the company automatically identifies when a customer is satisfied or dissatisfied with approximately 70% accuracy, in comparison with the results of a determination made by the human ear.

In a period of field testing, the use of technology in the call centers Fujitsu Limited and Fujitsu FSAS Inc., the company confirmed the increase in the efficiency of the training, as well as in monitoring, evaluation of care, and feedback of results. In this way, it was possible to reduce time-to-contact with the client in about 30%. There was also greater acceptance of the evaluator and the person evaluated due to the increased objectivity in the service.

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