You can't fix what you don't measure. Most B2B companies track dozens of financial metrics — MRR, ARR, NRR, churn, LTV, CAC — but zero revenue leakage KPIs. The result: revenue leakage runs 3-5% of ARR while finance teams have no visibility into it.
These 7 KPIs create that visibility. Each includes a definition, calculation method, industry benchmark, and target for best-in-class performance.
1. Leak Rate
Definition: Revenue leakage as a percentage of total revenue.
Calculation: (Expected revenue - Actual collected revenue) / Expected revenue × 100
Benchmarks:
- Best-in-class: <0.5%
- Industry median: 3-5%
- Red flag: >7%
Leak rate is the master metric. It tells you the total magnitude of the problem. If you only track one revenue leakage KPI, track this one.
The challenge: calculating leak rate requires knowing your expected revenue, which means running the detection analysis. Companies that don't actively detect leakage can't calculate this metric — which is why most companies don't know their leak rate.
2. Detection Latency
Definition: Average time from when a leak starts to when it's detected.
Calculation: Average of (detection date - leak start date) across all detected leaks in the period.
Benchmarks:
- Best-in-class: <24 hours (continuous monitoring)
- Industry median: 45-90 days (quarterly audit cycle)
- Red flag: >90 days (no systematic detection)
Detection latency directly determines financial impact. A leak detected after 1 day costs 1 day's worth of revenue. The same leak detected after 90 days costs 90 days' worth — across every affected customer.
Moving from quarterly audits (90-day latency) to continuous monitoring (<24-hour latency) reduces the financial impact per leak by 90x.
3. Recovery Rate
Definition: Percentage of detected revenue leakage that is successfully recovered.
Calculation: (Revenue recovered from detected leaks / Total detected leakage) × 100
Benchmarks:
- Best-in-class: >85%
- Industry median: 60-70%
- Red flag: <40%
Not all detected leakage can be recovered. Some has already been written off, some involves customers who have churned, and some would damage relationships to collect retroactively. But a recovery rate below 60% usually indicates process issues — leaks are detected but not acted on quickly enough.
4. Time-to-Resolution
Definition: Average days from leak detection to leak remediation (fix applied).
Calculation: Average of (resolution date - detection date) across all resolved leaks.
Benchmarks:
- Best-in-class: <7 days
- Industry median: 21-45 days
- Red flag: >60 days
Every day between detection and resolution is a day the leak continues to drain revenue. Long resolution times often indicate organizational friction — the person who detects the leak isn't the person who can fix it, and handoffs create delays.
5. Recurrence Rate
Definition: Percentage of fixed leaks that reappear within 6 months (same category, same or different accounts).
Calculation: (Number of recurring leaks / Total fixed leaks) × 100
Benchmarks:
- Best-in-class: <5%
- Industry median: 15-25%
- Red flag: >30%
High recurrence means you're fixing symptoms, not root causes. If the same category of leak keeps appearing — pricing configuration errors, discount expiration failures, contract compliance gaps — the underlying process that creates them hasn't been addressed.
6. False Positive Rate
Definition: Percentage of flagged findings that turn out not to be actual leaks upon investigation.
Calculation: (False positive findings / Total flagged findings) × 100
Benchmarks:
- Best-in-class: <10%
- Industry median: 20-30%
- Red flag: >40%
False positives erode trust. A finance team that receives 50 alerts with a 40% false positive rate will stop investigating after the first few weeks. The detection system becomes noise. Accuracy matters more than volume — 20 high-confidence findings are more valuable than 100 mixed-confidence alerts.
7. Category Coverage
Definition: How many of the 12 revenue leak categories your organization actively monitors.
Benchmarks:
- Best-in-class: 12/12
- Industry median: 2-3/12
- Red flag: 0/12 (no systematic monitoring)
Most companies only monitor the most obvious categories (billing errors, failed payments) while ignoring the rest. The unmonitored categories — contract compliance, entitlement enforcement, usage metering — often contain larger leaks precisely because nobody has been looking.
Building Your Revenue Leakage Dashboard
Start with two KPIs: Leak Rate and Detection Latency. They answer the two most important questions: "How big is the problem?" and "How fast are we catching it?"
Add Recovery Rate and Time-to-Resolution once you have detection in place. They measure the effectiveness of your remediation process.
Add Recurrence Rate, False Positive Rate, and Category Coverage as your program matures. They measure the quality and completeness of your detection system.
Start Measuring Your Revenue Leakage →
For the framework behind these metrics, see our guide to revenue leakage analysis. New to the topic? Start with our complete guide to revenue leakage.