We will work on a cross-sectional analysis of VOC from the NPS surveys collected from EC and stores, aiming to maximize LTV.
We would like to introduce a case where the "Visualization Engine" was implemented at Pal Co., Ltd., a major apparel manufacturer. The company was looking to start analyzing the VOC from NPS surveys conducted through their CRM tool, "Customer Rings," for customer management. By linking the response data with the customer data accumulated in "Customer Rings," they were able to integrate it into the system and compare and analyze by segment. By attaching customer information to the data, they could perform analyses from perspectives that could not be obtained from a single survey. [Challenges] - While gathering a vast amount of feedback through NPS, there were limitations to analysis by manual effort. - Due to changes in consumer behavior, there was a need to analyze VOC from both e-commerce and physical stores in a cross-sectional manner to grasp the "accurate picture" of customers. *For more details, please refer to the related links or feel free to contact us.
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【Results】 ■ We have established a system that captures customer characteristics from our unique perspective, allowing us to identify key points for deeper exploration rather than merely viewing aggregated data as a collection of numbers, leading to valuable insights. ■ The analysis results serve as evidence, enabling service improvements exemplified by revisions related to returns. *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.
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