Understanding Patient Satisfaction and Attrition Through Customer Data Analysis

- Deepening Customer Insight to Become a Truly “Chosen” Medical Institution -

In healthcare management, “knowing your customers” is both the most fundamental and the most challenging task.

In this second article of the series, we explore how to organize and interpret customer data, and how such insights contribute to more effective and confident management decisions.

Organizing Customer Data Reveals Structures That Were Previously Invisible

Medical institutions accumulate vast amounts of customer data through daily clinical operations and health checkup services.

However, much of this information remains unused.

By simply organizing a few essential data elements, the behavioral patterns and characteristics of your customers become surprisingly clear.

1. Foundational Data for Understanding Your Customers

A. Address (Trade Area Analysis)

• What percentage of customers reside within a certain radius (e.g., 80%)?

• Which areas are strong, and which areas are weak in terms of customer draw?

Clarifying your primary trade area allows you to make more confident decisions regarding:

• Advertising and promotional targeting

• Corporate health checkup outreach

• Access and transportation improvements

B. Demographics (Age, Gender, etc.)

Analyzing customer attributes reveals which segments your facility appeals to most.

Examples:

• Men aged 40–55 → strong interest in lifestyle disease prevention

• Women aged 30–40 → high interest in wellness, prevention, and self-care

In other words, demographic data clarifies:

“Who supports your facility, and to whom is your value currently reaching?”

C. Frequently Used Services (Your Strengths)

Patterns in service utilization provide clear insight into where your strengths lie.

• High utilization of specific courses

• Popular combinations of optional tests

• High concentration of demand in certain time slots

These characteristics represent important clues about where your facility is creating the most value.

D. Services That Are Not Being Used (Your Weaknesses)

Low-utilization services often hold the key to improvement.

Questions to consider:

• Is it a matter of insufficient awareness?

• Is the value proposition unclear?

• Are competitors offering a more attractive option?

• Are pricing or explanations misaligned with customer expectations?

Understanding weaknesses is the first step toward effective redesign.

2. Tracking Data Over Time Reveals Emerging Trends

Customer data becomes most powerful when viewed through the lens of change.

A. Are utilizations increasing or decreasing?

Examples of trends that reflect shifts in market needs:

• Premium course usage is rising

• Certain options are declining

• Weekend demand is rapidly increasing

These indicators highlight how customer needs are evolving.

B. Differences in Trends by Service Category

Even when overall numbers appear stable, the internal composition may be shifting significantly.

• Decline in low-cost courses, increase in mid-tier programs

• Growth in specific age groups

• Rapid increase in female users

Such insights provide evidence for optimizing service composition.

C. Trends by Residential Area (Competitive Landscape)

Tracking address data over time can reveal competitive dynamics:

• Sharp decline from Area A → possible competitor expansion

• Sudden increase from Area B → competitor service reduction or saturation

Data becomes a powerful tool for drawing a competitive map.

Data Offers More Than an Understanding of the Present

Through these analyses, you gain hints about:

• What is happening now, and

• What is likely to happen next

But the value of data goes beyond situational diagnosis.

Practical Data Utilization for Profitability and Strategic Planning

A. Designing Strategies to Increase Utilization of High-Profit Services

If your strategic direction is already clear—for example, strengthening high-profit services—customer data becomes extremely powerful.

Examples:

• Attribute analysis → which groups are more likely to upgrade

• Behavioral patterns → which options often serve as “entry points”

• Time-slot analysis → which sessions are optimal for conversion

The deeper your customer insights, the more precise your 誘導設計（conversion strategy） becomes.

B. Creating New High-Profit Services Based on Market Needs

Customer data also reveals unmet needs and emerging preferences.

Examples:

• Increase in women in their 30s → women-focused checkup packages

• High prevalence of cardiovascular risk → cardiovascular-focused plans

• Increasing corporate demand → development of corporate health packages

This means your facility can develop new revenue-generating services tailored to real customer characteristics.

C. Designing Advertising and Sales Approaches That Truly Resonate

Once customer characteristics become clear, it becomes much easier to determine:

“What message resonates with which audience?”

Examples:

• Men in their 40s → fatigue, lifestyle-related risks

• Women in their 30s → self-care and well-being

• Corporations → ROI of employee health investment

Both marketing messaging and sales approaches can shift from intuition-based to data-driven optimization.

Conclusion

Customer data analysis is not merely a way to understand your current situation.

It provides a foundation for determining where your institution should go next,

and for building strategies that strengthen both competitiveness and profitability.

In the next article, we will apply this customer understanding to the practical creation of a Profitability Map, revealing how medical institutions can redesign their service menus for sustainable growth.