感性AI List of Products and Services

"Emotional AI Analytics" is an image analysis AI tool that instantly analyzes and visualizes the sound of names, the impression of catchphrases, and package designs using AI trained on consumer data. Without conducting surveys such as marketing research, it enables instant testing of names, catchphrases, and package designs. Additionally, it allows for easy text mining from your existing documents. 【Features】 ■ Impression evaluation analysis ■ Analysis by age and gender, and by product ■ Analysis results that are easy to understand intuitively ■ Project registration function ■ Display of average values ■ CSV download of data *For more details, please refer to the related links or feel free to contact us.

We would like to introduce a case study on the implementation of the image analysis AI tool "Kansei AI Analytics" at a confectionery manufacturer. At this manufacturer, the criteria for selecting packaging had become based on intuition, and they were struggling with how to choose designs that effectively conveyed their concept due to a lack of research funding. After implementation, they were able to visualize color impressions in graphs simply by uploading images. It became possible to select packaging with emotional value that they wanted to convey to consumers based on solid evidence from multiple ideas. [Case Overview] ■ Before Implementation - They were always selecting packaging ideas based on intuition, but they wanted to demonstrate internally that they could make selections based on evidence that would contribute to sales. ■ After Implementation - By using visually clear selection criteria, the level of agreement within the company increased, and they were able to showcase the presence of their department. *For more details, please refer to the related links or feel free to contact us.

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.

We would like to introduce a case study on the implementation of the image analysis AI tool "Kansei AI Analytics" at an advertising agency. As an advertising agency, we have been delivering catchphrase proposals for hand soap to clients, but since these proposals were created based on years of intuition and insights, it was difficult to provide evidence for them, making it challenging to gain client approval. After the implementation, the emotional impressions felt by consumers can be instantly visualized in graph form on the spot. Since evaluations can be conducted repeatedly, we are now able to assess all catchphrases from the stage of brainstorming ideas for delivery. [Case Overview] ■ Before Implementation - While we could understand the tendencies preferred by the persona from past data, we could not provide evidence for why this catchphrase resonates, as it was based on long-standing intuition. ■ After Implementation - By being able to provide evidence for intuitive insights, the delivery process has become smoother, and the number of requests has increased. *For more details, please refer to the related links or feel free to contact us.

We would like to introduce the feature "Catchphrase/Package Analytics" in the AI tool "Kansei AI Analytics" for testing catchphrases and banners. Visualize the effectiveness of catchphrases and banners instantly. Even catchphrases and banners that are usually not subjected to research can be determined based on quantitative data using this tool. This can solve the problem of having few opportunities for user testing of catchphrases and banners. 【Features】 ■ Instantly visualize the effectiveness of catchphrases and banners ■ Even catchphrases and banners that are usually not researched can be determined based on quantitative data using this tool *For more details, please refer to the related links or feel free to contact us.

We would like to introduce the feature "Package Analytics" in the development of the image analysis AI tool "Kansei AI Analytics." It instantly visualizes the impressions consumers have of packaging. Since it can quantify the impressions of packaging proposals without conducting surveys, the time for package development is significantly reduced. This solves the problem of "not having enough time to reach a package that realizes the concept." 【Features】 ■ Instantly visualizes the impressions consumers have of packaging ■ Since it can quantify the impressions of packaging proposals without conducting surveys, the time for package development is significantly reduced *For more details, please refer to the related links or feel free to contact us.

We would like to introduce the feature "Associative Word Brainstorm" of the image analysis AI tool "Kansei AI Analytics" for exploring consumer needs. By entering a keyword, a large number of words associated with that keyword are displayed. You can expand associative words based on popular snacks to consider the next hit product, or explore new flavors, allowing for various leaps in creativity. 【Features】 ■ By entering a keyword, a large number of words associated with that keyword are displayed. ■ You can expand associative words based on popular snacks to consider the next hit product or explore new flavors, enabling various leaps in creativity. *For more details, please refer to the related links or feel free to contact us.

We would like to introduce a case study utilizing "sensitivity AI analytics" for the new 2000 series train of Keio Corporation. In the concept development phase, we utilized "text mining" for survey analysis and word extraction. From multiple proposals by designers, we analyzed consumer perceptions using "image impression analysis" to determine the final design that matches the concept. [Case Overview] ■ Target: Keio Corporation New 2000 Series Train ■ Utilized Functions: Text Mining, Image Impression Analysis *For more details, please download the PDF or feel free to contact us.

We would like to introduce a case study utilizing "Emotional AI Analytics" in the selection of packaging at advertising agency A. The company faced a challenge where designers typically selected product packaging based on intuition, but ideally wanted to make selections based on evidence. By utilizing this tool, it became possible to choose packaging that conveys the desired emotions to consumers, backed by solid reasoning from multiple ideas. 【Case Overview】 ■Challenge - The product concept itself is "cheerfulness" and "fun," so they wanted to select packaging ideas that align with this concept. ■Solution - By using visually clear selection criteria, it became an effective persuasive tool during internal submissions. *For more details, please download the PDF or feel free to contact us.

We will introduce case studies of utilizing "Emotional AI Analytics" for efficient advertising/product design. A certain company faced the challenge of not clearly understanding what kind of creative would attract attention and lead to sales. By combining the viewing and purchasing data of their own creatives with emotional evaluations of the creatives, they were able to identify impressions that are believed to lead to attention and sales. [Case Overview] ■ Challenge - They wanted to create creatives efficiently with minimal variation. ■ Solution - By combining their own creatives' viewing and purchasing data with emotional evaluations, they were able to identify impressions that are believed to lead to attention and sales. *For more details, please download the PDF or feel free to contact us.

We would like to introduce a case study utilizing "Sensory AI Analytics" in the design of automobiles at automotive company B. By analyzing freely written documents from brainstorming meetings, target hearings, and surveys, we visually grasped frequently used words and the relationships between them. Additionally, we confirmed the words that the target associates through text and images in the expression of the worldview and the creation of mood boards, exploring vocabulary to express the image. 【Case Overview】 ■ Subject: Automobile design ■ Challenge: Verbalizing images and sourcing materials for persona setting ■ Effect: Accelerating the construction of worldview and concepts *For more details, please download the PDF or feel free to contact us.

This document provides detailed information on sensory information and methods for measuring sensitivity. It introduces the basics of visual, auditory, and tactile information, as well as psychological methods such as the SD method and tasks. Additionally, it explains intuitive one-word methods for measuring sensitivity, so please take a moment to read it. 【Contents】 ■ What is sensitivity ■ What is sensory information - Visual information - Auditory information - Tactile information ■ Measurement of sensory information *For more details, please download the PDF or feel free to contact us.

This document provides a detailed explanation of the fundamentals of AI. It introduces what AI is, including the differences between AI, humans, and robots, as well as AI technologies such as machine learning and deep learning. Additionally, it includes information on what can be achieved with AI, along with challenges and initiatives, so please take a moment to read it. [Contents] ■ What is AI ■ Types of AI: Narrow AI and General AI ■ AI Technologies: Machine Learning and Deep Learning ■ History of AI ■ What can be done with AI (Examples of Affective AI) *For more details, please download the PDF or feel free to contact us.

This document introduces the differences between hiragana and katakana in the representation of onomatopoeia. It explains the definition and classification of onomatopoeia, as well as the rules for representation in newspapers, communications, and broadcasting. Additionally, it includes graphs to clearly illustrate the differences in imagery based on the representation of onomatopoeia. [Contents] ■ What is onomatopoeia ■ Rules for representing onomatopoeia ■ Actual representation of onomatopoeia ■ Differences in imagery based on the representation of onomatopoeia ■ Research from the Sakamoto Laboratory at the University of Electro-Communications and development by Kansei AI Inc. *For more details, please download the PDF or feel free to contact us.

This document explains the significant keywords related to exploring the impression of sounds in words, specifically focusing on onomatopoeia and sound symbolism. It includes research on Japanese onomatopoeia, the arbitrariness of language and sound symbolism, and the parts of speech of onomatopoeia. Additionally, it provides a detailed introduction to the history of the birth, disappearance, and changes of onomatopoeia, so please take a moment to read it. 【Contents (excerpt)】 ■ Onomatopoeia and sound symbolism ■ The arbitrariness of language and sound symbolism ■ Research on Japanese onomatopoeia ■ Parts of speech of onomatopoeia ■ The modality and polysemy of the five senses expressed by onomatopoeia *For more details, please download the PDF or feel free to contact us.

This document introduces a course on the principles of naming, conducted by the COO of Kansei AI Inc. and the Vice President of the University of Electro-Communications. It provides detailed explanations on tips for creating hit product names, as well as the effects of naming for different product categories. Additionally, it summarizes an AI system that evaluates the impression of product names. [Contents] ■ Tips for creating hit product names ■ The connection between the sound of names and their impressions ■ The effects of naming for different product categories ■ AI that evaluates naming *For more details, please download the PDF or feel free to contact us.

This document discusses a value strategy utilizing AI focused on emotional appeal. It introduces the three fundamental theories of marketing regarding what it means to sell products to consumers. Additionally, it provides a detailed explanation of the brand-building blocks that visualize the steps for brands to build connections with consumers, as well as methods for quantifying and visualizing emotional information. [Contents (excerpt)] ■ What it means to sell products to consumers ■ DAGMAR theory ■ Brand-building blocks ■ What is emotion? ■ Methods for quantifying and visualizing emotional information *For more details, please download the PDF or feel free to contact us.

This document provides a detailed introduction to brand value and emotional value in marketing. It includes information on brands that demonstrate superiority in marketing and methods for building strong brands. Additionally, it summarizes the value of brands as discussed by leading experts in brand research, so please take a moment to read it. [Contents] ■ What is a brand? ■ What is branding? ■ How to build a strong brand ■ Value of a strong brand 1 ■ Value of a strong brand 2 *For more details, please download the PDF or feel free to contact us.

"Emotional AI Analytics" is an image analysis AI tool that instantly analyzes and visualizes the sound of names, the impression of catchphrases, and package designs using AI trained on consumer data. Without conducting surveys such as marketing research, it enables instant testing of naming, catchphrases, and package designs. Additionally, it allows for easy text mining from your existing documents. 【Features】 ■ Impression evaluation analysis ■ Analysis by age and gender, and by product ■ Analysis results that are easy to grasp intuitively ■ Project registration function ■ Display of average values ■ CSV download of data *For more details, please refer to the related links or feel free to contact us.

When developing a marketing strategy, have you ever wondered, "What position does our product hold in the market?" or "How can we differentiate ourselves from competitors?" A powerful tool to address these challenges is the "Positioning Map." Among them, the method that conducts market analysis based on consumer recognition and perception is the "Perception Map." This article comprehensively explains the basic concepts of Positioning Maps and Perception Maps, practical ways to create them, and industry-specific case studies. Additionally, we will introduce a new approach using AI that overcomes the limitations of traditional methods. *For detailed content of the column, you can view it through the related links. For more information, please feel free to contact us.*

"There are multiple design proposals, but there is no objective basis for deciding which one to choose." "I cannot provide a convincing explanation to my superiors and stakeholders beyond just a vague sense of goodness." "When compiling a report on panel surveys, simply listing numbers is not satisfying." These are challenges that every marketing professional faces. In particular, there are many situations where a clear rationale for "why this proposal was chosen" is required within limited budgets and time. Whether it's package design, product naming, or catchphrases—despite conducting consumer research, it often takes a lot of time to interpret and explain the evaluation results, and even then, it is difficult to make them sufficiently persuasive. To address these challenges, we introduce the new features "AI Insights" and "AI Chat" added to "Kansei AI Analytics." *For more details on the column, please refer to the related link. For further inquiries, feel free to contact us.*

The strategy of package design that is essential for attracting consumers' attention and prompting them to pick up products among the countless items lined up on the shelves of supermarkets and convenience stores. Especially in the case of beverages, packaging serves as the "face" of the product, not only shaping the brand image but also directly appealing to consumers' visual senses and emotions, significantly influencing the repeat purchase rate. Therefore, rather than relying on vague impressions, it becomes extremely important to evaluate packaging from multiple perspectives and scientifically analyze consumers' sensibilities through "packaging research." This article focuses on the package design of beverage cans and introduces effective case studies of packaging research using the AI tool "Kansei AI Analytics," which has learned from consumer survey data. *For more details, please refer to the related links. Feel free to contact us for further information.

We would like to introduce a case where "Kansei AI Analytics" was utilized in the package design production of the new product "Yonezawa Beef Curry" by Keio Restaurant Co., Ltd. Since it is a premium product, it is essential to effectively convey a sense of "luxury" to the target customers. There was a challenge in determining whether the design truly resonates with customers, as it was difficult to judge solely based on the subjective opinions of the person in charge. By utilizing our product, we were able to visualize the "luxury" that resonates with the target audience and achieve package design production based on objective data. We received feedback stating, "We felt that we could successfully incorporate not only the preferences and sensibilities of senior professionals but also elements from a third-party perspective into the design." [Case Overview] ■ Hypothesis examination of focal points: Identifying elements of luxury through market research ■ Positioning determination: Establishing the design direction that resonates with the target audience ■ Reevaluation of revised designs: Incorporating consumer perspectives to refine the design ■ Visualization of improvement points: Clarifying the strengths and weaknesses of the design *For more details, please download the PDF or feel free to contact us.

On the October 27 broadcast of TV Tokyo's "Yugata Satellite," the development process of Keio Electric Railway's new commuter train model "2000 series," which utilizes "sensitivity AI analytics," was introduced. *For more detailed information, you can view the related links. For further details, please download the PDF or feel free to contact us.*