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The voice of the market is a treasure trove of ideas that leads to the development and improvement of products and services, as well as promotional planning. Its importance in corporate activities is increasingly rising. However, when it comes to "utilizing the voice of the market in marketing strategies," many responsible individuals may find themselves wondering, "How should we do this...?" To address the challenges of analyzing the voice of the market in marketing activities, we will introduce the know-how of a "visualization engine" that supports the analysis and utilization of text data from 1,600 companies, focusing on the series of actions involved in collecting, analyzing, and utilizing data. *For detailed content of the column (such as blogs), please refer to the related links. For more information, feel free to contact us.*

• Business Intelligence and Data Analysis

With the evolution of voice recognition technology in digitalization, the voice recognition market is expanding due to the needs for online business activities caused by the COVID-19 pandemic, data utilization from the perspectives of DX (Digital Transformation) and CX (Customer Experience), and the visualization of customer experiences. However, even with the spread of voice recognition, there are still many companies that only focus on transcribing voice into text. When it comes to "effectively utilizing voice recognition data," many responsible individuals may find themselves wondering, "How should we do this?" To address the challenges in analyzing VOC (Voice of Customer) data related to voice recognition, we will introduce a series of initiatives for collecting, analyzing, and utilizing VOC, leveraging the know-how of a "visualization engine" that supports VOC analysis and utilization for 1,600 companies. *For more detailed information, please refer to the related links. Feel free to contact us for further inquiries.*

• Business Intelligence and Data Analysis

Text mining is the process of analyzing the words in a text to extract useful information. With the widespread use of the internet and social media, it has become possible to obtain vast amounts of text data, and companies can effectively utilize this data to enhance their marketing efforts. In this article, we will explain what text mining can actually do and how it can be utilized. *For detailed content of the article, please refer to the related links. For more information, feel free to contact us.*

• Business Intelligence and Data Analysis

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.

• Business Intelligence and Data Analysis

To Chūnihon Expressway Company, which is responsible for the operation of service areas, we would like to introduce a case where the "Visualization Engine" was implemented. The company needed to establish a system that automatically detects related controversies and notifies stakeholders in a way that is easily understandable to anyone, without allocating human resources for social media monitoring. With the implementation, the burden of having staff monitor social media daily, classify, and report manually, even on their days off, has been completely eliminated. Additionally, by building the automatic detection system, the company can now respond to an increase in new monitoring and reporting requirements with minimal effort. [Challenges and Background] - There was a growing need for real-time situational awareness instead of post-event reporting. - Manual monitoring required about an hour of resources each day. - There was a need to build a system that automatically notifies stakeholders without using human resources and in a way that is easily understandable to anyone. *For more details, please refer to the related links or feel free to contact us.*

• Business Intelligence and Data Analysis

We would like to introduce a case where the "Visualization Engine" was implemented at the Morohashi Modern Art Museum, a public interest foundation. Using a word cloud, we projected the voices of visitors both in the venue and online onto the venue itself, challenging the concept of "interactive appreciation" during the COVID-19 pandemic. We adopted this system for its pop and easily readable output. We collected feedback on the artworks using this system and projected it as a word cloud on the walls of the museum using a projector. This allowed us to express the impressions of those who viewed the same artwork as a "form," regardless of location or time. [Initiatives] - Feedback posted by visitors from tablets within the museum and impressions shared by online viewers on social media were visualized in a word cloud format. - In addition to projecting in real-time on the walls of the museum, the output was also shared on the web. *For more details, please refer to the related links or feel free to contact us.

• Business Intelligence and Data Analysis

At Osaka Gas Co., Ltd., we introduced a case study on the implementation of generative AI training, focusing on the summarization and classification of texts using the "Visualization Engine" AI features. As we manage customer feedback (such as VOC and social media posts) from various channels in a centralized manner to enhance services and improve operations, we faced challenges in the rapid and accurate (not reliant on individual judgment) analysis of the increasing volume of feedback. By utilizing generative AI features, we realized the potential to streamline daily and monthly analysis tasks and report creation, making traditional processes simpler and more effective. [Case Overview] ■ Challenges - Rapid and accurate (not reliant on individual judgment) analysis of increasing feedback ■ Achievements - Streamlined daily and monthly analysis tasks and report creation, realizing the potential to advance traditional processes in a simpler and more effective manner - Improved the accuracy of summarization and classification of VOC data through prompt tuning *For more details, please refer to the related links or feel free to contact us.

• Business Intelligence and Data Analysis

We would like to introduce a case where Bandai Co., Ltd. implemented the "Visualization Engine." Until now, we had only been using BI tools to check quantitative data, but to understand the details of where product defects were occurring, we had to read through each text one by one. Additionally, with a large number of items, classifying the symptoms of defects and understanding their content required an enormous amount of time and effort, which was a challenge. With the implementation, it became easier to predict fluctuations in product inquiries, allowing us to anticipate necessary responses in the future and communicate with related departments earlier, resulting in smoother collaboration. [Challenges and Background] - With the conventional BI tools, it was necessary to read through each detail to grasp the specifics of defects, which hindered sufficient analysis due to issues of effort and labor. - There was a need to enhance VOC activities to connect VOC to improvements in products and services. *For more details, please refer to the related links or feel free to contact us.*

• Business Intelligence and Data Analysis

We would like to introduce a case where Mizuho Bank, Ltd. has implemented a new feature using the generative AI of the "Visualization Engine" that enables positive and negative assessments of social media posts. The company is actively working on utilizing VOC (Voice of Customer) and has leveraged this to enhance the collection and analysis of VOC across a wide range of areas, aiming to further improve customer satisfaction. With this implementation, it has become possible to analyze the full text of social media posts and understand the context, allowing for the detection of nuanced expressions that were previously difficult to identify, thereby enabling a more accurate grasp of customer voices on social media. [Case Overview] ■ Background - To strengthen the collection and analysis of VOC across a wide range of areas ■ Results - It has become possible to detect nuanced expressions that were previously difficult to identify - A more accurate understanding of customer voices on social media has been achieved *For more details, please refer to the related links or feel free to contact us.

• Business Intelligence and Data Analysis

We would like to introduce a case study of the implementation of the "Visualization Engine" at Sekisui Chemical Co., Ltd. The company recognized a problem where, despite accumulating a lot of data across various sites, the utilization of qualitative data was insufficient. After the implementation, by utilizing text mining to analyze qualitative data such as open-ended survey responses to discover backgrounds and causes, they were able to acquire fundamental knowledge regarding qualitative analysis. [Initiatives] - Planned a total of six training sessions to learn qualitative data analysis methods while actually operating the product. - A public call for participants attracted 117 applications, and the program was conducted with 32 participants across different groups. - Participants brought in data they actually handle in their departments and engaged in group discussions to promote practical application in their work. *For more details, please refer to the related links or feel free to contact us.

• Business Intelligence and Data Analysis

We would like to introduce a case where Panasonic Operational Excellence Co., Ltd. implemented our "Visualization Engine." Quantitative data is easily visualized in numbers, but qualitative data is difficult to measure, often relying on subjective confirmation through visual inspection. Additionally, we wanted to improve the efficiency of survey aggregation, which was being done manually by the person in charge of each program. By utilizing services that include "Solrepo" for survey analysis, we were able to eliminate analysis resource constraints while enabling advanced analysis, resulting in higher resolution of analysis results. [Challenges and Background] - We wanted to utilize qualitative data, which had been limited to visual inspection, for improvement activities. - There was a lack of resources for qualitative data analysis. - We felt the need to reconsider aspects such as survey design to enhance the analysis. *For more details, please refer to the related links or feel free to contact us.*

• Business Intelligence and Data Analysis

We would like to introduce a case where the "Visualization Engine" was implemented at the Osaka University Microbial Disease Research Institute, which has been engaged in research on microorganisms that are factors in diseases. The organization has faced the challenge of increasing the number of people aspiring to be scientists and those who understand science, as the number of individuals pursuing careers in science and research has been decreasing year by year. With the implementation, when creating an information site, the direction was changed based on the results of surveys and analyses, leading to the development of a Q&A site that meets the needs of the public. [Challenges and Background] - The decreasing number of individuals aspiring to be scientists and researchers, and the need to increase those who aspire to be scientists and understand science. - Considering how to better utilize the feedback from surveys accumulated at the research institute in practical initiatives. *For more details, please refer to the related links or feel free to contact us.*

• Business Intelligence and Data Analysis

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.

• Business Intelligence and Data Analysis

We would like to introduce a case where TSI Holdings Co., Ltd., a major apparel company, has implemented the "Visualization Engine." At the beginning of our NPS initiative, we handled everything in-house, categorizing voices based on our own interpretations and analyzing them using Excel. However, we realized that this approach had limitations in terms of the volume of voices we could manage, and relying on individual analysis skills hindered our potential for growth. After the implementation, we were able to validate the intuitive aspects and understand customer voice data objectively. [Challenges and Background] - As the number of brands implementing NPS increased, the volume of data became unmanageable manually. - Initially, each person conducted analyses at their own discretion, which limited the development of analytical skills and introduced subjective judgment. - With the introduction of NPS, we believed that further VOC analysis was necessary to motivate staff involved in the business to take action with a sense of conviction. *For more details, please refer to the related links or feel free to contact us.*

• Business Intelligence and Data Analysis

We would like to introduce a case where Hakuhodo Connect, Inc., which provides one-stop support for direct marketing business as a BPO, implemented the "Visualization Engine." In operating a contact center, we wanted to return the true voices of customers to our clients. To achieve this, we believed it was necessary to capture and analyze the call audio without missing any details. After the implementation, we were able to extract keywords left by operators when they repeated information and tag them to the CU data, allowing us to identify topics and keywords. [Challenges and Background] - Although a vast amount of VOC (Voice of Customer) accumulates in the contact center, the information that operators can input as interaction history is limited. - We believed it was essential to understand customer insights in detail, even more than the clients themselves, to ensure the success of the direct marketing business for our contracted clients. *For more details, please refer to the related links or feel free to contact us.

• Business Intelligence and Data Analysis

We would like to introduce a case where JTB Corporation, which has a group of companies engaged in various businesses centered around the travel industry, has implemented the "Visualization Engine." This system was introduced with the aim of integrating and visualizing customer feedback gathered from multiple customer touchpoints, as well as collecting customer voices from the perspective of hypothesis exploration and verification in product and service development. By conveying VOC analysis as an easy-to-understand output, employees have been able to engage in product and service improvements with a sense of conviction that could not be achieved by simply presenting numerical data. 【Initiatives】 ■ Monthly analysis of customer feedback from multiple touchpoints, shared as VOC reports ■ Identifying priority improvement points and accumulating actions for improvement through consideration and implementation ■ Utilizing Instant Research (self-service consumer monitor survey function) to understand customer needs during product and service planning *For more details, please refer to the related links or feel free to contact us.

• Business Intelligence and Data Analysis

We would like to introduce a case where PHC Corporation implemented a "Visualization Engine" to strengthen their efforts in utilizing VOC (Voice of Customer). The company began working on building a system to effectively utilize VOC. While they recognized the importance of customer feedback, it was necessary to shape it into a form that could be operated as an organization (business unit). The richness of knowledge and the excellent sharing capabilities of the system were decisive factors in its implementation. Gradually, inquiries regarding specific items decreased, ultimately achieving the goal of "reducing inquiries." [Challenges] - There were many opinions that VOC was not being fully utilized in products and services. - Analyzing approximately 10,000 pieces of data manually took 5 people three months, and categorization was the best they could manage. - They felt the need to improve the quality of analysis while leveraging the perspectives of the business unit. *For more details, please refer to the related links or feel free to contact us.*

• Business Intelligence and Data Analysis

We would like to introduce the case study of the implementation of the "Visualization Engine" by Book Off Corporation, which operates approximately 800 reuse shops nationwide. With over 20,000 VOCs collected in peak months, the tool was essential for both improving the efficiency of analysis and enhancing its quality. The decision to implement this system was based on its rich variety of analysis types, high flexibility for cross-analysis, and the clarity of trend changes. It has made it easier to identify issues, difficulties, and customer needs, leading to improvement measures. [Challenges and Background] - Monthly reports were conducted amidst the operation of the customer center. Due to a lack of resources, it took about a week each month just for aggregation and reporting. - Manual aggregation was the limit, preventing the allocation of time to the analyses and proposals that should have been prioritized, resulting in a decrease in the quality of analysis and the number of proposals. - As the number of customers using both in-store and online services increased, there was a demand for integrated data analysis to achieve seamless customer understanding. *For more details, please refer to the related links or feel free to contact us.*

• Business Intelligence and Data Analysis

We would like to introduce the high-security environment and flexible data integration capabilities of our "Visualization Engine," which is handled by a major company. By implementing hardware redundancy and a robust security system managed by our data center, we provide a higher quality ASP service. Additionally, we have implemented security measures for both hardware and software to prevent unauthorized access. 【Main Security Measures (System Side)】 ■Application ・Cross-Site Scripting ・SQL Injection ■System ・Firewall ・SSL Communication, Port Blocking, Port Monitoring *For more details, please download the PDF or feel free to contact us.

• Software (middle, driver, security, etc.)

We would like to introduce the overwhelming high-speed functionality development and consulting system of our "Visualization Engine." We have prepared various points of contact and content tailored to your goals and style. We will also participate in internal feedback sessions regarding the results produced, conduct interviews to identify areas for improvement, clarify any uncertainties, and hold study sessions aimed at expanding operations. 【Points of Contact / Content】 ■ FAQ Site ■ Mastery Sessions & Follow-up Study Groups ■ Zoom Space "Zoom Lab!" ■ Support Desk *For more details, please download the PDF or feel free to contact us.

• Software (middle, driver, security, etc.)

The "Visualization Engine" is a platform that supports effective utilization of "customer feedback" tailored to a wide range of purposes. It establishes a system to deliver voices throughout the entire organization as a platform for utilizing customer feedback. It captures the (raw) voices of suspicion, dissatisfaction, and anxiety regarding products, brands, and the company in real-time, as well as the budding risks and sudden surges in situations. [Objectives of Utilizing Customer Feedback] ■ Understanding trends ■ Generating new ideas ■ Evaluating customer experience and promotional measures ■ Improving products and services ■ Risk analysis and crisis management *For more details, please download the PDF or feel free to contact us.

• Software (middle, driver, security, etc.)

Our "Visualization Engine" is a top-level text mining tool that has been adopted by 1,800 companies. At Mizuho Bank, which has implemented our tool, we visualize the content and number of positive and negative feedback regarding products and services, as well as the reactions on social media to specific events. By utilizing features such as posting insights and suggestions based on feedback, we have revitalized communication between management, headquarters, and sales branches, strengthening the overall use of VoC within the organization. 【Implementation Results】 ■ Manufacturing/Manufacturers ■ Retail/Distribution ■ Transportation/Real Estate/Infrastructure ■ Finance/Banks ■ IT/Telecommunications/E-commerce ■ Pharmaceuticals/Medical ■ Other Services *For more details, please download the PDF or feel free to contact us.

• Software (middle, driver, security, etc.)

The "Visualization Engine" is a data utilization VOC platform that uses text mining technology and generative AI. The data sources include various social media and reviews, starting with X. A specialized team continuously implements updates to align with changes in Japanese expressions. Additionally, a variety of analytical functions are standardly equipped to meet diverse needs. 【Analytical Functions (Excerpt)】 ■ Ranking (Words/Dependencies) ■ Comparison Mapping ■ Response Analysis ■ Surge Words ■ Word Cloud *For more details, please download the PDF or feel free to contact us.

• Software (middle, driver, security, etc.)

The "Visualization Engine" is a platform for utilizing customer feedback that supports enterprises and large companies. It shares fresh customer satisfaction data daily and weekly with all executives and employees, and establishes a system to verify the effectiveness of measures based on the field through newly created meetings involving frontline departments, constantly validating the discrepancies between analytical data and the on-the-ground feel. Through thorough customer satisfaction promotion activities via "visualization," we have made customer satisfaction issues visible and achieved innovation in a customer-centric management system. 【Features】 1. Acquires a wide range of data sources, enabling specialized analysis 2. Visualizes data in an easy-to-understand manner with an intuitive UI 3. High-precision natural language processing technology that captures the true feelings of customers *For more details, please download the PDF or feel free to contact us.

• Software (middle, driver, security, etc.)

This document introduces how to create a "skill map" that can be utilized for human resource development. A skill map is a list that outlines the skill levels related to the current job responsibilities of employees. By objectively evaluating employees' abilities, it becomes easier to achieve planned human resource development and placement. This document provides a comprehensive explanation of the basics of skill maps, the steps for creating them, and templates. We encourage you to read it. [Contents] ■ What is a skill map? ■ Steps for creating a skill map ■ Templates to assist in creating a skill map ■ Skill maps that can be created with Talent Palette ■ Can also be used for competency evaluation (ISO 9001) ■ For skill management, use "Talent Palette" *For more details, please download the PDF or feel free to contact us.

• Workflow System

This document introduces how to create a "skill map" that can be utilized for human resource development. A skill map is a list that outlines the skill levels related to employees' current job responsibilities. By objectively evaluating employees' abilities, it becomes easier to achieve planned human resource development and placement. This document provides a comprehensive explanation of the basics of skill maps, the steps for creating them, and templates. We encourage you to read it. [Contents] ■ What is a skill map? ■ Steps for creating a skill map ■ Templates to assist in creating a skill map ■ Skill maps that can be created with Talent Palette ■ Can also be used for competency evaluation (ISO 9001) ■ For skill management, use "Talent Palette" *For more details, please download the PDF or feel free to contact us.

• Workflow System

The all-in-one talent management system "Talent Palette" provides essential functions for HR. "Talent Palette" is the number one talent management system with a proven track record among major companies. It realizes recruitment, development, placement, retention, and management decision support on a single platform. It practices a "scientific HR strategy" that incorporates a marketing perspective into HR. By centralizing and accumulating all human resource data, it supports data-driven scientific HR strategies with rich features, from placement and development to recruitment and improving employee satisfaction. *Source: Deloitte Tohmatsu Mic Research Institute, "HRTech Cloud Market Status and Outlook 2022 Edition - Revenue of HR and Placement Cloud Vendors by User Scale (Fiscal Year 2022)."

• Personnel and Labor