homula List of Products and Services

The MCP Server (Model Control Protocol Server) integrates business systems, SaaS, and databases scattered throughout the company, creating a common platform that can be safely and flexibly utilized by AI and automation tools. Its greatest feature is the ability to centrally manage and connect multiple internal data sources and standardize them into a format that can be handled by AI and n8n. This integration significantly reduces the development effort required for new integration implementations and AI adoption by consolidating API connections and processing flows that were individually developed for each department. Additionally, it standardly addresses enterprise requirements such as authentication, permissions, and logging, allowing companies with strict security policies to build an AI utilization platform in a short period. It also anticipates connections with legacy environments, enabling phased AI implementation without waiting for the renewal of existing systems, which is a significant advantage. As a result, it is utilized as a core platform to accelerate the company-wide deployment of AI and automation projects, moving away from individual requests to the information systems department and from person-dependent operational designs.

• Database

Homula Inc. offers a no-code AI agent construction support service for businesses that combines the open-source workflow automation tool "n8n," used in over 150 countries worldwide, with the AI agent platform "Agens," which is responsible for understanding and executing business tasks. Compared to Zapier and Dify, n8n excels in scalability and flexibility, allowing for no-code integration with over 500 external services. It supports integration not only with Slack and Google Workspace but also with Japanese SaaS products such as Money Forward and freee. Agens features RAG (Retrieval-Augmented Generation) and multi-agent capabilities, interpreting instructions in natural language and executing business workflows in conjunction with n8n. It integrates the intelligence and functionality of AI, enabling autonomous operation of business agents within departments. Comprehensive support is also provided, including implementation consulting, templates, training, and ongoing assistance.

• Workflow System

"LeedScope" is an innovative tool that leverages the power of generative AI to automate everything from managing inbound leads to personalized follow-ups. It synchronizes data instantly with CRM systems like HubSpot, initiating the automatic acquisition and processing of new leads. Additionally, based on the basic information entered into the CRM, AI constructs detailed profiles and reflects enriched information in the CRM in real-time. [Effects] ■ Reduced response time ■ Improved personalization ■ Optimization of sales resources ■ Ensured scalability *For more details, please download the PDF or feel free to contact us.

• Other information systems

This document provides a detailed explanation of how AI can innovate sales teams and improve efficiency. It includes the sales processes before and after the introduction of AI, as well as the benefits of utilizing AI in sales. Additionally, you can find examples of how AI is used in sales teams, such as prospecting and competitive analysis. We encourage you to read it. [Contents (partial)] ■ Sales process before AI implementation ■ Sales process after AI implementation ■ Benefits of utilizing AI in sales: Improvement in productivity and efficiency ■ Benefits of utilizing AI in sales: Enhancement of analysis and insights *For more details, please download the PDF or feel free to contact us.

• Other information systems

This guide provides a detailed explanation of how to acquire "Qualified Leads," which are essential for business growth, and how to lead them to conversion. Acquiring leads, improving their quality, and ensuring high-quality follow-up are challenges faced by many companies, but with LeedScope, these challenges can be efficiently addressed. Please take a look at the importance and types of high-quality leads. [Contents (Excerpt)] ■ What are high-quality leads? ■ Three types of high-quality leads ■ Definition of Ideal Customer Profile (ICP) ■ Enrichment of lead information ■ Establishing lead scoring criteria *For more details, please download the PDF or feel free to contact us.

• Other information systems

A CDP (Customer Data Platform) is a software application that integrates and analyzes various data related to customers through functions such as data collection, allowing for its utilization. By utilizing a CDP, personalized sales and marketing become possible, enhancing customer satisfaction. Additionally, it identifies customer segments with low acquisition costs and clarifies segments with high LTV (Lifetime Value), achieving high ROI in sales and marketing. 【Objectives of Implementing a CDP (Partial)】 ■ Improvement of LTV through enhanced customer experience ■ Reduction of customer acquisition costs ■ Increased operational efficiency ■ Product improvement ■ Appropriate management decisions *For more details, please download the PDF or feel free to contact us.

• Other information systems

This document provides a detailed explanation of the challenges of CRM data enrichment and the solutions offered by LeedScope. It highlights common issues in typical CRM setups, such as insufficient data coverage, data obsolescence, and the burden of manual tasks. Additionally, it introduces the tracking of live signals in CRM with LeedScope, management of inbound leads, and the advantages of LeedScope. [Featured Items (Excerpt)] ■ Common issues in typical CRM setups ■ Automation of unstructured research in CRM with LeedScope ■ Tracking of live signals in CRM with LeedScope ■ Management of inbound leads ■ Advantages of LeedScope *For more details, please download the PDF or feel free to contact us.

• Other information systems

This document provides a detailed explanation of a comprehensive framework for maximizing the potential of AI and effectively transitioning from Proof of Concept (PoC) to a production environment. It addresses the challenges of AI implementation, including the lack of standardized processes, the absence of appropriate tools, and the underdeveloped automated pipelines. If you are considering implementation, please take a moment to read it. 【Contents (Excerpt)】 ■ Introduction to Generative AI Implementation Support Services ■ Challenges in AI Implementation ■ Evals: Accurately Measuring LLM Performance ■ RAG (Retrieval-Augmented Generation): Effectively Integrating Advanced External Knowledge *For more details, please download the PDF or feel free to contact us.

• Other information systems

In this document, we introduce the "Generative AI PoC Support Service" provided by Homula Inc. We provide an overview of the generative AI implementation support service and explain seven detailed steps to successfully lead a proof of concept (PoC) for generative AI. We offer tailored, one-stop support, covering everything from localized consulting, data analysis, development, infrastructure implementation, to marketing operations. Please feel free to consult us first. 【Highlighted Items (Excerpt)】 ■ Understanding the essence of LLMs: The first step to success ■ Involving the entire organization: Identifying and prioritizing issues ■ Checking the data preparation status: Factors that influence the success of the PoC ■ Forming cross-functional teams: The power of diversity ■ Proper sequencing of the PoC: A strategic approach *For more details, please download the PDF or feel free to contact us.

• Other information systems

We would like to introduce a case study of the implementation of "Agens" at a provider of professional services for corporations. The implementation site faced challenges such as strict deadlines and quality requirements, as well as spending 10 hours a week on contract and proposal creation. As a result, service delivery efficiency improved by 30% through automated document generation and knowledge base integration. Document creation time was also reduced by 60%. [Challenges/Time Consumption] ■ Handling 5-7 client cases per day ■ Spending 10 hours a week on contract and proposal creation ■ Frequent reference to and application of specialized knowledge ■ Strict deadlines and quality requirements *For more details, please download the PDF or feel free to contact us.

• Other information systems

We would like to introduce a case study of the implementation of 'Agens' by a management consultant. The consultant faced challenges such as managing multiple clients simultaneously and the complexity of client-specific information management. 'Agens' was used for context understanding, automatic report generation, analysis, and integrated management of client information. Client satisfaction increased by 20%, and the quality and depth of analysis improved. [Challenges/Time Consumption] ■ Managing multiple clients simultaneously ■ Over 20 hours per week spent on report creation ■ Majority of time spent on industry research and analysis ■ Complexity in managing client-specific information *For more details, please download the PDF or feel free to contact us.

• Other information systems

We would like to introduce a case study of the implementation of "Agens" for an investment fund VC partner. Before the implementation, the challenges included tracking the latest trends across multiple industries, conducting 10-15 startup meetings per week, and the time-consuming nature of continuous high-level decision-making. After the implementation, we utilized automated research and analysis features. This allowed us to reduce research time by 15 hours per week and shorten investment decision time by 40%. [Challenges/Time Consumption] ■ 10-15 startup meetings per week ■ Analysis of vast research reports ■ Tracking the latest trends across multiple industries ■ Continuous high-level decision-making *For more details, please download the PDF or feel free to contact us.

• Other information systems

We would like to introduce a case where the AI agent platform 'Agens' was implemented for cross-functional PM/PdM. As a challenge, we were consuming time on over 20 decisions and approvals per day, as well as more than 15 hours per week on status checks. By using it for automatic tracking of project progress, we were able to reduce information gathering and organizing time by 60% and improve project efficiency by 20%. [Challenges/Time Consumption] ■ Management of multiple projects and teams ■ Over 20 decisions and approvals per day ■ More than 15 hours per week on status checks ■ Daily use of more than five tools *For more details, please download the PDF or feel free to contact us.

• Other information systems

We would like to introduce a case where 'Agens' was implemented by a high-touch customer success representative. Previously, there were challenges such as managing 40-50 customer accounts and being overwhelmed with ticket responses and problem-solving. After implementation, by using it for task automation and client relationship management, we were able to reduce response preparation time by 70% and increase the renewal rate by 25%. [Current Challenges/Time Consumption] ■ Management of 40-50 customer accounts ■ 3-4 customer meetings per day ■ Overwhelmed with ticket responses and problem-solving ■ Need to integrate product usage data with conversations *For more details, please download the PDF or feel free to contact us.

• Other information systems

We would like to introduce a case study of the implementation of the AI agent platform 'Agens' in the enterprise sales of a large corporation. The company faced challenges such as spending over an hour a day on CRM updates and having customer information dispersed across multiple tools. By using it for customer information research, they were able to reduce preparation and information gathering time by 75%. [Challenges/Time Consumption] ■ 60-100 communications per day ■ Over an hour a day for CRM updates ■ Preparation for business negotiations ■ 8 hours a week for follow-ups ■ Customer information dispersed across multiple tools *For more details, please download the PDF or feel free to contact us.

• Other information systems

We would like to introduce a case where our client, a busy middle management department head, implemented 'Agens'. Previously, they faced challenges such as 30-45 minutes of post-meeting processing for each meeting and being caught between team management and upper management reporting. By implementing the system, the post-meeting processing time was reduced by 90%, resulting in the creation of 15-20 hours per week. [Challenges/Time Consumption] ■ 6-8 meetings per day leading to information overload ■ 30-45 minutes of post-meeting processing for each meeting ■ 30-40 follow-up tasks per week ■ Being caught between team management and upper management reporting *For more details, please download the PDF or feel free to contact us.

• Other information systems

Agens is an AI agent platform that alleviates the task-related stress arising from business communication. It understands the context of various communication channels such as meetings, emails, and chats, automatically extracting and executing tasks and to-dos that arise. Meeting minutes are automatically generated, and to-dos such as sending promised materials or conducting research are immediately extracted, with the AI agent autonomously executing these tasks. By referencing past communication history with clients and the internal knowledge base, it can instantly generate high-quality outputs and respond smoothly to clients and colleagues. Agens is not just a chatbot; it functions as an "excellent subordinate" that executes tasks on your behalf. Through autonomous agent technology, it collaborates with internal and external knowledge bases and workflows, providing appropriate outputs while understanding the business context.

• project management

This is a case study of a food processing manufacturer that implemented AI-driven sales coaching to improve sales skills and increase closing rates. Challenges: Many sales representatives had limited experience, leading to issues with closing deals. There was no standardization of sales skills, and sharing of successful patterns was lacking. There was a shortage of managerial guidance resources, making effective training difficult. Measures: Implementation of an AI coaching system: Analyzing sales meeting audio to learn excellent sales pitches. Automation of feedback: AI provides real-time suggestions for improving sales pitches. Creation of skill reports: Visualizing strengths and weaknesses for each sales representative to provide appropriate training. Results: Improvement in sales pitches led to a 30% increase in closing rates. The labor required for sales training was reduced by 50%, creating an environment where even newcomers could achieve results in a short period. Utilizing AI feedback improved the accuracy of the sales meeting process.

• SFA/Sales Support System

A case study of improving the contract rate through the optimization of sales talks using AI at a medical device manufacturer. Challenges: Sales representatives had different approaches to negotiations, resulting in variability in contract rates. They were unable to make appropriate proposals based on customer needs, leading to delays in the progress of negotiations. The utilization of sales data was insufficient, and successful patterns were not shared within the team. Measures: Introduction of an AI sales support tool: Analyzes negotiation data and suggests high-conversion sales talks. Real-time proposal support: AI provides optimal responses and closing talks during negotiations. Analysis of negotiation data: AI identifies high-conversion sales processes and shares them with the entire sales team. Results: The contract rate improved by 25%, stabilizing the sales win rate. With AI proposal support, the speed of negotiation progress increased by 30%. Even new sales representatives achieved high contract rates, reducing training costs.

• SFA/Sales Support System

This is a case study of a metal processing manufacturer that implemented an AI voice bot to automate telephone inquiries and improve the number of business negotiations generated. Challenges: There were many phone inquiries regarding quotation requests and product specifications, increasing the burden on sales representatives. The management of call response history was done manually, leading to insufficient accumulation and utilization of lead information. The appointment acquisition rate was low, and the inefficiency of phone responses resulted in lost business opportunities. Measures: Implementation of an AI voice bot: The inquiry content is automatically classified, and inquiries that can be handled by FAQs are processed by AI. CRM integration: The AI transcribes call content and automatically manages lead information. Creation of business opportunities: The voice bot conducts pre-screening for appointment acquisition. Results: Approximately 65% of phone responses were automated, optimizing sales resources. Strengthened lead management through AI support resulted in a 35% increase in the number of business negotiations. The conversion rate of inquiry leads via phone improved by 20%.

• SFA/Sales Support System

A case study of a chemical manufacturer that improved its deal conversion rate through the automation of lead management using AI. Challenges: The number of BtoB inquiries was increasing, but the speed of sales responses was slow, leading to a high number of leads being lost to competitors. The diverse applications of the products made it difficult for sales to quickly identify the appropriate targets. It was challenging to respond immediately to all leads, resulting in missed opportunities for high-potential leads. Measures: Implementation of an AI lead management system: AI automatically replies immediately after inquiries and organizes lead information in real-time. Lead scoring: AI analyzes behavioral data to automatically extract cases that sales should prioritize. CRM integration: High-conversion leads are identified in real-time and notifications are sent to sales representatives. Results: Lead response speed improved by 70%, preventing loss to competitors. The deal conversion rate for inquiry leads increased by 45%. The efficiency of sales responses led to a 30% increase in the success rate of lead follow-ups.

• SFA/Sales Support System

This is a case study in which an automotive parts manufacturer utilized an AI sales agent to maximize business opportunities and improve sales efficiency. Challenges: Although there were many inquiry leads, follow-ups were delayed due to a lack of sales resources. Sales teams were unable to prioritize leads effectively, resulting in missed opportunities with high closing probabilities. Preparation for proposals took too much time, preventing sales representatives from focusing on effective closing. Measures: Introduction of AI sales agent: The AI analyzes the behavior history and interests of leads to extract those with a high potential for business negotiations. Automation of follow-ups: The AI conducts appropriate follow-ups for each lead, improving the rate of guiding them to negotiations. Optimization of sales proposals: The AI learns closing patterns and recommends the most suitable proposal content for each customer to the sales team. Results: The negotiation conversion rate improved by 40%, leading to an increase in the number of contracts. The follow-up burden on sales was reduced by 50%, enabling a more strategic approach. The appointment acquisition rate increased by 30%, creating an environment where the team could focus on high-probability deals.

• SFA/Sales Support System

This is a case study of an electronic components manufacturer that improved the conversion rate (CVR) of its website and increased lead acquisition through AI-driven content personalization. Challenges: The variety of products made it difficult to provide appropriate information for each visitor, resulting in a high bounce rate. The content design was uniform, and there was no approach tailored to the interests of leads. User behavior data was not being utilized, leading to suboptimal content delivery. Measures: AI-driven content optimization: Analyzed visitors' browsing history and behavior data to automatically display content tailored to their interests. Personalized landing pages: Displayed different product appeals for each visitor based on their past search history and visited pages. Automated A/B testing optimization: AI analyzed high CVR patterns in real-time and selected the optimal page structure. Results: The website's CVR improved by 50%, leading to an increase in inquiries. The bounce rate decreased by 30%, enhancing lead engagement. The cost per lead acquisition was reduced by 20% due to the personalization features.

• SFA/Sales Support System

This is a case study of a parts manufacturer that improved targeting accuracy and lead acquisition efficiency through AI-driven advertising optimization. Challenges: There were many leads from advertisements, but the probability of them leading to business negotiations was low. Previous advertising operation data was not utilized, resulting in unnecessary advertising budget expenditures. Advertisements were not reaching the appropriate target audience, leading to inconsistencies in the quality of inquiries. Measures: Introduction of AI advertising operations: Analyzed past lead data to identify the target audience with the highest conversion rates. Optimization of creatives: AI automatically analyzed the performance of advertisements and made automatic changes to creatives with high CTR (click-through rates). Automatic adjustment of ad distribution: Ads were delivered only to the most effective targets based on time, region, and device. Results: The conversion rate of advertisements improved by 40%, and the cost per lead decreased. The ratio of leads that led to business negotiations increased by 50%, improving the cost-effectiveness of advertisements. Through AI-driven operational optimization, advertising budgets were reduced by 25% while maximizing results.

• SFA/Sales Support System

This is a case study of a machinery manufacturer that utilized an AI marketing agent to automate lead nurturing and improve sales efficiency. Challenges: There were many leads acquired through exhibitions and the website, but prioritization for follow-up was not established. Leads that did not progress to negotiations were often neglected, resulting in poor efficiency in lead utilization. Sales teams were unable to grasp the interest level of each lead, frequently missing the timing for negotiations. Measures: Introduction of an AI marketing agent: Analyzes lead behavior data and automatically conducts nurturing based on interests and concerns. Scoring function: The AI evaluates the interest level of leads and automatically notifies sales of leads with a high likelihood of negotiation. Personalized email distribution: Provides optimal content based on the lead's behavior history. Results: The negotiation rate of leads improved by 35%, enhancing the efficiency of sales approaches. Automation of nurturing reduced the follow-up workload for sales by 50%. Sales teams were able to approach leads at the appropriate timing, resulting in a 20% increase in the closing rate.

• SFA/Sales Support System

This is a case where an electronic components manufacturer implemented an AI-powered document search system to improve the speed of information retrieval for sales, thereby enhancing proposal capabilities and closing rates. Challenges: The volume of product specifications and technical documents was vast, causing sales representatives to spend a lot of time searching for necessary information. Knowledge from past proposal documents and similar cases was not shared among sales, leading to inefficient use of information during negotiations. Measures: Implementation of an AI document search system: AI automatically classifies proposal documents and technical manuals, creating an environment where sales can search instantly. CRM integration: Records the history of documents searched by sales, improving proposal accuracy for each case. Results: The time taken for sales to retrieve information was reduced by 60%, allowing negotiations to progress smoothly. Proposal accuracy improved, resulting in a 25% increase in closing rates.

• SFA/Sales Support System

This is a case study of a precision parts manufacturer that implemented an AI FAQ system to reduce the burden of technical support operations and optimize inquiry responses. Challenges: Frequent specialized inquiries regarding product technical specifications and application ranges increased the workload for technical staff. The existing FAQ was not organized, making it difficult for customers to quickly find the information they needed. Measures: Implementation of an AI FAQ system: Built a self-service FAQ system by learning from past inquiry data. CRM integration: Established a system to record FAQ viewing history, allowing sales to prioritize responses to highly interested leads. Results: The number of views on the FAQ page tripled, and the self-resolution rate before inquiries improved by 50%. The burden on technical support was reduced by 40%, allowing for better resource allocation to sales follow-up.

• SFA/Sales Support System

This is an example of a case where an industrial machinery manufacturer implemented an AI chatbot to automate inquiry responses and improve sales efficiency. Challenges: There were many inquiries regarding product specifications and customizations, increasing the burden on sales and technical staff. Repeated inquiries were common, causing a strain on human resources and delaying the handling of new leads. The handover to sales representatives was done manually, resulting in slow response times. Measures: AI Chatbot Implementation: Utilizing an AI trained on product manuals and FAQs to handle basic inquiries 24/7. CRM Integration: Recording inquiry details in real-time and automatically transferring high-quality leads to sales. Results: 70% of inquiry responses were automated, reducing the burden on sales and technical staff. The speed of lead handling improved, resulting in a 40% increase in the conversion rate to business negotiations.

• SFA/Sales Support System

This is a case study of supporting a precision machinery manufacturer in strengthening lead acquisition through SEO and optimizing information dissemination through no-code solutions. Challenges Due to the high specialization of the products, it was difficult for information to reach the appropriate target audience. There was a desire to increase technical content, but the internal environment for editing was not established. Compared to competitor sites, there was a lack of information online, making it hard to generate inquiries. Measures SEO content enhancement: Researched high-volume technical keywords and created blogs and white papers. No-code CMS implementation: Established a system that allows internal technical staff to directly edit and publish content. LP creation: Developed a technical explanation page with SEO in mind to increase search traffic. MA measures: Collected lead information through downloadable materials and automated nurturing. Results The number of leads acquired through the technical blog increased by 3.2 times. The speed of content updates improved by 5 times due to no-code implementation. Lead nurturing measures after inquiries increased the conversion rate to business negotiations by 40%.

• SFA/Sales Support System

This is a case study of a semiconductor manufacturer that utilized no-code editing to improve the efficiency of product information updates and optimize SEO. Challenges: Updating the product catalog took a long time, leading to delays in the release of new product information. The differences between competing products were unclear on the website, making it difficult to generate inquiries. There was little traffic from search engines, making it challenging to acquire new leads. Measures: No-code CMS implementation: Established an environment where marketing personnel can easily update product pages. SEO measures: Added content that explains the features of each product in detail to enhance search traffic. LP creation: Developed a landing page that includes competitive comparison content to improve inquiry rates. CRM utilization: Scored leads based on their interests and optimized the prioritization of sales responses. Results: The speed of website page updates improved by four times, allowing for smoother release of new products. The number of inquiries from organic search increased by two times. The bounce rate of the product comparison page decreased by 25%, improving lead engagement.

• SFA/Sales Support System

This is a case study of an industrial machinery manufacturer that achieved an increase in traffic through the use of SEO and improved efficiency in website updates through no-code editing. Challenges: The website's search ranking was low, and the influx of new leads was stagnating. Updates to product specifications and case studies could not be done in-house, leading to costs and time spent on external vendors. There were delays in responding to inquiries, causing leads to flow to competitors. Measures: SEO measures: Set target keywords and strengthened the technical blog and FAQ pages. No-code CMS implementation: Established an environment where staff could easily update case studies and product information. LP creation: Created landing pages focused on search traffic to increase inquiries. MA measures: Set up automated follow-up emails after inquiries to improve the conversion rate to business negotiations. Results: The website's search ranking entered the TOP 5, and organic traffic increased by 2.5 times. With no-code support, the frequency of web page updates improved by 3 times. The speed of lead response after inquiries improved, resulting in a 35% increase in the conversion rate to business negotiations.

• SFA/Sales Support System

This is a case study of strengthening web marketing using video content at a precision metal processing manufacturer. Challenges: It was difficult to convey complex processing techniques through text alone, resulting in few inquiries via the web. To differentiate from competitors, it was necessary to more clearly highlight the company's strengths. Strengthening relationships with existing customers was a challenge. Measures: LP creation: Created a landing page (LP) incorporating videos of processing techniques to appeal visually. CMS implementation: Established a system to regularly add video content. CRM utilization: Scored interest levels based on video viewing history to optimize sales responses. MA measures: Automatically sent follow-up emails after video viewing to encourage inquiries. Results: The number of inquiries via the website increased by 3.5 times. The conversion rate of video viewers to business negotiations improved by 50%. The reorder rate of existing customers increased by 20%.

• SFA/Sales Support System

This is a case study of supporting the optimization of product customization proposals and the efficiency of the sales process at a construction machinery manufacturer. Challenges: Due to the need for customization for each customer, organizing inquiry details was complicated. The burden on sales representatives was significant, leading to delays in response speed. While there were inquiries from the website, it was difficult to convert them into business discussions due to unclear specific needs. Measures: LP creation: Published usage-specific and customization examples to clarify how to utilize the products. CMS implementation: Optimized the inquiry form to collect detailed information in advance. CRM utilization: Automatically classified inquiry data and assigned it to the most suitable sales representative. MA measures: Automated follow-up emails to potential customers to maintain interest. Results: The conversion rate to business discussions after inquiries increased by 2.2 times. The response time for sales was reduced by 30%. The success rate of customization proposals improved by 25%.

• SFA/Sales Support System

This is a case study of supporting lead acquisition and business negotiations using technical documents for a manufacturer that develops and manufactures industrial sensors. Challenges: Due to the need for advanced technical information for the products, simple materials lacked persuasive power. Sales representatives needed to provide technical explanations, placing a heavy burden on human resources. The product selection process was prolonged, necessitating the establishment of a follow-up system. Measures: LP creation: Created a download page for highly specialized technical documents. CMS implementation: Established technical blogs for each product to enhance SEO traffic. CRM utilization: Scored leads after downloads and classified the likelihood of business negotiations. MA measures: Conducted email marketing using technical documents to promote business negotiations. Results: The number of downloads of technical documents increased threefold. The rate of business negotiations after document downloads improved by 45%. Sales response time was reduced by 20%, allowing focus on higher-probability customers.

• SFA/Sales Support System

This is a case study of a casting manufacturer that achieved enhanced lead acquisition through the visualization of the manufacturing process and the utilization of web marketing. Challenges: Due to the nature of the products, there were many customers focused on specifications, resulting in few inquiries through the website. The request for quotes was inefficient, causing customers to drop off before progressing to negotiations. They were considering expansion into overseas markets, but there were few inquiries from local sources. Measures: LP creation: Strengthened product comparison content based on material and durability to emphasize expertise. CMS implementation: Provided digital data of the manufacturing process on the web to enhance trust. CRM utilization: Tracked customer behavior after quote requests to optimize priority responses. MA measures: Automated multilingual nurturing emails for overseas markets. Results: The number of inquiries increased by 2.1 times. Inquiries from overseas customers increased by 150%. The lead time from quote request to negotiation was shortened by 35%.

• SFA/Sales Support System

This is a case study of supporting a precision measuring instrument manufacturer in enhancing lead acquisition and deal conversion through the use of online demos. Challenges: Due to the high cost of the equipment, it was difficult to close deals without conducting a demo beforehand. Although there were many leads from exhibitions, the conversion rate to deals was low, and follow-up took a lot of time. Sales visits to distant customers incurred high costs, necessitating a more efficient approach. Measures: LP Creation: Created a dedicated landing page for online demo reservations to lower the barrier for inquiries. CMS Implementation: Published past demo results and case studies to enhance credibility. CRM Utilization: Scored the interest levels of demo participants and prioritized follow-up with customers likely to convert. MA Measures: Automated follow-up emails after demos to reduce the burden on sales efforts. Results: The number of online demo reservations increased by 2.8 times. The conversion rate of demo participants to deals improved by 40%. Sales efficiency for distant customers improved, reducing response costs by 30%.

• SFA/Sales Support System

This is an example of strengthening the follow-up system for long-term projects in an industrial robot manufacturer, promoting the conversion into business negotiations. Challenges: Due to the need for significant capital investment, the period from lead acquisition to order placement tends to be prolonged. Unable to utilize past inquiry leads, relying on acquiring new projects. Insufficient technical sales resources led to delays in project follow-up. Measures: LP Production: Created landing pages that communicate the benefits of implementation by application, appealing to leads in the consideration stage. CMS Implementation: Established an environment where technical documents and white papers can be added as needed. CRM Utilization: Built a system for continuous engagement using past lead data. MA Measures: Designed scenarios for phased information provision to inquiry leads. Results: By reviving past leads, the conversion rate to business negotiations doubled. The closing rate for long-term projects increased by 35%. Optimizing sales resources increased the number of projects that could be handled by 1.5 times.

• SFA/Sales Support System

This is a case study supporting the enhancement of web marketing and sales follow-up for a medical device manufacturer. Challenges: There was a lack of follow-up for existing customers, making it difficult to generate new projects. Product information was not appropriately displayed on the website, leading to a lack of inquiries. There was a shortage of content to increase customer purchasing motivation. Measures: LP creation: Created detailed pages for each product, emphasizing the benefits of implementation. CMS introduction: Ensured the ability to update in response to regulatory changes in medical devices. CRM utilization: Conducted nurturing based on past inquiry history. MA measures: Automated regular product information delivery using email marketing. Results: The number of inquiries doubled. The contract rate through sales agents improved by 30%. The dissemination of product update information became faster, and compliance response improved.

• SFA/Sales Support System

This is a case study on optimizing agency management and improving the use of customer data in a chemical manufacturer. Challenges: Sales were primarily conducted through agencies, making it difficult to obtain information about end-users. The follow-up status of agencies was unclear, leading to potential customers being neglected. The product lineup was extensive, and appropriate information was not reaching the right customers. Measures: Creation of landing pages by application and industry: Providing optimal information to target customers. Implementation of a CMS: Building a dedicated portal for agencies and developing sales support content. CRM integration: Centralized management of agency follow-ups, prioritizing high-conversion cases. MA measures: Automating nurturing emails for each product and scoring customer interest levels. Results: The conversion rate through agencies improved by 30%. Support inquiries from agencies were reduced by 40%. The construction of a database for end-users clarified customer insights.

• SFA/Sales Support System

This is a case study of a precision parts manufacturer that achieved the promotion of online orders and reduced the burden on sales. Challenges: It was difficult to convert inquiries into projects without direct visits from sales, resulting in few online orders. There were frequent delays in follow-ups after inquiries, leading to many cases of potential customers turning to competitors. Updating the website took a long time, causing delays in the release of new product information. Measures: Strengthening the technical blog and case study landing pages: Enhancing credibility and increasing inquiries. Implementing a CMS: Establishing a system that allows easy page updates within the company. Utilizing CRM: Visualizing the priority of sales follow-ups and focusing on high-probability leads. MA measures: Automating follow-ups for exhibition leads and designing nurturing scenarios. Results: The speed of converting inquiries into business negotiations improved threefold. The amount of orders received through the web expanded by 1.8 times. The lead time for releasing new products was shortened by 50%.

• SFA/Sales Support System

This is a case study of supporting lead management and improving the conversion rate of negotiations via the web for an industrial machinery manufacturer. Challenges The main website, which featured the product catalog, was not generating inquiries. There were numerous leads from exhibitions and Ipros, but nurturing was not being conducted. Sales resources were limited, making it impossible to respond immediately to all inquiries. Measures Dedicated landing page creation: Clearly communicated the benefits of implementation for each key product. CMS implementation: Enabled no-code updates, allowing for immediate reflection of new product information. CRM integration: Implemented automatic email sending after inquiries and prioritized management of sales follow-ups. Utilization of MA: Promoted the conversion of existing leads into negotiations through white papers and webinar initiatives. Results The number of inquiries via the landing page increased by 2.5 times. The conversion rate of negotiations improved from 8% to 22% (+175%). The workload for the sales team was reduced by 30%.

• SFA/Sales Support System

This is a "HubSpot × Website Building and Optimization" service that strengthens lead acquisition and sales support in the manufacturing industry. It automates lead management and follow-up from sources such as landing pages, Ipros, and trade shows, maximizing the number of business negotiations acquired. With expertise specialized in BtoB manufacturers, we support effective marketing strategies.

• SFA/Sales Support System

We would like to introduce a case study of a SaaS company's customer support that implemented "HubSpot." In this company, the information necessary for customer support was scattered within the organization, and employees were working across multiple tools, resulting in poor operational efficiency. Therefore, we integrated the information needed for customer support into our product to streamline operations. This led to a reduction in the human connection rate and an improvement in response speed. 【Case Overview】 ■Challenges - Information necessary for customer support was scattered within the organization - Operations were conducted across multiple tools, leading to inefficiency ■Results - Reduction in the human connection rate and improvement in response speed in customer support *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented in the customer support of a consumer goods manufacturer. The company faced the challenge of inefficient knowledge sharing in customer support. To address this, they built a knowledge database using RAG, which enabled faster information retrieval and sharing, as well as improved onboarding efficiency for new members. 【Case Overview】 ■Challenges - Inefficient knowledge sharing in customer support - Time-consuming onboarding for new members ■Results - Faster information retrieval and sharing - Improved consistency of responses *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study of a major company in the insurance industry that has implemented "generative AI." The company faced the challenge of analyzing the reasons for cancellations due to fragmented data sources. To address this, they implemented a real-time cancellation risk assessment system, achieving efficient sales follow-up and reducing the sales follow-up workload by 30%. [Case Overview] ■Challenges - Cancellation rate increased compared to the previous year - Insufficient prediction of customer behavior patterns ■Results - Reduced cancellation rate of high-risk customers by 30% - Able to detect signs of cancellation three months in advance *For more details, please refer to the related links or feel free to contact us.

• Other information systems