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  6. [Case Study of Visualization Engine Implementation] Nestlé Japan Ltd.

[Case Study of Visualization Engine Implementation] Nestlé Japan Ltd.

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last updated:May 29, 2025

プラスアルファ・コンサルティング 本社
プラスアルファ・コンサルティング 本社
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We will introduce examples where data-backed analysis not only contributed to product improvement and development but also supported B2B sales!

We would like to introduce a case study on the use of VOC by Nestlé Japan, which operates over 2,000 brands worldwide, including coffee, snacks, and pet food. As a background, the challenge has been how to keep up with the diversification of VOC and the rapid changes in consumer behavior and trends. By analyzing internal data from phone, chat, and email, as well as external data from social media, consumer interviews, and reviews, we achieved high-resolution data analysis through a combination of "listening" to voices on social media and "asking" questions to deepen understanding. [Challenges and Background] - We felt the necessity to deepen our understanding of consumers by paying attention to voices that are not visible through data alone. - The role has shifted from defensive use of VOC for improvements to proactive use that starts from the planning and development stage. *For more details, please refer to the related links or feel free to contact us.

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[Case Study of Visualization Engine Implementation] Nestlé Japan Ltd.

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  • Related Link - https://www.mieruka-engine.com/case/nestle2/

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【Results】 ■ Began to notice hints that were difficult to recognize just by looking at statistical data. ■ Analysis of feedback on products that became popular during the COVID-19 pandemic served as a catalyst for new product development. ■ Not only connected various plans and improvements from VOC, but also managed to communicate information to customers, including feedback on subsequent improvements. *For more details, please refer to the related links or feel free to contact us.

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プラスアルファ・コンサルティング

プラスアルファ・コンサルティング 本社

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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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