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[Case Study] Customer Service / AI Function Conversation Analysis (Speaker Separation)

By obtaining and transcribing conversation data with customers, it becomes possible to understand the situation even without being on-site.

We will introduce a case that addresses the issues of not being able to grasp the customer service situation and content in stores, and staff being exhausted due to customer harassment. By implementing "Actcast" and capturing the conversation content as text data, we can enhance the quality of customer service and allow staff to serve customers with peace of mind. Additionally, by placing AI microphones in stores and processing the audio data to separate it into customer and staff sides, we can further convert this data into text on the server side. Based on this conversation data, we can improve employee training and implement measures against customer harassment. [Case Overview] ■ Issues - Unable to grasp the customer service situation and content in stores - Staff are exhausted due to customer harassment ■ Results - Ability to understand the situation even when not on-site - Improvement of employee training and implementation of measures against customer harassment based on conversation data *For more details, please refer to the related links or feel free to contact us.

  • DMP
  • IoT
  • Edge analysis device

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