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A gym boosted conversions by extending its no-fee offer via automated follow-up emails.

1. Issue: Insufficient Outreach to Potential Members

A membership-based gym chain with 30 locations across the country offers prospective members a trial program before they decide whether to sign up.While the studio gauges interest after the trial, few individuals sign up immediately. This has highlighted a need to boost their conversion rates.

To address this, the Kyoto branch independently launched a “No Enrollment Fee Campaign”. This initiative waived the enrollment fee for anyone who joined within seven days of their trial. The campaign successfully increased the branch’s membership conversion rate by 1.5 times compared to before its implementation.

However, a new challenge has emerged: this campaign doesn’t effectively reach potential members who don’t sign up within the initial seven-day window.

2. Solution: Automated Email for Extended Campaign Offers

First-First Fitness Studio’s Kyoto branch is supercharging its “No Enrollment Fee Campaign” to better engage potential members. They’ll launch a special email campaign targeting individuals who didn’t sign up immediately after their trial. This email will announce a seven-day extension of the “No Enrollment Fee” offer, giving them another chance to reconsider joining.

To make this happen, the process owner will revamp the workflow system. It’ll automatically dispatch the “Campaign Extension Email” seven days after a free trial if the prospective member hasn’t yet enrolled.

The plan boosts conversions by extending the “No Enrollment Fee” offer, giving trial members a second chance to join.

Before

View details of the workflow diagram

• 3.Membership Confirmation
  • We’ll confirm your enrollment after the trial on the same day
• 4.Enter Keyword (for Pending Membership)
  • The assigned trainer will input three keywords gathered from the prospective member
• The AI will generate a thank-you message
• 5.Content Confirmation
  • The receptionist will review the generated text and make minor adjustments to the phrasing
• A thank-you email containing feedback from the assigned trainer will be sent to the prospective member
• 6.Later Enrollment
  • We’ll process the membership application if the candidate wishes to join at a later date. This option automatically expires if 7 days pass from the trial date.
• 7.Feedback
  • The trainer who provided the free trial will check the membership outcome and enter their reflections

After

View details of the workflow diagram

• 3.Membership Confirmation
  • We’ll confirm your enrollment after the trial on the same day
• 4.Enter Keyword (for Pending Membership)
  • The assigned trainer will input three keywords gathered from the prospective member
• The AI will generate a thank-you message
• 5.Content Confirmation
  • The receptionist will review the generated text and make minor adjustments to the phrasing
• A thank-you email containing feedback from the assigned trainer will be sent to the prospective member
• 6.Later Enrollment
  • We’ll process the membership application if the candidate wishes to join at a later date. This option automatically expires if 7 days pass from the trial date.
• Send campaign extension email
  • If 7 days have passed since the trial date, an email will be sent
• 7.Final Judgment
  • After the extension email is sent, we’ll process the membership if there’s an enrollment request
• 8.Feedback
  • The trainer who provided the free trial will check the membership outcome and enter their reflections

3. Customers Case Study

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Surging orders overwhelmed rotating staff, so tasks are auto-reassigned after two hours to prevent delays.

1. Issue: Shipping Delays Due to Overwhelmed Staff

A traditional inn, known for its exceptional cuisine and prime location near major tourist attractions, is now facing a new challenge. The recent launch of their signature hot pot soup in vacuum-sealed frozen packs has been a huge success, leading to a surge in orders via phone, fax, and their website.

While their current system attempts to balance the workload by rotating shipping assignments among the team, the sheer volume of new orders means that assigned staff are frequently overwhelmed, causing significant backlogs.

2. Solution: Automated Task Handoffs Based on Staff Availability

The process owner implemented a system that automatically reassigns shipping tasks to the next available staff member, if the initially assigned person can’t complete the work within two hours. This ensures that tasks are handed off proactively before delays occur, as assignments are rotated sequentially within the shipping team.

Automatically reassigning handlers prevents backlogs and ensures on-time shipping.

Before

View details of the workflow diagram

1. Order Information Entry (Manual)

The team manually inputs customer order information.

2. Primary Shipping Task (Main Handler)

The main shipping handler carries out the shipping tasks. Once complete, a shipping confirmation email is sent.

x1. Subject Line Configuration

The workflow system sets the subject line for communications, including the order ID and order date.

x2. Primary Handler Assignment

The workflow system designates the main shipping handler by rotating assignments among the shipping team.

After

View details of the workflow diagram

1. Order Information Entry (Manual)

Staff members manually input order information.

2. Shipping Task (Primary Handler)

The primary shipping handler performs the shipping tasks. A shipping confirmation email is sent upon completion.

2′. Shipping Task (Secondary Handler)

The secondary shipping handler performs the shipping tasks. A shipping confirmation email is sent upon completion.

x1. Subject Line Setting

The workflow platform sets the subject line with the order ID and order date.

x2. Primary Handler Assignment

The workflow platform designates the primary shipping handler from the shipping team on a rotating basis.

x3. Exclude Primary Handler from Candidates

The workflow platform adds a rule to exclude the primary handler from further assignment considerations.

x4. Secondary Handler Assignment

The workflow platform designates a secondary handler, excluding the primary shipping handler.

3. Customers Case Study

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AI automates thank-you messages, reducing staff workload and improving efficiency.

1. Issue: The Effort of Writing Thank You Notes for Visitors

A membership-based gym chain with 30 locations across Japan offers a successful free trial program that significantly contributes to new member acquisition. While member management is centralized, each branch handles free trial registration and management independently.

The Kyoto branch has implemented a unique workflow system that includes a web form for trial sign-ups and automated booking confirmation emails. After a free trial, reception staff ask visitors about their interest in joining. However, many attendees don’t commit on the spot and prefer to decide later. This makes sending a prompt thank you email crucial to keep their interest high.

It’s been observed that sending a personalized thank you email, including a message from the assigned trainer, on the same day as the trial has significantly improved visitor impression and led to an average 5% increase in membership conversion rates. The thank you email sending function is also integrated into the workflow system.

Despite its proven effectiveness, the current process of trainers individually crafting these thank you messages is time-consuming and labor-intensive, leading to increased overtime hours. Furthermore, this task presents a significant psychological burden for trainers who struggle with writing. Therefore, efficiency is urgently needed to maintain the positive impact on conversion rates without overworking staff.

2. Solution: Automating Thank You Message Generation with AI

The process owner will revamp the workflow to enable automatic thank you message generation using AI (ChatGPT).

Based on these inputs, the AI will automatically generate the thank you message. This change eliminates the need for trainers to compose messages themselves.

Automating thank-you messages reduces workload and stress for trainers, improving productivity and overall business efficiency.

Before

View details of the workflow diagram

3.Membership Confirmation

We’ll confirm your membership after your trial session concludes today.

4.Post-Trial Thank You (If Membership is Pending)

The assigned trainer will enter feedback for the trial participant, limited to approximately 100 characters.

A thank-you email containing feedback from your assigned trainer will be sent to all visitors.

5.Delayed Membership Enrollment

Should a visitor express a desire to join at a later date, we’ll process their membership enrollment. (This option will automatically expire after a set period.)

Post-Trial Review

Trainers who provided the free trial will check the membership outcome (whether the visitor joined or not) and enter their reflections.

After

View details of the workflow diagram

3.Membership Confirmation

We’ll confirm your membership after your trial session concludes today.

Keyword Entry (If Membership is Pending)

The assigned trainer will enter three keywords gathered from the visitor during the consultation.

AI will generate the thank-you message.

Review Message

The reception staff will review the generated message and make minor wording adjustments.

A thank-you email containing feedback from your assigned trainer will be sent to all visitors.

5.Delayed Membership Enrollment

Should a visitor express a desire to join at a later date, we’ll process their membership enrollment. (This option will automatically expire after a set period.)

Post-Trial Review

Trainers who provided the free trial will check the membership outcome (whether the visitor joined or not) and enter their reflections.

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Automating risk workflows ensures all high-risk cases are addressed promptly, reducing missed actions and accelerating response times.

1. Issue: Slow Initial Responses

In a cloud-based company, every employee can keep track of each client’s usage. Specifically, the Usage Aggregation Process workflow app automatically posts usage graphs (Looker Studio reports) for each client to the internal chat tool, Collab Chat. On top of that, each graph comes with an account cancellation risk assessment generated by AI.

The Customer Success team manually initiates the Risk Action Process (risk response workflow) when risk mitigation is needed. However, with the recent increase in the number of clients, there have been instances where the Risk Action Process is not being initiated. The root cause of this is that team members are unsure how to make a decision. For example, time can pass while they consider that maybe no risk mitigation is necessary if they feel that there was a similar risk in the past.

2. Solution: Initiate Countermeasures Immediately Upon High-Risk Identification

The process owner changed their approach to initial risk response measures.

The new rule is to initiate the Risk Action Process for all high-risk assessments, meaning risk countermeasures will be considered within the Risk Action Process. Even if a risk was previously addressed or is currently being handled, any usage graph data (client data) determined to be high-risk will now be passed to the Risk Action Process. Within this process, the risk control policy will then be decided.

Specifically, an automated step to launch the Risk Action Process was added downstream in the workflow diagram.

This process improvement ensures that all client data identified as high-risk by either the AI-generated system or human assessment is automatically passed to the Risk Action Process. Additionally, a new option, “5. Previously Addressed / Currently Being Handled”, was added to the Risk Control Policy management item within the downstream Risk Action Process.

• 1. Risk Avoidance
• 2. Risk Reduction
• 3. Risk Sharing
• 4. Risk Retention
• 5. Previously Addressed / Currently Being Handled

Automated risk processes eliminate missed cases and enable faster responses to cancellation risks.

Before

After

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AI now auto-assigns responders to inquiry emails, reducing workload and improving efficiency.

1. Issue: Selecting Call Handlers is Time-consuming

There is a company that offers a wide range of office essentials, including copiers and printers.The company utilizes a Representative Phone Answering Service where professional external operators handle phone calls as if they were in-house employees. They then report the call’s content via email. This service ensures a courteous initial response that only professionals can provide.

Recently, an AI-generated system was integrated into their call answering operations to automatically classify the priority of these report emails. This new system automatically notifies the management department when a report email requiring urgent attention arrives, thereby reducing the risk of delays in responding to inquiries.

Upon receiving these notifications, the Management Department assigns responders based on the priority of the report emails, starting with the most urgent. However, they ultimately need to allocate responders for all inquiry resolution emails, which results in a significant workload.

Currently, we’re managing within our capacity. However, we anticipate an increase in projects due to business expansion, which raises concerns about an even heavier workload. If this burden continues to grow, it risks interfering with other crucial operations.

While the current workload is manageable, the company anticipates an increase in cases due to business expansion, raising concerns about an even greater burden. If this burden continues to grow, there’s a risk it could disrupt other critical operations.

2. Solution: Automating Responder Selection with AI

To address these issues, the process owner integrated an AI-generated system into their workflow to automatically assign responders. Specifically, the AI analyzes the content of report emails and selects the most suitable responder from a prepared list. Following this, the selected responder is automatically set as the processor for the Record Response Outcome step.

This new system automates the entire process, from the arrival of an operator’s email regarding an important call to the assignment of the Record Response Outcome step to an internal team member. As a result, the management department no longer needs to manually select responders for critical calls, minimizing the impact on other operations as the business expands. Ultimately, this enables efficient and low-burden operations.

Automating responder selection reduces manual work for management, allowing them to focus on more important tasks.

Before

View details of the workflow diagram

x1. Retrieve Email Content

When an email with the label “Phone” arrives in Gmail, its content is read.

x2. Urgency Assessment by AI

The AI analyzes the email content to determine if it’s a sales solicitation. The result is then assigned to the data field “Judgment Result”, if it’s a sales pitch, it’s set to “not important”; otherwise, it’s set to “important.”

g1. AI Judgment Result

The workflow path is selected based on the value in the Judgment Result data field, as follows:

• If the Judgment Result is “not important,” the workflow proceeds to the “1. Assign Responder” step.
• If the Judgment Result is “important,” the workflow proceeds to the “m1. Urgent Action Request” email sending event (which is technically referred to as a Throwing Message Intermediate Event).

m1. Urgent Action Request

An email is sent to the management department members, prompting them to accept and process the “1. Assign Responder” step.

1. Assign Responder

A member of the management department determines the “responder” based on the email’s content.

2. Record Response Outcome

The assigned responder reviews the email content and records how the inquiry was handled.

After

View details of the workflow diagram

x1. Retrieve Email Content

When an email with the label “Phone” arrives in Gmail, its content is read.

x2. Urgency Assessment by AI

The AI analyzes the email content to determine if it’s a sales solicitation. The result is then assigned to the data field “Judgment Result”, if it’s a sales pitch, it’s set to “not important”; otherwise, it’s set to “important”.

x3. Responder Selection by AI

The AI analyzes the email content and selects the appropriate responder (their email address) from a prepared list of contacts.

x4. Setting the Responder

Based on the responder’s email address selected in the “3. Responder Selection by AI” automated process, the handler for the “2. Record Response Outcome” step is set.

g1. AI Judgment Result

The workflow path is selected based on the value in the Judgment Result data field, as follows:

• If the Judgment Result is “not important,” the workflow proceeds to the “1. Assign Responder” step.
• If the Judgment Result is “important,” the workflow proceeds to the “m1. Urgent Action Request” email sending event (which is technically referred to as a Throwing Message Intermediate Event).

m1. Urgent Action Request

An email is sent to the management department members, prompting them to accept and process the “1. Assign Responder” step.

1. Assign Responder

A member of the management department determines the “responder” based on the email’s content.

2. Record Response Outcome

The assigned responder reviews the email content and records how the inquiry was handled.

3. Customers Case Study

Honda Motor Co., Ltd.

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AI filters inquiry emails, separating spam from real leads for faster response.

1. Issue: Delayed Response to Inquiries

A comprehensive provider of office essentials such as copiers and printers has significantly streamlined its inquiry management process. The company utilizes a representative telephone answering service, where professional external operators handle incoming calls on behalf of employees and report the contents of the calls by email. This not only reduces the burden of initial call handling for staff but also ensures a polite and professional first point of contact for callers.

Recently, the company implemented an automated system that integrates report emails from the answering service directly into its workflow system.This crucial enhancement plays a vital role in preventing missed inquiries and ensures that all communications are tracked and addressed efficiently.

Despite these improvements, the company now faces a new challenge: more than half of the automatically imported report emails are sales solicitations. This creates a significant problem where genuine inquiries from potential customers get buried amidst the spam.

As a direct result, the company is unable to respond promptly to valuable leads, leading to a serious risk of missing out on crucial business opportunities.

2. Solution: AI-Powered Urgency Assessment

The process owner has successfully integrated an AI-powered automatic classification system into their workflow for handling report emails.

Specifically, as soon as a report email enters the workflow system, an automated AI step analyzes its content and classifies it as either a sales solicitation or not. Based on this classification, the processing path automatically diverges.

With this setup, “report emails” identified as sales solicitations are categorized as not important. Conversely, all other emails are classified as important. Furthermore, whenever an email is classified as important, a notification email is automatically sent to the relevant administrative department, prompting their immediate attention.

Before

View details of the workflow diagram

x1. Retrieve Email Content

When an email with the label “Phone” arrives in Gmail, its content is read.

1. Assign Responder

A member of the management department determines the “responder” based on the email’s content.

2. Record Response Outcome

The assigned responder reviews the email content and records how the inquiry was handled.

After

View details of the workflow diagram

x1. Retrieve Email Content

When an email with the label “Phone” arrives in Gmail, its content is read.

x2. Urgency Assessment by AI

The AI analyzes the email content to determine if it’s a sales solicitation. The result is then assigned to the data field “Judgment Result”, if it’s a sales pitch, it’s set to “not important”; otherwise, it’s set to “important.”

g1. AI Judgment Result

The workflow path is selected based on the value in the Judgment Result data field, as follows:

• If the Judgment Result is “not important”, the workflow proceeds to the “1. Assign Responder” step
• If the Judgment Result is “important,” the workflow proceeds to the “m1. Urgent Action Request” email sending event (which is technically referred to as a Throwing Message Intermediate Event).

m1. Urgent Action Request

An email is sent to the management department members, prompting them to accept and process the “1. Assign Responder” step.

1. Assign Responder

A member of the management department determines the responder based on the email’s content.

2. Record Response Outcome

The assigned responder reviews the email content and records how the inquiry was handled.

3. Customers Case Study

Honda Motor Co., Ltd.

Used for Company-wide Approval Flows such as general affairs applications, training recepti…

View More

Toho Gas Network Co., Ltd. (Negotiation and Design Section)

500 Applications Per Month Completely Digitized! Reduced Labour and Eliminated Printing and…

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MITSUBISHI PENCIL CO., LTD.

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We will enable AI-based reviews for the following tasks:

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