Practical Application of Customer 360° View (Part 2): Setting KPIs and Implementing Data-Driven Management

In the previous article, we explained in detail the seven types of information visible in the Customer 360° View and how to read the three dashboards. We covered the Individual Customer View for grasping the overall picture of each customer, the Overall Statistics View for getting a bird's-eye view of the salon's management status, and the Segment Analysis View for analyzing specific customer groups. By mastering these, you have deepened your data-based understanding of customers. However, many of you may have questions such as, "I can see the data now, but what specifically should I improve?", "Which numbers should I focus on?", or "How can I translate data analysis into actual actions?"
In this second part, we will explain how to set five key KPIs (Key Performance Indicators) important for salon management and how to translate data analysis into improvement measures, along with concrete examples. We will share practical know-how to move from "looking" at data to "using" it, and ultimately achieving management results.

What is Data-Driven Management?

Data-driven management is a management style that makes management decisions based on objective data rather than relying solely on intuition and experience.
Instead of saying "It feels like this might be better," you make decisions by saying, "Looking at the data, there is this trend, so let's implement this measure."
In traditional salon management, the manager's experience and intuition played an important role.
These were intuitive judgments such as, "This customer is probably due for a visit soon," "This menu seems popular," or "Staff utilization seems to be fine."
Of course, experience and intuition are important, but relying on them alone leads to oversights and errors in judgment.
You might not notice that customers are becoming dormant, you might be spending time on unpopular menus, or you might not realize that staff are under excessive pressure.
Data-driven management visualizes these problems with numbers.
Problems become clear in forms such as, "There are 15 dormant customers," "The reservation rate for the XX menu is only 5%," or "Staff A's utilization rate exceeds 95%."
Then, you implement specific measures for the problems, measure their effects, and run a PDCA cycle to make further improvements.
By introducing Pimo, anyone can practice this data-driven management.

5 Important KPIs for Salon Management

Now, let's look at the five important KPIs for salon management.
KPI stands for Key Performance Indicator, which is an important metric for measuring the degree of achievement of management goals.
There are countless numbers in salon management, but we will introduce five that are particularly important.

KPI 1: Number of New Customers Acquired

The number of new customers acquired is the number of customers who visited for the first time that month.
Acquiring new customers is essential for salon growth.
As for the approach to setting goals, it is common to grasp the current number of new customers and aim for a 10-20% increase compared to the previous year.
For example, if you currently have 10 new customers per month, the goal is 11-12 per month.
However, acquiring new customers costs money. This includes advertising expenses, Hot Pepper Beauty listing fees, and first-time discounts.
Measure the acquisition cost per new customer (CPA: Cost Per Acquisition) as well to check cost performance.
As a guideline, it is healthy if the acquisition cost per new customer is within 50% of the sales from the first visit.
If the first visit sales are 10,000 yen, the acquisition cost should be within 5,000 yen.

KPI 2: Repeat Rate (Return Rate)

The repeat rate is the percentage of customers who visited for the first time and then returned for a second visit or more.
It is no exaggeration to say that this is the most important KPI in salon management.
The calculation formula is "Number of people who visited for the second time or more ÷ Number of people who visited for the first time × 100".
For example, if there were 10 first-time visitors this month and 3 of them returned for a second visit or more, the repeat rate is 30%.
The average repeat rate in the beauty salon industry is said to be about 20-30%.
As a goal, first aim for the industry average of 30%, and then aim for 40% or more.
Improving the repeat rate costs less than acquiring new customers.
By deepening relationships with existing customers, you can build a stable sales foundation.

KPI 3: Average Spending per Customer

Average spending per customer is the average amount of money customers spend per visit.
There are two ways to increase sales: increase the number of visits or increase the spending per customer.
The calculation formula is "Total sales ÷ Number of visitors". For example, if monthly sales are 1.2 million yen and the number of visitors is 100, the average spending per customer is 12,000 yen.
Ways to increase average spending per customer include:
✅ Upselling to higher-tier menus
✅ Adding option menus
✅ Selling home care products
✅ Selling coupon books or courses
However, forced upselling will lower customer satisfaction.
Appropriate proposals tailored to the customer's concerns and budget are important.
By utilizing recommendation AI, you can make optimal proposals to customers.
For goal setting, grasp the current average spending per customer and aim for a 5-10% increase compared to the previous year. If it is currently 12,000 yen, the goal is 12,600 yen to 13,200 yen.

KPI 4: Customer Lifetime Value (LTV)

LTV stands for Lifetime Value, which is a predicted value of how much money one customer will spend as long as their relationship with the salon continues.
A simple calculation formula is "Average spending per customer × Annual number of visits × Average duration of relationship".
For example, if the average spending per customer is 12,000 yen, the annual number of visits is 6, and the average duration is 3 years, the LTV is 216,000 yen.
Customers with high LTV are extremely important to the salon.
Increasing such customers leads to long-term management stability.
Ways to improve LTV include measures such as increasing the repeat rate, increasing visit frequency, increasing spending per customer, and extending the duration of the relationship (preventing dormancy).
For goal setting, grasp the current average LTV and aim for a 10-20% increase compared to the previous year.
If it is currently 200,000 yen, the goal is 220,000 yen to 240,000 yen.

KPI 5: Staff Utilization Rate

The staff utilization rate is the percentage of time staff are actually using for treatments or counseling.
If the utilization rate is too high, staff will be exhausted, and if it is too low, you will miss sales opportunities.
The calculation formula is "Actual working time ÷ Working hours × 100".
For example, if you spent 6 hours on treatments out of an 8-hour shift, the utilization rate is 75%.
The appropriate utilization rate is said to be 70-80%.
If it exceeds 80%, the burden on staff is too high, increasing the risk of service quality decline and turnover.
If it is less than 70%, there is a possibility that you are missing sales opportunities.
For goal setting, grasp the current utilization rate and adjust it to the 70-80% range.
If it is too high, consider automation or operational efficiency improvements; if it is too low, consider strengthening customer acquisition or optimizing reservation slots.

Creation and Operation of a KPI Dashboard

Once you have set the five KPIs, let's create a KPI dashboard where you can check them on a single screen.
Pimo's Overall Statistics View has a custom dashboard function.
You can select and arrange important KPIs to suit your own salon.

Dashboard

Display the current value, target value, month-on-month comparison, and year-on-year comparison for each KPI.
Furthermore, make it possible to visually check the trends with graphs.

Repeat Rate

The current month's figures/target figures, their month-over-month comparisons, and graphs showing monthly trends are displayed.
✅ Average transaction value
✅ Average LTV and LTV distribution by segment
✅ Staff utilization rate
Executives and managers check this dashboard every week.
At monthly management meetings, this dashboard is displayed on the screen to check the degree of goal achievement, and improvement measures are discussed for KPIs that have not been met.
KPIs are not just about 'measuring and finishing'.
It is important to take concrete actions based on the measured numbers.

Translating data analysis into improvement measures

Improvement Case Study 1: Solving the problem of low repeat rates

At one salon, the repeat rate was 18%, which was below the industry average. The owner wanted to solve this problem.
First, analyze the data in detail. Using the segment analysis view of the Customer 360° View, we created a 'first-time visitor' segment and analyzed their subsequent behavioral patterns.
The analysis results showed that the repeat rate for customers who received a follow-up message within two weeks of their first visit was 35%, while the repeat rate for those who did not receive a follow-up message was 12%.
There is about a threefold difference.
Looking in more detail, the repeat rate for customers who were followed up within two weeks of their first visit and were also offered a second-visit incentive (20% OFF) rose to 42%.
Based on these analysis results, the following improvement measures were implemented.
Set up an automatic follow-up message to be sent two weeks after the first visit.
Include an incentive in the message: '20% OFF all menus for second-time visitors only.' The message is personalized according to the customer's treatment content (e.g., include information related to facials for those who received a facial).
As a result of implementing this measure for three months, the repeat rate improved from 18% to 32%. This is a 14-point, approximately 78% improvement.
Calculating with 10 new customers per month, there used to be 1.8 repeaters, but after the improvement, it became 3.2. This is an increase of 1.4 repeaters per month, or 16.8 per year. Calculating with an average transaction value of 12,000 yen, this led to an annual sales increase of approximately 200,000 yen.
※Average values based on our company's track record

Improvement Case Study 2: Solving the problem of low reservation rates for specific menus

At one clinic, the reservation rate for the newly introduced 'HydraFacial' was sluggish.
Even though it was listed on the menu, there were only 2-3 reservations per month.
Analyzing the data revealed the following.
Many customers did not understand what kind of treatment 'HydraFacial' was even after seeing the name. The price was high at 18,000 yen, and many seemed hesitant compared to the basic facial (12,000 yen).
There were few proactive suggestions from staff, and customers rarely asked, 'What is a HydraFacial?'
Based on these analysis results, the following improvement measures were implemented. Add a 'What is a HydraFacial?' button to the LINE rich menu and provide links to easy-to-understand explanatory videos and case photos.
For repeaters who have received a basic facial two or more times, send a segment message saying, 'How about a HydraFacial as your next step?'
Set an initial limited price (18,000 yen → 14,400 yen, 20% OFF) to lower the psychological hurdle.
Train staff on the features, effects, and proposal scripts for HydraFacial.
Make it a rule to always suggest a HydraFacial to customers who say they are 'concerned about clogged pores'.
As a result of implementing this measure for two months, the monthly number of HydraFacial reservations increased from 2-3 to 12. This is an approximately fourfold improvement.
Since HydraFacial has a high transaction value, it contributed significantly to sales, leading to a monthly sales increase of approximately 180,000 yen, or approximately 2.16 million yen annually.
※Average values based on our company's track record

Improvement Case Study 3: Excavating dormant customers

At one salon, there were 25 dormant customers who had not visited for more than 3 months.
If left alone, there is a possibility that they will leave completely.
Analyzing the data revealed the characteristics of dormant customers.
The average number of visits before becoming dormant was 3.5, and a certain level of trust had been built.
The average transaction value before becoming dormant was 15,000 yen, indicating a customer segment with disposable income. About 30% of customers who have not visited for 3 to 6 months will return with a special campaign. After 6 months, the return rate drops to less than 10%.
Based on these analysis results, the following improvement measures were implemented. First, create a segment with the conditions 'no visit for 3-6 months', 'past visit count of 3 or more', and 'LTV of 50,000 yen or more'. 18 people met these criteria.
Implement a 'Welcome Back Campaign' for this segment. 30% OFF all menus, valid for 1 month.
The message is not sent as a mass broadcast, but is personalized according to each customer's past treatment content.
The content is something like, 'Did you enjoy your last facial treatment?'
In addition to LINE messages, staff will follow up by phone directly for particularly important customers (LTV of 100,000 yen or more).
As a result of implementing this measure, 6 out of 18 people returned.
The return rate is 33%. Considering that the return rate for a normal dormant customer excavation campaign is about 10%, this is more than three times as effective.
The return of 6 people recovered approximately 90,000 yen in sales.
Furthermore, 4 of them resumed regular visits, which also led to the recovery of a long-term sales base.
※Average values based on our company's track record

Practicing the PDCA cycle

The core of data-driven management is to continuously run the PDCA cycle.
PDCA is a method for continuous improvement by repeating the four steps of Plan, Do, Check, and Action.

Plan: Data analysis and strategy formulation

First, analyze data using the Customer 360° View or KPI dashboard to identify issues.
These are issues such as 'low repeat rate', 'specific menus not selling', or 'increasing number of dormant customers'.
Next, formulate a hypothesis for that issue.
Hypotheses such as 'Is the repeat rate low because follow-up after the first visit is insufficient?' or 'Is a specific menu not selling because customers do not understand its value?'
Then, formulate improvement measures based on the hypothesis.
Concrete measures such as 'send an automatic follow-up message two weeks after the first visit' or 'create a menu explanation video and distribute it via LINE'.

Do: Implementation of measures

Actually implement the planned measures.
Use Pimo's functions to set up automatic messages, execute segment distribution, and give instructions to staff.
The implementation period for the measures should be at least 1 month, preferably 2-3 months.
If it is too short, the effect cannot be measured, and if it is too long, course correction will be delayed.

Check: Effect measurement

After implementing the measures, measure how the KPIs have changed.
Quantitative evaluations such as 'repeat rate improved from 18% to 32%' or 'HydraFacial reservations increased from 2 to 12'.
In addition, collect feedback from customers and staff.
Qualitative evaluations such as 'I was happy with the follow-up message' or 'the menu explanation became easier to understand' are also important.

Action: Next action

Decide on the next action based on the evaluation results.
If the measure is successful, continue it and expand it horizontally to other segments and other menus.
For example, 'Since the follow-up message after the first visit was effective, let's also set up a follow-up message after the second visit'.
If the measure did not produce the expected effect, analyze the cause and improve it.
For example, 'I sent a follow-up message, but the repeat rate did not increase. Perhaps the content of the message was not attractive. Let's review the content of the incentive'.
By running this PDCA cycle monthly, the salon's management will be continuously improved.

Success stories of data-driven management

Finally, I will introduce a case study of a salon that practiced data-driven management and succeeded.

Case Study: Mid-sized Aesthetic Salon (100 monthly reservations)

Before introducing Pimo, this salon was operated based on the owner's intuition and experience. While they felt vague issues like 'sales aren't growing for some reason' or 'the staff seems tired,' they didn't know exactly what to do.
Since introducing Pimo and starting to use the Customer 360° View, their management has changed significantly.
First, they set five KPIs and began checking them on a dashboard every week.
As a result, the following issues became clear:
📝 The number of new customer acquisitions was not low at 10 per month, but the acquisition cost was too high at 8,000 yen per person.
📝 The repeat rate was 15%, significantly lower than the industry average.
📝 The average transaction value was 11,000 yen, failing to reach the target of 12,000 yen.
📝 There were 30 dormant customers, meaning sales opportunities were being missed.
📝 Staff utilization rate exceeded 90% on average, placing too much burden on them.
They implemented data-based improvement measures to address these issues.
✅ New Customer Acquisition
Shifted from reliance on Hot Pepper to LINE-based customer acquisition, reducing acquisition costs from 8,000 yen to 4,500 yen.
✅ Repeat Rate
Set up automated follow-ups for two weeks after the first visit and exclusive benefits for the second visit, increasing the repeat rate from 15% to 35%.
✅ Increasing Transaction Value
Strengthened recommendations for higher-tier menus using AI, increasing the average transaction value from 11,000 yen to 13,500 yen.
✅ Re-engaging Dormant Customers
Conducted special campaigns segmented by customer type, resulting in 10 out of 30 customers returning.
✅ Staff Utilization Rate
Improved operational efficiency through the use of AI-summarized medical records and an AI concierge, improving the utilization rate from 90% to 75%.

Through these improvement measures, the following results were achieved within 6 months of introducing Pimo.
Monthly sales increased from 1.1 million yen to 1.65 million yen (+50%).
Annual sales increased by approximately 6.6 million yen. The repeat rate improved from 15% to 35% (+20 points).
Staff overtime decreased from 40 hours to 15 hours per month, improving the work environment.
Customer satisfaction increased, and review ratings improved from 4.2 to 4.7.
The owner commented, 'By looking at the data, it became clear what I needed to do.
Management has shifted from relying on intuition to acting with conviction.'
※Average values based on our company's performance

Summary: Using Data Changes Management

In this article, we explained how to set five key KPIs for salon management (number of new customer acquisitions, repeat rate, average transaction value, LTV, and staff utilization rate) and how to translate data analysis into improvement measures.
By setting KPIs and visualizing them on a dashboard, vague management issues become clear as concrete numbers.
Then, through data analysis, you identify the causes of issues and implement improvement measures based on hypotheses.
By continuously cycling through PDCA, salon management will steadily improve.
Data-driven management does not deny intuition or experience; rather, it adds objective evidence in the form of data to enable more reliable management decisions.
Customer 360° View is not just a data management tool.
It is a powerful partner for deeply understanding your customers, improving management, enhancing staff work environments, and achieving sustainable growth.
In the next issue, #18, we will explain 'Pimo Success Stories: Introduction Effects by Business Type and Real-world Management Improvements.'
We will introduce detailed case studies from various business types, such as cosmetic dermatology clinics, aesthetic salons, plastic surgery clinics, and small private salons, along with specific management improvement figures and key points for implementation.
You will be able to visualize the future after implementation based on cases similar to your own salon, so please look forward to it.

Thank you for reading to the end once again.

■ Leave it to Fourglobe for consultations on LINE and AI utilization for clinics and salons!

Fourglobe possesses high expertise in LINE and AI utilization within the clinic and salon sectors, with a wealth of support experience and knowledge in related fields. Based on the know-how cultivated through years of digital marketing support, we provide support for optimizing customer communication using LINE and for customer understanding and operational efficiency using AI.
We can also propose mechanisms to improve service quality, repeat rates, and LTV by utilizing reservation information, visit history, counseling content, purchase history, and LINE interactions.
Please feel free to consult with us regarding proposals for improving marketing measures, LINE utilization tailored to your operations, and support for the introduction and use of AI tools!