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