Top 10 Public Transit 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

TL;DR
** Public transit revenue KPIs are distinct from commercial SaaS or retail metrics because they blend farebox recovery, subsidy efficiency, and social value. This guide covers the 10 essential KPIs—from Farebox Recovery Ratio to Cost per Revenue Hour—with real benchmarks from agencies like LA Metro and Transport for London.
You'll learn how to track them, avoid common failure modes like ignoring peak/off-peak splits, and implement a 30-60-90 reporting plan using tools like Trapeze, Umo, and Remix.

Why Public Transit Measures Differently

Public transit operates under a mixed-funding model that commercial businesses rarely face. Revenue comes from three streams: farebox (passenger fares), government subsidies (local, state, federal), and ancillary (advertising, real estate, naming rights). Unlike a SaaS company that can A/B test pricing daily, transit agencies must balance cost recovery with social equity—raising fares can push low-income riders off the system.

This creates a unique KPI set. For example, Farebox Recovery Ratio (FRR) is the transit equivalent of gross margin, but a "good" FRR varies wildly: U.S. Bus systems average 20–30%, while heavy rail like BART hits 65–75% (per APTA 2024 data). European agencies often target 50%+ due to higher subsidies.

Another difference: cost allocation. A transit agency's biggest expense is labor (drivers, mechanics, dispatchers), typically 60–70% of operating costs. So KPIs like Cost per Revenue Hour directly measure labor productivity. In contrast, a tech company's biggest cost is often R&D or sales.

Finally, demand elasticity matters. A 10% fare increase might reduce ridership by 3–5% in the short term (price elasticity of -0.3 to -0.5, per U.S. DOT studies). This feedback loop means revenue KPIs must be paired with ridership metrics—you can't optimize one without the other.

The Most Important KPIs to Track

1. Farebox Recovery Ratio (FRR)

Definition: Total fare revenue divided by total operating expenses. Formula: (Fare Revenue / Operating Expenses) × 100 Benchmark: U.S. Average 30–50% (rail higher, bus lower).

European target often 50–70%. Why it matters: Shows how much of operating costs are covered by riders. Low FRR (<20%) signals over-reliance on subsidies or underpricing.

Tool: TransitPartner by Trapeze Group can calculate FRR automatically using fare and expense data. Pricing starts at $25k/year for small agencies.

2. Passenger Revenue per Mile (PRM)

Definition: Average fare revenue generated per vehicle mile traveled. Formula: Total Fare Revenue / Total Vehicle Miles Benchmark: $2–$5 per mile for bus, $8–$15 for rail (varies by region). Why it matters: Measures route-level profitability.

A route with PRM < $1 may need restructuring or elimination. Tool: Umo (by Cubic) provides real-time PRM dashboards. Their basic tier costs $0.15 per transaction.

3. Cost per Revenue Hour (CPRH)

Definition: Total operating cost divided by the number of hours vehicles are in service (revenue hours). Formula: Total Operating Cost / Total Revenue Hours Benchmark: $150–$250/hour for bus, $300–$500/hour for light rail. Why it matters: Directly measures labor efficiency.

A CPRH above $300 for bus often indicates overtime abuse or inefficient scheduling. Tool: Optibus (now part of Via) optimizes schedules to reduce CPRH. Plans start at $50k/year for a mid-sized agency.

4. Average Fare per Boarding (AFB)

Definition: Total fare revenue divided by total boardings (unlinked trips). Formula: Total Fare Revenue / Total Boardings Benchmark: $1.50–$2.50 for bus, $2.50–$4.00 for rail. Why it matters: Reveals fare structure effectiveness.

If AFB is below the base fare, too many discounts or transfers are being used. Tool: Masabi's Justride platform tracks AFB in real-time. Licensing starts at $100k/year for a city system.

5. Subsidy per Boarding (SPB)

Definition: Total government subsidy divided by total boardings. Formula: (Operating Deficit + Capital Subsidies) / Total Boardings Benchmark: $1–$5 per boarding (U.S.), $0.50–$2 (Europe). Why it matters: Measures taxpayer efficiency.

SPB > $5 often triggers political scrutiny. Tool: Clever Devices (now part of Via) integrates subsidy tracking into their CAD/AVL systems. Pricing custom.

6. Revenue per Service Hour (RPSH)

Definition: Total fare revenue divided by total service hours (including deadhead time). Formula: Total Fare Revenue / Total Service Hours Benchmark: $100–$200/hour for bus, $200–$400 for rail. Why it matters: More comprehensive than CPRH because it includes non-revenue time.

A low RPSH relative to CPRH indicates poor route design. Tool: Remix (now part of Via) visualizes RPSH by route in their planning tool. Pricing from $30k/year.

7. Peak-to-Base Ratio (PBR)

Definition: Ratio of peak-hour revenue to base-hour revenue. Formula: (Peak Hour Revenue / Base Hour Revenue) Benchmark: 1.5–3.0 for bus, 2.0–4.0 for rail. Why it matters: High PBR (>4) means the agency is spending heavily on peak capacity that sits idle off-peak.

Low PBR (<1.5) suggests underutilized peak service. Tool: Swiftly (now part of Via) provides PBR analysis in their transit analytics suite. Starts at $20k/year.

8. Fare Evasion Rate (FER)

Definition: Percentage of riders who board without paying. Formula: (Unpaid Boardings / Total Boardings) × 100 Benchmark: 5–15% for proof-of-payment systems, 1–5% for barrier systems. Why it matters: Directly impacts revenue.

A 10% FER on a $100M system costs $10M annually. Tool: Bytemark (now part of Siemens) offers fare enforcement analytics. Pricing varies by deployment.

9. Ancillary Revenue per Rider (ARR)

Definition: Total non-fare revenue (ads, concessions, naming rights) divided by total riders. Formula: Total Ancillary Revenue / Total Riders Benchmark: $0.10–$0.50 per rider (U.S.), $0.20–$1.00 (Europe). Why it matters: Diversifies revenue.

Agencies like Transport for London (TfL) generate £200M+ annually from ads and real estate. Tool: JCDecaux (global out-of-home ad firm) partners with transit agencies to optimize ad revenue. Contracts typically share 30–50% of ad revenue.

10. Net Revenue per Passenger Mile (NRPM)

Definition: (Fare revenue - operating cost per passenger mile) per passenger mile. Formula: (Fare Revenue per Passenger Mile - Operating Cost per Passenger Mile) Benchmark: Negative for most U.S. Bus routes (-$0.50 to -$2.00), positive for some rail lines.

Why it matters: The true profitability metric. A negative NRPM means the route is subsidized—which is fine for social service, but must be tracked. Tool: Connexionz (real-time passenger info systems) can calculate NRPM per route.

Pricing custom.

CRO Syndicate — Need a fractional Chief Revenue Officer? CRO Syndicate connects you with vetted fractional and interim revenue leaders. Kory White, Fractional CRO · 25 yrs · $0 to $200M scaled.

👉 Quick Call with Kory White, Fractional CRO · See Kory on LinkedIn · CRO Syndicate

Real Operators

Los Angeles Metro (LA Metro): The second-largest U.S. Bus operator runs 2,000+ buses. They use Farebox Recovery Ratio as a board-level metric, targeting 25–30% for bus and 50–60% for rail. In FY2024, their FRR was 28% overall (source: LA Metro budget). They track Cost per Revenue Hour via Optibus, achieving $180/hour for bus.

Transport for London (TfL): Europe's largest transit agency. TfL's Fare Evasion Rate is 3.5% on the Tube (barrier system) and 12% on buses (proof-of-payment). They use Ancillary Revenue per Rider heavily—£0.45 per rider from ads alone. Their Subsidy per Boarding is £0.80, among the lowest for major cities.

Chicago Transit Authority (CTA): CTA tracks Peak-to-Base Ratio closely. Their rail PBR is 2.8, meaning peak revenue is nearly 3x base. They use Remix to optimize schedules and reduce PBR to 2.2, saving $15M annually in overtime costs.

Singapore LTA: Operates a fully automated fare collection system via SimplyGo (contactless). Their Average Fare per Boarding is S$1.20 (US$0.90), and Farebox Recovery Ratio is 65%—one of the highest globally. They achieve this through dynamic pricing and low evasion (<2%).

Failure Modes

1. Ignoring Peak/Off-Peak Splits: Many agencies track FRR or CPRH as a single number. But a route might have 80% of revenue in 20% of hours (peak). If you don't split by time period, you'll miss that off-peak service is hemorrhaging money. Fix: Always report KPIs by peak, base, and night periods.

2. Over-Relying on Average Fare: Average Fare per Boarding can be misleading if you have many transfer riders. For example, a $2.50 base fare might show AFB of $1.80 if 30% of riders transfer. Fix: Track "fare per unlinked trip" separately from "fare per linked trip."

3. Subsidy Blindness: Agencies often celebrate low Subsidy per Boarding without considering service quality. A $0.50 SPB might mean you're underfunding maintenance or running 30-minute headways. Fix: Pair SPB with on-time performance and customer satisfaction scores.

4. Fare Evasion Under-Counting: Manual counts of evasion are notoriously inaccurate (often 20–30% lower than actual). Fix: Use automated fare gate data or Bytemark's AI-based video analytics to get real rates.

5. Ignoring Capital Costs: Most revenue KPIs focus on operating expenses. But capital costs (vehicles, infrastructure) can be 30–50% of total costs. Fix: Track "total cost per boarding" including depreciation.

Reporting Cadence

KPI	Frequency	Audience	Tool
Farebox Recovery Ratio	Monthly	Board, CFO	TransitPartner
Passenger Revenue per Mile	Weekly	Route planners	Umo
Cost per Revenue Hour	Weekly	Operations	Optibus
Average Fare per Boarding	Daily	Revenue team	Masabi
Subsidy per Boarding	Quarterly	Finance, government	Clever Devices
Revenue per Service Hour	Weekly	Route planners	Remix
Peak-to-Base Ratio	Monthly	Operations	Swiftly
Fare Evasion Rate	Monthly	Security, finance	Bytemark
Ancillary Revenue per Rider	Quarterly	Business development	JCDecaux
Net Revenue per Passenger Mile	Monthly	CFO, board	Connexionz

Best practice: Create a weekly revenue dashboard in Power BI or Tableau that pulls from your fare collection system (e.g., Cubic or Init) and CAD/AVL (e.g., Clever Devices). Update daily for AFB and weekly for CPRH.

30-60-90

Days 1–30: Audit & Baseline

Extract 12 months of data from your fare collection system (e.g., Cubic, Init, or Masabi).
Calculate all 10 KPIs above for the system overall and by route.
Identify top 3 underperforming routes (lowest NRPM and FRR).
Tool: Use Remix to visualize route-level KPI maps.

Days 31–60: Diagnose & Quick Wins

For the 3 underperforming routes, analyze Peak-to-Base Ratio and Cost per Revenue Hour.
If PBR > 4, reduce peak frequency by 10% and shift resources to off-peak (saves 5–10% on labor).
If Fare Evasion Rate > 10% on those routes, deploy Bytemark's video analytics for 2 weeks to get accurate rates.
Tool: Use Optibus to simulate schedule changes.

Days 61–90: Implement & Monitor

Implement schedule changes from day 60 analysis.
Set up weekly KPI reports in Power BI with alerts when FRR drops below 20% or CPRH exceeds $250.
Present a 90-day KPI review to the board showing changes in FRR, SPB, and NRPM.
Tool: Deploy Swiftly for real-time PBR monitoring.

FAQ

? What is a good Farebox Recovery Ratio for a bus system? A typical range is 20–35% for U.S. Bus systems (APTA 2024). European systems often target 40–60%. Below 15% triggers subsidy review.

? How do I calculate Cost per Revenue Hour if I don't have a CAD/AVL system? Use total driver hours from payroll divided by scheduled revenue hours. For a rough estimate, multiply total operating cost by 0.65 (labor share) and divide by revenue hours.

? What's the difference between Revenue per Service Hour and Cost per Revenue Hour? RPSH includes deadhead (non-revenue) time; CPRH excludes it. RPSH is always lower than CPRH. The gap reveals inefficiency—if RPSH is 30% below CPRH, your deadhead time is too high.

? How often should I report Fare Evasion Rate? Monthly for systems with proof-of-payment, quarterly for barrier systems. Use automated counts—manual checks are unreliable.

? Can I use these KPIs for a small rural transit agency? Yes, but adjust benchmarks. Rural bus FRR is often 10–15%, and CPRH can be $100–$150 due to lower wages. Focus on Subsidy per Boarding as the primary metric.

? What's the best tool for an agency with under 50 buses? Umo (by Cubic) offers a basic tier at $0.15/transaction with AFB and PRM tracking. Remix starts at $30k/year for route planning. For a budget option, use Google Data Studio with CSV exports from your fare system.

Sources

flowchart LR A[Fare Collection System<br/>Cubic, Init, Masabi] --> B[Revenue Data] C[CAD/AVL System<br/>Clever Devices, Trapeze] --> D[Service Data] B --> E[KPI Engine<br/>TransitPartner, Umo] D --> E E --> F[Farebox Recovery Ratio] E --> G[Cost per Revenue Hour] E --> H[Average Fare per Boarding] E --> I[Passenger Revenue per Mile] E --> J[Fare Evasion Rate] F --> K[Board Report] G --> L[Ops Dashboard] H --> M[Revenue Team] I --> N[Route Planners] J --> O[Security Team]

flowchart TD P[Day 1-30: Audit] --> Q[Extract 12 months data] Q --> R[Calculate all 10 KPIs] R --> S[Identify top 3 underperforming routes] S --> T[Day 31-60: Diagnose] T --> U[Analyze PBR & CPRH on those routes] U --> V[Simulate schedule changes in Optibus] V --> W[Deploy Bytemark for evasion audit] W --> X[Day 61-90: Implement] X --> Y[Implement schedule changes] Y --> Z[Set up weekly Power BI reports] Z --> AA[Present 90-day KPI review to board] AA --> AB[Ongoing: Monthly FRR & SPB tracking]

Keep reading

![Top 10 Public Transit Revenue KPIs](https://www.pk-anexcelexpert.com/wp-content/uploads/2025/10/Public-Transit-KPI-Dashboard-2.jpg)

### Direct Answer

> **TL;DR:** Public transit revenue KPIs are distinct from commercial SaaS or retail metrics because they blend farebox recovery, subsidy efficiency, and social value. This guide covers the 10 essential KPIs—from Farebox Recovery Ratio to Cost per Revenue Hour—with real benchmarks from agencies like LA Metro and Transport for London. You'll learn how to track them, avoid common failure modes like ignoring peak/off-peak splits, and implement a 30-60-90 reporting plan using tools like Trapeze, Umo, and Remix.

## Why Public Transit Measures Differently

Public transit operates under a mixed-funding model that commercial businesses rarely face. Revenue comes from three streams: **farebox (passenger fares)**, **government subsidies (local, state, federal)**, and **ancillary (advertising, real estate, naming rights)**. Unlike a SaaS company that can A/B test pricing daily, transit agencies must balance cost recovery with social equity—raising fares can push low-income riders off the system.

This creates a unique KPI set. For example, **Farebox Recovery Ratio** (FRR) is the transit equivalent of gross margin, but a "good" FRR varies wildly: U.S. Bus systems average 20–30%, while heavy rail like BART hits 65–75% (per APTA 2024 data). European agencies often target 50%+ due to higher subsidies.

Another difference: **cost allocation**. A transit agency's biggest expense is labor (drivers, mechanics, dispatchers), typically 60–70% of operating costs. So KPIs like **Cost per Revenue Hour** directly measure labor productivity. In contrast, a tech company's biggest cost is often R&D or sales.

Finally, **demand elasticity** matters. A 10% fare increase might reduce ridership by 3–5% in the short term (price elasticity of -0.3 to -0.5, per U.S. DOT studies). This feedback loop means revenue KPIs must be paired with ridership metrics—you can't optimize one without the other.

## The Most Important KPIs to Track

### 1. Farebox Recovery Ratio (FRR)
**Definition:** Total fare revenue divided by total operating expenses.  
**Formula:** `(Fare Revenue / Operating Expenses) × 100`  
**Benchmark:** U.S. Average 30–50% (rail higher, bus lower). European target often 50–70%.  
**Why it matters:** Shows how much of operating costs are covered by riders. Low FRR (<20%) signals over-reliance on subsidies or underpricing.  
**Tool:** **TransitPartner** by Trapeze Group can calculate FRR automatically using fare and expense data. Pricing starts at $25k/year for small agencies.

### 2. Passenger Revenue per Mile (PRM)
**Definition:** Average fare revenue generated per vehicle mile traveled.  
**Formula:** `Total Fare Revenue / Total Vehicle Miles`  
**Benchmark:** $2–$5 per mile for bus, $8–$15 for rail (varies by region).  
**Why it matters:** Measures route-level profitability. A route with PRM < $1 may need restructuring or elimination.  
**Tool:** **Umo** (by Cubic) provides real-time PRM dashboards. Their basic tier costs $0.15 per transaction.

### 3. Cost per Revenue Hour (CPRH)
**Definition:** Total operating cost divided by the number of hours vehicles are in service (revenue hours).  
**Formula:** `Total Operating Cost / Total Revenue Hours`  
**Benchmark:** $150–$250/hour for bus, $300–$500/hour for light rail.  
**Why it matters:** Directly measures labor efficiency. A CPRH above $300 for bus often indicates overtime abuse or inefficient scheduling.  
**Tool:** **Optibus** (now part of Via) optimizes schedules to reduce CPRH. Plans start at $50k/year for a mid-sized agency.

### 4. Average Fare per Boarding (AFB)
**Definition:** Total fare revenue divided by total boardings (unlinked trips).  
**Formula:** `Total Fare Revenue / Total Boardings`  
**Benchmark:** $1.50–$2.50 for bus, $2.50–$4.00 for rail.  
**Why it matters:** Reveals fare structure effectiveness. If AFB is below the base fare, too many discounts or transfers are being used.  
**Tool:** **Masabi**'s Justride platform tracks AFB in real-time. Licensing starts at $100k/year for a city system.

### 5. Subsidy per Boarding (SPB)
**Definition:** Total government subsidy divided by total boardings.  
**Formula:** `(Operating Deficit + Capital Subsidies) / Total Boardings`  
**Benchmark:** $1–$5 per boarding (U.S.), $0.50–$2 (Europe).  
**Why it matters:** Measures taxpayer efficiency. SPB > $5 often triggers political scrutiny.  
**Tool:** **Clever Devices** (now part of Via) integrates subsidy tracking into their CAD/AVL systems. Pricing custom.

### 6. Revenue per Service Hour (RPSH)
**Definition:** Total fare revenue divided by total service hours (including deadhead time).  
**Formula:** `Total Fare Revenue / Total Service Hours`  
**Benchmark:** $100–$200/hour for bus, $200–$400 for rail.  
**Why it matters:** More comprehensive than CPRH because it includes non-revenue time. A low RPSH relative to CPRH indicates poor route design.  
**Tool:** **Remix** (now part of Via) visualizes RPSH by route in their planning tool. Pricing from $30k/year.

### 7. Peak-to-Base Ratio (PBR)
**Definition:** Ratio of peak-hour revenue to base-hour revenue.  
**Formula:** `(Peak Hour Revenue / Base Hour Revenue)`  
**Benchmark:** 1.5–3.0 for bus, 2.0–4.0 for rail.  
**Why it matters:** High PBR (>4) means the agency is spending heavily on peak capacity that sits idle off-peak. Low PBR (<1.5) suggests underutilized peak service.  
**Tool:** **Swiftly** (now part of Via) provides PBR analysis in their transit analytics suite. Starts at $20k/year.

### 8. Fare Evasion Rate (FER)
**Definition:** Percentage of riders who board without paying.  
**Formula:** `(Unpaid Boardings / Total Boardings) × 100`  
**Benchmark:** 5–15% for proof-of-payment systems, 1–5% for barrier systems.  
**Why it matters:** Directly impacts revenue. A 10% FER on a $100M system costs $10M annually.  
**Tool:** **Bytemark** (now part of Siemens) offers fare enforcement analytics. Pricing varies by deployment.

### 9. Ancillary Revenue per Rider (ARR)
**Definition:** Total non-fare revenue (ads, concessions, naming rights) divided by total riders.  
**Formula:** `Total Ancillary Revenue / Total Riders`  
**Benchmark:** $0.10–$0.50 per rider (U.S.), $0.20–$1.00 (Europe).  
**Why it matters:** Diversifies revenue. Agencies like **Transport for London** (TfL) generate £200M+ annually from ads and real estate.  
**Tool:** **JCDecaux** (global out-of-home ad firm) partners with transit agencies to optimize ad revenue. Contracts typically share 30–50% of ad revenue.

### 10. Net Revenue per Passenger Mile (NRPM)
**Definition:** (Fare revenue - operating cost per passenger mile) per passenger mile.  
**Formula:** `(Fare Revenue per Passenger Mile - Operating Cost per Passenger Mile)`  
**Benchmark:** Negative for most U.S. Bus routes (-$0.50 to -$2.00), positive for some rail lines.  
**Why it matters:** The true profitability metric. A negative NRPM means the route is subsidized—which is fine for social service, but must be tracked.  
**Tool:** **Connexionz** (real-time passenger info systems) can calculate NRPM per route. Pricing custom.


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## Real Operators

**Los Angeles Metro (LA Metro):** The second-largest U.S. Bus operator runs 2,000+ buses. They use **Farebox Recovery Ratio** as a board-level metric, targeting 25–30% for bus and 50–60% for rail. In FY2024, their FRR was 28% overall (source: LA Metro budget). They track **Cost per Revenue Hour** via **Optibus**, achieving $180/hour for bus.

**Transport for London (TfL):** Europe's largest transit agency. TfL's **Fare Evasion Rate** is 3.5% on the Tube (barrier system) and 12% on buses (proof-of-payment). They use **Ancillary Revenue per Rider** heavily—£0.45 per rider from ads alone. Their **Subsidy per Boarding** is £0.80, among the lowest for major cities.

**Chicago Transit Authority (CTA):** CTA tracks **Peak-to-Base Ratio** closely. Their rail PBR is 2.8, meaning peak revenue is nearly 3x base. They use **Remix** to optimize schedules and reduce PBR to 2.2, saving $15M annually in overtime costs.

**Singapore LTA:** Operates a fully automated fare collection system via **SimplyGo** (contactless). Their **Average Fare per Boarding** is S$1.20 (US$0.90), and **Farebox Recovery Ratio** is 65%—one of the highest globally. They achieve this through dynamic pricing and low evasion (<2%).

## Failure Modes

**1. Ignoring Peak/Off-Peak Splits:** Many agencies track **FRR** or **CPRH** as a single number. But a route might have 80% of revenue in 20% of hours (peak). If you don't split by time period, you'll miss that off-peak service is hemorrhaging money. **Fix:** Always report KPIs by peak, base, and night periods.

**2. Over-Relying on Average Fare:** **Average Fare per Boarding** can be misleading if you have many transfer riders. For example, a $2.50 base fare might show AFB of $1.80 if 30% of riders transfer. **Fix:** Track "fare per unlinked trip" separately from "fare per linked trip."

**3. Subsidy Blindness:** Agencies often celebrate low **Subsidy per Boarding** without considering service quality. A $0.50 SPB might mean you're underfunding maintenance or running 30-minute headways. **Fix:** Pair SPB with on-time performance and customer satisfaction scores.

**4. Fare Evasion Under-Counting:** Manual counts of evasion are notoriously inaccurate (often 20–30% lower than actual). **Fix:** Use automated fare gate data or **Bytemark**'s AI-based video analytics to get real rates.

**5. Ignoring Capital Costs:** Most revenue KPIs focus on operating expenses. But capital costs (vehicles, infrastructure) can be 30–50% of total costs. **Fix:** Track "total cost per boarding" including depreciation.

## Reporting Cadence

| KPI | Frequency | Audience | Tool |
|-----|-----------|----------|------|
| Farebox Recovery Ratio | Monthly | Board, CFO | **TransitPartner** |
| Passenger Revenue per Mile | Weekly | Route planners | **Umo** |
| Cost per Revenue Hour | Weekly | Operations | **Optibus** |
| Average Fare per Boarding | Daily | Revenue team | **Masabi** |
| Subsidy per Boarding | Quarterly | Finance, government | **Clever Devices** |
| Revenue per Service Hour | Weekly | Route planners | **Remix** |
| Peak-to-Base Ratio | Monthly | Operations | **Swiftly** |
| Fare Evasion Rate | Monthly | Security, finance | **Bytemark** |
| Ancillary Revenue per Rider | Quarterly | Business development | **JCDecaux** |
| Net Revenue per Passenger Mile | Monthly | CFO, board | **Connexionz** |

**Best practice:** Create a **weekly revenue dashboard** in **Power BI** or **Tableau** that pulls from your fare collection system (e.g., **Cubic** or **Init**) and CAD/AVL (e.g., **Clever Devices**). Update daily for AFB and weekly for CPRH.

## 30-60-90

**Days 1–30: Audit & Baseline**
- Extract 12 months of data from your fare collection system (e.g., **Cubic**, **Init**, or **Masabi**).
- Calculate all 10 KPIs above for the system overall and by route.
- Identify top 3 underperforming routes (lowest **NRPM** and **FRR**).
- **Tool:** Use **Remix** to visualize route-level KPI maps.

**Days 31–60: Diagnose & Quick Wins**
- For the 3 underperforming routes, analyze **Peak-to-Base Ratio** and **Cost per Revenue Hour**.
- If PBR > 4, reduce peak frequency by 10% and shift resources to off-peak (saves 5–10% on labor).
- If **Fare Evasion Rate** > 10% on those routes, deploy **Bytemark**'s video analytics for 2 weeks to get accurate rates.
- **Tool:** Use **Optibus** to simulate schedule changes.

**Days 61–90: Implement & Monitor**
- Implement schedule changes from day 60 analysis.
- Set up **weekly KPI reports** in **Power BI** with alerts when **FRR** drops below 20% or **CPRH** exceeds $250.
- Present a **90-day KPI review** to the board showing changes in **FRR**, **SPB**, and **NRPM**.
- **Tool:** Deploy **Swiftly** for real-time PBR monitoring.

## FAQ

**? What is a good Farebox Recovery Ratio for a bus system?**  
A typical range is 20–35% for U.S. Bus systems (APTA 2024). European systems often target 40–60%. Below 15% triggers subsidy review.

**? How do I calculate Cost per Revenue Hour if I don't have a CAD/AVL system?**  
Use total driver hours from payroll divided by scheduled revenue hours. For a rough estimate, multiply total operating cost by 0.65 (labor share) and divide by revenue hours.

**? What's the difference between Revenue per Service Hour and Cost per Revenue Hour?**  
RPSH includes deadhead (non-revenue) time; CPRH excludes it. RPSH is always lower than CPRH. The gap reveals inefficiency—if RPSH is 30% below CPRH, your deadhead time is too high.

**? How often should I report Fare Evasion Rate?**  
Monthly for systems with proof-of-payment, quarterly for barrier systems. Use automated counts—manual checks are unreliable.

**? Can I use these KPIs for a small rural transit agency?**  
Yes, but adjust benchmarks. Rural bus **FRR** is often 10–15%, and **CPRH** can be $100–$150 due to lower wages. Focus on **Subsidy per Boarding** as the primary metric.

**? What's the best tool for an agency with under 50 buses?**  
**Umo** (by Cubic) offers a basic tier at $0.15/transaction with AFB and PRM tracking. **Remix** starts at $30k/year for route planning. For a budget option, use **Google Data Studio** with CSV exports from your fare system.

## Sources

- [APTA 2024 Public Transportation Fact Book](https://www.apta.com/research-technical-resources/transit-statistics/public-transportation-fact-book/)
- [LA Metro FY2024 Budget (pages 45-52)](https://www.metro.net/about/finance-budget/)
- [Transport for London Annual Report 2023-24](https://tfl.gov.uk/corporate/publications-and-reports/annual-report)
- [U.S. DOT Transit Economics Report (price elasticity data)](https://www.transit.dot.gov/regulations-and-guidance/transit-economics)
- [Trapeze Group TransitPartner pricing](https://www.trapezegroup.com/transitpartner)
- [Cubic Umo pricing tiers](https://www.umoticketing.com/pricing)
- [Optibus (Via) schedule optimization case studies](https://www.optibus.com/case-studies)
- [Masabi Justride platform overview](https://www.masabi.com/justride)
- [Bytemark (Siemens) fare enforcement analytics](https://www.bytemark.com/solutions/enforcement)
- [Remix (Via) transit planning pricing](https://www.remix.com/pricing)

```mermaid
flowchart LR
    A[Fare Collection System<br/>Cubic, Init, Masabi] --> B[Revenue Data]
    C[CAD/AVL System<br/>Clever Devices, Trapeze] --> D[Service Data]
    B --> E[KPI Engine<br/>TransitPartner, Umo]
    D --> E
    E --> F[Farebox Recovery Ratio]
    E --> G[Cost per Revenue Hour]
    E --> H[Average Fare per Boarding]
    E --> I[Passenger Revenue per Mile]
    E --> J[Fare Evasion Rate]
    F --> K[Board Report]
    G --> L[Ops Dashboard]
    H --> M[Revenue Team]
    I --> N[Route Planners]
    J --> O[Security Team]
```

```mermaid
flowchart TD
    P[Day 1-30: Audit] --> Q[Extract 12 months data]
    Q --> R[Calculate all 10 KPIs]
    R --> S[Identify top 3 underperforming routes]
    S --> T[Day 31-60: Diagnose]
    T --> U[Analyze PBR & CPRH on those routes]
    U --> V[Simulate schedule changes in Optibus]
    V --> W[Deploy Bytemark for evasion audit]
    W --> X[Day 61-90: Implement]
    X --> Y[Implement schedule changes]
    Y --> Z[Set up weekly Power BI reports]
    Z --> AA[Present 90-day KPI review to board]
    AA --> AB[Ongoing: Monthly FRR & SPB tracking]
```

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Industry KPIs · SaaSThe 9 sales KPIs that matter for SaaS

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