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  6. [Case Study of Implementing Sensory AI Analytics] Daily Necessities Manufacturer

[Case Study of Implementing Sensory AI Analytics] Daily Necessities Manufacturer

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last updated:Apr 21, 2025

感性AI
感性AI
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Examples of replacing research and analysis conducted by research companies or in-house.

We would like to introduce a case study on the implementation of the image analysis AI tool "Kansei AI Analytics" at a daily goods manufacturer. The manufacturer wanted to conduct market research for naming a new fabric softener product using a new fragrance technology, but due to cost-cutting measures, the number of research instances was limited, resulting in a long wait for results and concerns about meeting deadlines. After implementation, the phonetic impressions felt by consumers were instantly visualized on-site. Since there was no need to wait for research results, the team could efficiently refine naming proposals without feeling rushed, all while reducing costs. [Case Overview] ■ Before Implementation - It was a project where failure was not an option, but research costs were being cut, and there was little time before the deadline. ■ After Implementation - It became easier to compare using a position map. - The impressions of each naming proposal could be visualized, making it easier to create internal documents. *For more details, please refer to the related links or feel free to contact us.

    Business Intelligence and Data Analysis
日用品メーカー.PNG

[Case Study of Implementing Sensory AI Analytics] Daily Necessities Manufacturer

日用品メーカー.PNG
日用品メーカー.PNG
  • Related Link - https://www.kansei-ai.com/marketingsolution-usecas…
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Emotional AI Analytics Service Introduction Document

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【Release of New Features in Sensory AI Analytics】Started offering "Custom Sensory Scales" that allow users to analyze design impressions based on their unique evaluation criteria.

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The web service "Kansei AI Analytics," which analyzes and visualizes the impressions of images and texts using AI trained on consumer data, allows for the evaluation of package design, naming, and catchphrases based on various adjectives from a marketing research perspective. As a new feature, we have released the "Custom Kansei Scale," which enables users to create their own unique impression evaluation scales and analyze the impressions of images based on them. This feature was developed in response to numerous requests from our customers, such as "I want to evaluate using industry-specific terms" and "I want to measure whether it aligns with the image our brand aims for." By quantifying evaluation axes specific to industries and brands, such as "looks delicious" and "brand identity," we can identify differentiation points from competitors and delve deeper into consumer insights, contributing to more strategic creative design.

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感性AI

感性AI

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Our company was established on May 25, 2018, through joint investment by Keio Corporation and Professor Maki Sakamoto of the National University Corporation, University of Electro-Communications. We are a company that can commercially utilize the intellectual property from the Sakamoto Laboratory at the University of Electro-Communications, which has been certified as a venture originating from the university. By creating AI that understands the hidden senses within people and supports their expression, we aim to become a platform for the utilization of sensitivity.

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