Top 10 Laundromat Revenue KPIs

Curated by Kory White · Fractional CRO, CRO Syndicate

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📅 Published Jun 26, 2026 · Updated Jun 26, 2026 · 9 min read

Direct Answer

This guide defines the top 10 revenue KPIs for laundromat operators, providing actionable benchmarks and reporting cadences to maximize profitability. You will learn which metrics matter most, how to track them using real tools, and common mistakes to avoid.

TL;DR
** Laundromat revenue health is driven by 10 KPIs: Revenue Per Square Foot, Washer/Dryer Turn Rate, Average Ticket Size, Customer Retention Rate, Peak vs. Off-Peak Revenue Split, Vended Revenue Per Machine, Service Revenue (wash-dry-fold), Coin vs. Card Load Rate, Operating Expense Ratio, and Revenue Per Employee.
Track these weekly using POS data (e.g., Cents, LaundryLux), reconcile with QuickBooks, and avoid vanity metrics like "total customers." A 30-60-90 plan focuses on machine utilization first, then pricing, then labor efficiency.

Why Laundromats Measure Differently

Laundromats are a unique retail subsegment: high fixed costs (lease, utilities, equipment), low variable costs per transaction, and heavy dependence on foot traffic and machine uptime. Unlike SaaS or e-commerce, revenue is not subscription-based but transactional and capacity-constrained.

A washer running 24/7 generates a hard ceiling on revenue per machine. This forces operators to focus on throughput and yield rather than just customer count.

Another key difference: laundromats have two distinct revenue streams—self-service (coin/card) and service (wash-dry-fold, drop-off). Each has different margins. Self-service is high-margin but capital-intensive (machines).

Service is labor-intensive but can double revenue per square foot. Most operators fail to separate these in their P&L, leading to mispricing.

Finally, laundromats are hyper-local. A store in a dense urban area (e.g., New York City) will have different KPIs than one in a suburban strip mall. Revenue per square foot can range from $150 to $400 annually depending on location and service mix. This makes industry averages less useful than store-specific benchmarks.

The Most Important KPIs to Track

1. Revenue Per Square Foot (RevPSF)

Formula: Total annual revenue ÷ total square footage of the store (including back-of-house). Why it matters: This is the ultimate efficiency metric. A store with 2,000 sq ft generating $400,000/year has a RevPSF of $200.

Industry benchmarks: $150–$300 for self-service only; $250–$500 for stores with wash-dry-fold. If your RevPSF is below $150, you likely have underutilized space or poor machine mix. How to improve: Add high-margin services (wash-dry-fold, dry cleaning drop-off).

Reconfigure floor plan to reduce wasted aisle space. Increase machine density (e.g., replace 20-pound washers with 40-pound models).

2. Washer/Dryer Turn Rate (WTR)

Formula: Total cycles per machine per day ÷ 24 hours. Usually expressed as cycles per machine per day. Why it matters: A washer that runs 6 cycles per day at $4.00 per cycle generates $24/day in revenue.

A machine running 3 cycles generates $12/day. Industry average: 4–8 cycles per machine per day for washers, 6–10 for dryers. Below 3 cycles indicates underutilization.

How to improve: Optimize cycle times (shorter cycles for small loads). Use dynamic pricing via POS systems like Cents to lower prices during off-peak hours. Ensure all machines are operational (downtime kills WTR).

3. Average Ticket Size (ATS)

Formula: Total revenue ÷ total transactions (including service orders). Why it matters: ATS measures how much each customer spends per visit. For self-service, ATS is typically $8–$15.

For wash-dry-fold, it’s $15–$30. Low ATS suggests customers are doing small loads or using only one machine. High ATS indicates bundling (e.g., multiple machines or added services).

How to improve: Offer bundled pricing (e.g., "Wash & Fold 20 lbs for $25"). Upsell with vending (detergent, dryer sheets). Implement loyalty programs (e.g., "Spend $100, get $10 free") via LaundryLux or Speed Queen’s app.

4. Customer Retention Rate (CRR)

Formula: (Number of repeat customers in a period ÷ total customers in that period) × 100. Why it matters: A laundromat with 70% CRR has predictable revenue. One with 40% is constantly acquiring new customers, which is expensive.

Industry average: 50–65% for self-service; 60–75% for wash-dry-fold. How to improve: Use a loyalty app (e.g., PayRange) to track visits. Send push notifications for promotions.

Maintain clean facilities—dirty floors or broken machines drive churn.

5. Peak vs. Off-Peak Revenue Split

Formula: Revenue during peak hours (e.g., Sat–Sun 9am–5pm) ÷ total weekly revenue. Why it matters: If 80% of revenue comes from peak hours, your store is capacity-constrained during peak and underutilized off-peak. Ideal split: 60% peak, 40% off-peak.

This spreads demand and reduces wait times. How to improve: Run off-peak promotions (e.g., "50% off dryers on Tuesday mornings"). Adjust pricing: lower rates during low-demand hours.

Use Clover or Square POS to track hourly revenue.

6. Vended Revenue Per Machine (VRPM)

Formula: Total revenue from a specific machine ÷ number of days in period. Why it matters: This identifies underperforming machines. A washer generating $3/day is likely broken or in a bad location.

Target: $5–$10/day for washers, $3–$6/day for dryers. How to improve: Move high-performing machines to high-traffic areas. Repair or replace low-performers.

Use Cents machine monitoring to get real-time alerts on downtime.

7. Service Revenue (Wash-Dry-Fold)

Formula: Total revenue from drop-off laundry services. Why it matters: This is the highest-margin revenue stream (50–70% gross margin) but requires labor. If service revenue is below 20% of total, you are leaving money on the table.

Top operators hit 30–40%. How to improve: Hire a dedicated service attendant. Set up a simple online ordering system via LaundryLux.

Price per pound at $1.50–$2.50 (adjust for your market).

8. Coin vs. Card Load Rate

Formula: Percentage of transactions using card (credit/debit/app) vs. Coin. Why it matters: Card users spend 20–30% more per visit than coin users.

They also reload more frequently. If card load rate is below 50%, you are losing revenue. How to improve: Install card readers on all machines (e.g., USA Technologies ePort).

Offer a "load $20, get $2 free" promotion. Remove coin-only machines.

9. Operating Expense Ratio (OER)

Formula: Total operating expenses (utilities, rent, labor, maintenance) ÷ total revenue. Why it matters: A healthy OER is 60–75%. Above 80% means you are bleeding cash.

Utilities alone should be 15–20% of revenue. Labor should be 20–30% (if offering service). How to improve: Negotiate utility rates (ask for commercial time-of-use pricing).

Reduce water usage with high-efficiency washers (e.g., Speed Queen models). Cross-train staff to reduce overtime.

10. Revenue Per Employee (RPE)

Formula: Total revenue ÷ total full-time equivalent employees (including owner). Why it matters: For a self-service store with no service, RPE should be $80,000–$120,000. For a store with wash-dry-fold, $50,000–$80,000.

Low RPE means overstaffing. How to improve: Use scheduling software (e.g., 7shifts) to match labor to demand. Automate coin counting with Coinmax machines.

Reduce service labor by batching orders.

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Real Operators

Operator A: A 2,000 sq ft store in Chicago with 30 washers and 20 dryers. RevPSF: $220. WTR: 5.5 cycles/machine/day.

ATS: $11. They use Cents for dynamic pricing and PayRange for card payments. Their OER is 68%.

Key lesson: they increased VRPM by 15% after replacing 10 underperforming washers with Speed Queen high-efficiency models.

Operator B: A 1,500 sq ft store in Phoenix with wash-dry-fold. Service revenue is 35% of total. ATS: $22. CRR: 72%. They use LaundryLux for online orders and QuickBooks for accounting. Their OER is 72% due to high labor costs. They reduced labor by 10% using 7shifts to schedule based on peak times.

Operator C: A 3,000 sq ft store in Los Angeles with no service. RevPSF: $180. WTR: 3.2 cycles/machine/day. Their OER is 80% because of high rent ($12,000/month). They are pivoting to add wash-dry-fold to increase RevPSF. Estimated impact: +$50,000/year in service revenue.

Failure Modes

Failure Mode 1: Ignoring Machine Utilization. Operators track total revenue but not per-machine revenue. A single broken washer can cost $100–$200/month in lost revenue. Fix: Use Cents or LaundryLux machine monitoring to get daily alerts on downtime.

Failure Mode 2: Pricing by Cost Plus Instead of Demand. Setting a flat $4.00 per wash regardless of time of day leaves money on the table. A store near a university could charge $5.00 during peak move-in weekends. Use dynamic pricing.

Failure Mode 3: Over-Servicing Without Pricing. Wash-dry-fold operators often underprice labor. If you charge $1.50/lb but labor is $15/hour, you need 10 lbs/hour to break even. Real cost is $2.00/lb minimum. Recalculate your service margin quarterly.

Failure Mode 4: Neglecting Card Load Rate. Stores with 80% coin usage have lower ATS and higher cash handling costs. Switching to 60% card can increase revenue by 10–15%. Install card readers as a priority.

Failure Mode 5: No Reporting Cadence. Operators who only look at monthly revenue miss weekly trends. A 10% drop in WTR over two weeks could be a broken machine. Set up weekly KPI dashboards in QuickBooks or Excel.

Reporting Cadence

Daily: Revenue per machine (via POS alerts). Check for machines with 0 cycles.
Weekly: WTR, ATS, Peak vs. Off-Peak Split, VRPM. Use a spreadsheet template.
Monthly: RevPSF, CRR, OER, Service Revenue %. Reconcile with QuickBooks.
Quarterly: RPE, Coin vs. Card Load Rate. Adjust pricing and labor.
Annually: Full P&L review. Benchmark against Coin Laundry Association reports.

30-60-90

Days 1–30: Audit and Fix Machine Utilization. Run a machine-by-machine VRPM report. Repair or replace any machine below $3/day. Install card readers if card load rate is below 40%. Set up daily alerts in Cents.

Days 31–60: Optimize Pricing and Service Mix. Implement dynamic pricing (peak vs. Off-peak). Launch a wash-dry-fold service if RevPSF is below $200. Test a $20 load card promotion to increase ATS.

Days 61–90: Streamline Labor and Reporting. Use 7shifts to schedule staff based on peak hours. Reduce labor hours by 10% without impacting service. Set up a weekly KPI dashboard in QuickBooks or Google Sheets. Review OER and target below 70%.

FAQ

? What is the single most important KPI for a laundromat? Revenue Per Square Foot (RevPSF). It captures both space utilization and revenue mix. Below $150/sq ft, you are underperforming.

? How do I track machine utilization without expensive software? Use a manual log: count cycles per machine per day for one week. Then extrapolate. For under $50/month, Cents offers basic machine monitoring.

? What is a good average ticket size for wash-dry-fold? $18–$25 per order. If below $15, you are underpricing or not upselling.

? How often should I adjust pricing? Quarterly for base prices. Weekly for promotions (e.g., off-peak discounts). Use Clover or Square to test price elasticity.

? Should I eliminate coin-only machines? Yes, if card load rate is below 40%. Card users spend 20–30% more. Phase out coin-only over 6 months.

? What is the biggest mistake new operators make? Underpricing wash-dry-fold. They set $1.50/lb but labor + utilities cost $1.20/lb. Margin is too thin. Price at $2.00/lb minimum.

Sources

flowchart TD A[Laundromat Revenue] --> B[Self-Service Revenue] A --> C[Service Revenue] B --> D[Coin Revenue] B --> E[Card Revenue] C --> F[Wash-Dry-Fold] C --> G[Drop-Off Dry Cleaning] D --> H[Coin Load Rate] E --> I[Card Load Rate] H --> J[VRPM] I --> J J --> K[RevPSF] F --> L[Service Revenue %] G --> L L --> K

flowchart LR M[Weekly KPI Dashboard] --> N[WTR] M --> O[ATS] M --> P[Peak vs Off-Peak Split] M --> Q[VRPM] N --> R[Action: Repair Machines] O --> S[Action: Adjust Pricing] P --> T[Action: Run Promotions] Q --> U[Action: Replace Underperformers] R --> V[Monthly Review] S --> V T --> V U --> V V --> W[Quarterly OER & RPE Review]

Keep reading

![Top 10 Laundromat Revenue KPIs](https://www.flexwasher.com/wp-content/uploads/2024/04/laundromat-kpis-metrics-1080x630.png)

### Direct Answer

This guide defines the top 10 revenue KPIs for laundromat operators, providing actionable benchmarks and reporting cadences to maximize profitability. You will learn which metrics matter most, how to track them using real tools, and common mistakes to avoid.

> **TL;DR:** Laundromat revenue health is driven by 10 KPIs: Revenue Per Square Foot, Washer/Dryer Turn Rate, Average Ticket Size, Customer Retention Rate, Peak vs. Off-Peak Revenue Split, Vended Revenue Per Machine, Service Revenue (wash-dry-fold), Coin vs. Card Load Rate, Operating Expense Ratio, and Revenue Per Employee. Track these weekly using POS data (e.g., **Cents**, **LaundryLux**), reconcile with **QuickBooks**, and avoid vanity metrics like "total customers." A 30-60-90 plan focuses on machine utilization first, then pricing, then labor efficiency.

## Why Laundromats Measure Differently

Laundromats are a unique retail subsegment: high fixed costs (lease, utilities, equipment), low variable costs per transaction, and heavy dependence on foot traffic and machine uptime. Unlike SaaS or e-commerce, revenue is not subscription-based but transactional and capacity-constrained. A washer running 24/7 generates a hard ceiling on revenue per machine. This forces operators to focus on **throughput** and **yield** rather than just customer count.

Another key difference: laundromats have two distinct revenue streams—self-service (coin/card) and service (wash-dry-fold, drop-off). Each has different margins. Self-service is high-margin but capital-intensive (machines). Service is labor-intensive but can double revenue per square foot. Most operators fail to separate these in their P&L, leading to mispricing.

Finally, laundromats are hyper-local. A store in a dense urban area (e.g., **New York City**) will have different KPIs than one in a suburban strip mall. Revenue per square foot can range from **$150 to $400** annually depending on location and service mix. This makes industry averages less useful than store-specific benchmarks.

## The Most Important KPIs to Track

### 1. Revenue Per Square Foot (RevPSF)
**Formula:** Total annual revenue ÷ total square footage of the store (including back-of-house).
**Why it matters:** This is the ultimate efficiency metric. A store with 2,000 sq ft generating $400,000/year has a RevPSF of **$200**. Industry benchmarks: **$150–$300** for self-service only; **$250–$500** for stores with wash-dry-fold. If your RevPSF is below **$150**, you likely have underutilized space or poor machine mix.
**How to improve:** Add high-margin services (wash-dry-fold, dry cleaning drop-off). Reconfigure floor plan to reduce wasted aisle space. Increase machine density (e.g., replace 20-pound washers with 40-pound models).

### 2. Washer/Dryer Turn Rate (WTR)
**Formula:** Total cycles per machine per day ÷ 24 hours. Usually expressed as cycles per machine per day.
**Why it matters:** A washer that runs 6 cycles per day at $4.00 per cycle generates **$24/day** in revenue. A machine running 3 cycles generates **$12/day**. Industry average: **4–8 cycles per machine per day** for washers, **6–10** for dryers. Below 3 cycles indicates underutilization.
**How to improve:** Optimize cycle times (shorter cycles for small loads). Use **dynamic pricing** via POS systems like **Cents** to lower prices during off-peak hours. Ensure all machines are operational (downtime kills WTR).

### 3. Average Ticket Size (ATS)
**Formula:** Total revenue ÷ total transactions (including service orders).
**Why it matters:** ATS measures how much each customer spends per visit. For self-service, ATS is typically **$8–$15**. For wash-dry-fold, it’s **$15–$30**. Low ATS suggests customers are doing small loads or using only one machine. High ATS indicates bundling (e.g., multiple machines or added services).
**How to improve:** Offer bundled pricing (e.g., "Wash & Fold 20 lbs for $25"). Upsell with vending (detergent, dryer sheets). Implement loyalty programs (e.g., "Spend $100, get $10 free") via **LaundryLux** or **Speed Queen’s** app.

### 4. Customer Retention Rate (CRR)
**Formula:** (Number of repeat customers in a period ÷ total customers in that period) × 100.
**Why it matters:** A laundromat with 70% CRR has predictable revenue. One with 40% is constantly acquiring new customers, which is expensive. Industry average: **50–65%** for self-service; **60–75%** for wash-dry-fold.
**How to improve:** Use a loyalty app (e.g., **PayRange**) to track visits. Send push notifications for promotions. Maintain clean facilities—dirty floors or broken machines drive churn.

### 5. Peak vs. Off-Peak Revenue Split
**Formula:** Revenue during peak hours (e.g., Sat–Sun 9am–5pm) ÷ total weekly revenue.
**Why it matters:** If 80% of revenue comes from peak hours, your store is capacity-constrained during peak and underutilized off-peak. Ideal split: **60% peak, 40% off-peak**. This spreads demand and reduces wait times.
**How to improve:** Run off-peak promotions (e.g., "50% off dryers on Tuesday mornings"). Adjust pricing: lower rates during low-demand hours. Use **Clover** or **Square** POS to track hourly revenue.

### 6. Vended Revenue Per Machine (VRPM)
**Formula:** Total revenue from a specific machine ÷ number of days in period.
**Why it matters:** This identifies underperforming machines. A washer generating **$3/day** is likely broken or in a bad location. Target: **$5–$10/day** for washers, **$3–$6/day** for dryers.
**How to improve:** Move high-performing machines to high-traffic areas. Repair or replace low-performers. Use **Cents** machine monitoring to get real-time alerts on downtime.

### 7. Service Revenue (Wash-Dry-Fold)
**Formula:** Total revenue from drop-off laundry services.
**Why it matters:** This is the highest-margin revenue stream (50–70% gross margin) but requires labor. If service revenue is below 20% of total, you are leaving money on the table. Top operators hit **30–40%**.
**How to improve:** Hire a dedicated service attendant. Set up a simple online ordering system via **LaundryLux**. Price per pound at **$1.50–$2.50** (adjust for your market).

### 8. Coin vs. Card Load Rate
**Formula:** Percentage of transactions using card (credit/debit/app) vs. Coin.
**Why it matters:** Card users spend **20–30% more** per visit than coin users. They also reload more frequently. If card load rate is below 50%, you are losing revenue.
**How to improve:** Install card readers on all machines (e.g., **USA Technologies** ePort). Offer a "load $20, get $2 free" promotion. Remove coin-only machines.

### 9. Operating Expense Ratio (OER)
**Formula:** Total operating expenses (utilities, rent, labor, maintenance) ÷ total revenue.
**Why it matters:** A healthy OER is **60–75%**. Above 80% means you are bleeding cash. Utilities alone should be **15–20%** of revenue. Labor should be **20–30%** (if offering service).
**How to improve:** Negotiate utility rates (ask for commercial time-of-use pricing). Reduce water usage with high-efficiency washers (e.g., **Speed Queen** models). Cross-train staff to reduce overtime.

### 10. Revenue Per Employee (RPE)
**Formula:** Total revenue ÷ total full-time equivalent employees (including owner).
**Why it matters:** For a self-service store with no service, RPE should be **$80,000–$120,000**. For a store with wash-dry-fold, **$50,000–$80,000**. Low RPE means overstaffing.
**How to improve:** Use scheduling software (e.g., **7shifts**) to match labor to demand. Automate coin counting with **Coinmax** machines. Reduce service labor by batching orders.


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## Real Operators

**Operator A:** A 2,000 sq ft store in Chicago with 30 washers and 20 dryers. RevPSF: **$220**. WTR: 5.5 cycles/machine/day. ATS: **$11**. They use **Cents** for dynamic pricing and **PayRange** for card payments. Their OER is **68%**. Key lesson: they increased VRPM by 15% after replacing 10 underperforming washers with **Speed Queen** high-efficiency models.

**Operator B:** A 1,500 sq ft store in Phoenix with wash-dry-fold. Service revenue is 35% of total. ATS: **$22**. CRR: 72%. They use **LaundryLux** for online orders and **QuickBooks** for accounting. Their OER is **72%** due to high labor costs. They reduced labor by 10% using **7shifts** to schedule based on peak times.

**Operator C:** A 3,000 sq ft store in Los Angeles with no service. RevPSF: **$180**. WTR: 3.2 cycles/machine/day. Their OER is **80%** because of high rent ($12,000/month). They are pivoting to add wash-dry-fold to increase RevPSF. Estimated impact: +$50,000/year in service revenue.

## Failure Modes

**Failure Mode 1: Ignoring Machine Utilization.** Operators track total revenue but not per-machine revenue. A single broken washer can cost **$100–$200/month** in lost revenue. Fix: Use **Cents** or **LaundryLux** machine monitoring to get daily alerts on downtime.

**Failure Mode 2: Pricing by Cost Plus Instead of Demand.** Setting a flat $4.00 per wash regardless of time of day leaves money on the table. A store near a university could charge **$5.00** during peak move-in weekends. Use dynamic pricing.

**Failure Mode 3: Over-Servicing Without Pricing.** Wash-dry-fold operators often underprice labor. If you charge $1.50/lb but labor is $15/hour, you need 10 lbs/hour to break even. Real cost is **$2.00/lb** minimum. Recalculate your service margin quarterly.

**Failure Mode 4: Neglecting Card Load Rate.** Stores with 80% coin usage have lower ATS and higher cash handling costs. Switching to 60% card can increase revenue by **10–15%**. Install card readers as a priority.

**Failure Mode 5: No Reporting Cadence.** Operators who only look at monthly revenue miss weekly trends. A 10% drop in WTR over two weeks could be a broken machine. Set up weekly KPI dashboards in **QuickBooks** or **Excel**.

## Reporting Cadence

- **Daily:** Revenue per machine (via POS alerts). Check for machines with 0 cycles.
- **Weekly:** WTR, ATS, Peak vs. Off-Peak Split, VRPM. Use a spreadsheet template.
- **Monthly:** RevPSF, CRR, OER, Service Revenue %. Reconcile with **QuickBooks**.
- **Quarterly:** RPE, Coin vs. Card Load Rate. Adjust pricing and labor.
- **Annually:** Full P&L review. Benchmark against **Coin Laundry Association** reports.

## 30-60-90

**Days 1–30: Audit and Fix Machine Utilization.** Run a machine-by-machine VRPM report. Repair or replace any machine below **$3/day**. Install card readers if card load rate is below 40%. Set up daily alerts in **Cents**.

**Days 31–60: Optimize Pricing and Service Mix.** Implement dynamic pricing (peak vs. Off-peak). Launch a wash-dry-fold service if RevPSF is below **$200**. Test a $20 load card promotion to increase ATS.

**Days 61–90: Streamline Labor and Reporting.** Use **7shifts** to schedule staff based on peak hours. Reduce labor hours by 10% without impacting service. Set up a weekly KPI dashboard in **QuickBooks** or **Google Sheets**. Review OER and target below 70%.

## FAQ

**? What is the single most important KPI for a laundromat?**  
Revenue Per Square Foot (RevPSF). It captures both space utilization and revenue mix. Below **$150/sq ft**, you are underperforming.

**? How do I track machine utilization without expensive software?**  
Use a manual log: count cycles per machine per day for one week. Then extrapolate. For under $50/month, **Cents** offers basic machine monitoring.

**? What is a good average ticket size for wash-dry-fold?**  
**$18–$25** per order. If below $15, you are underpricing or not upselling.

**? How often should I adjust pricing?**  
Quarterly for base prices. Weekly for promotions (e.g., off-peak discounts). Use **Clover** or **Square** to test price elasticity.

**? Should I eliminate coin-only machines?**  
Yes, if card load rate is below 40%. Card users spend 20–30% more. Phase out coin-only over 6 months.

**? What is the biggest mistake new operators make?**  
Underpricing wash-dry-fold. They set $1.50/lb but labor + utilities cost $1.20/lb. Margin is too thin. Price at **$2.00/lb** minimum.

## Sources

- [Coin Laundry Association - Industry Benchmarks](https://www.coinlaundry.org)
- [Cents - Laundry POS & Machine Monitoring](https://www.trycents.com)
- [LaundryLux - Wash-Dry-Fold Software](https://www.laundrylux.com)
- [Speed Queen - Commercial Washer/Dryer Specs](https://www.speedqueencommercial.com)
- [PayRange - Card & Mobile Payment for Laundromats](https://www.payrange.com)
- [USA Technologies - ePort Card Readers](https://www.usatech.com)
- [QuickBooks - Laundromat Accounting](https://quickbooks.intuit.com)
- [7shifts - Labor Scheduling for Retail](https://www.7shifts.com)
- [Clover - POS Systems for Small Business](https://www.clover.com)
- [Square - Payment Processing & POS](https://squareup.com)

```mermaid
flowchart TD
    A[Laundromat Revenue] --> B[Self-Service Revenue]
    A --> C[Service Revenue]
    B --> D[Coin Revenue]
    B --> E[Card Revenue]
    C --> F[Wash-Dry-Fold]
    C --> G[Drop-Off Dry Cleaning]
    D --> H[Coin Load Rate]
    E --> I[Card Load Rate]
    H --> J[VRPM]
    I --> J
    J --> K[RevPSF]
    F --> L[Service Revenue %]
    G --> L
    L --> K
```

```mermaid
flowchart LR
    M[Weekly KPI Dashboard] --> N[WTR]
    M --> O[ATS]
    M --> P[Peak vs Off-Peak Split]
    M --> Q[VRPM]
    N --> R[Action: Repair Machines]
    O --> S[Action: Adjust Pricing]
    P --> T[Action: Run Promotions]
    Q --> U[Action: Replace Underperformers]
    R --> V[Monthly Review]
    S --> V
    T --> V
    U --> V
    V --> W[Quarterly OER & RPE Review]
```

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