By delivering the feedback received from customers directly to the staff, we can enhance the motivation of the staff!
We would like to introduce a case where TSI Holdings Co., Ltd., a major apparel company, has implemented the "Visualization Engine." At the beginning of our NPS initiative, we handled everything in-house, categorizing voices based on our own interpretations and analyzing them using Excel. However, we realized that this approach had limitations in terms of the volume of voices we could manage, and relying on individual analysis skills hindered our potential for growth. After the implementation, we were able to validate the intuitive aspects and understand customer voice data objectively. [Challenges and Background] - As the number of brands implementing NPS increased, the volume of data became unmanageable manually. - Initially, each person conducted analyses at their own discretion, which limited the development of analytical skills and introduced subjective judgment. - With the introduction of NPS, we believed that further VOC analysis was necessary to motivate staff involved in the business to take action with a sense of conviction. *For more details, please refer to the related links or feel free to contact us.*
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【Results】 ■ Various actions have been challenged in stores based on the report, contributing to increased revenue. ■ The eNPS score has shifted from negative to positive. ■ By directly conveying customer feedback to the staff, staff motivation has improved, leading to benefits for both customers and the brand. ■ By being able to objectively analyze customer feedback, we can now provide more persuasive reports to the brand side. *For more details, please refer to the related links or feel free to contact us.
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For more details, please refer to the related links or feel free to contact us.
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As a company that continues to create added value from all kinds of information, we have been providing cloud solutions centered around technologies such as 'text mining' and 'data mining' since our establishment in 2006. We visualize big data, such as customer voices, customer data/purchase data, and HR information, and have the power to provide insights.