RevOps KPIs is the key performance indicators that measure revenue operations effectiveness across the full customer lifecycle. Unlike departmental metrics that optimize one team, RevOps KPIs track the health of the entire revenue engine — from pipeline generation through customer expansion.
The best RevOps teams track 8-12 core KPIs, not 50.
The most important RevOps KPI isn't any single metric — it's the relationship between pipeline velocity, win rate, and average deal size. When these three move together, the revenue engine is healthy. When they diverge, something is broken at a handoff point.
Pipeline & Funnel KPIs
These measure how efficiently you generate, qualify, and move deals through the funnel. If you track nothing else, track these.
1. Pipeline Velocity
Formula: (Number of Opportunities x Win Rate x Average Deal Size) / Sales Cycle Length
The single most comprehensive revenue health metric. It captures volume, quality, value, and speed in one number. Track it monthly and quarterly. A declining velocity with a growing pipeline means your funnel is getting clogged.
2. Pipeline Coverage Ratio
Target: 3x–4x of quota for most B2B SaaS
Total qualified pipeline divided by revenue target. Below 3x and you're relying on heroics. Above 5x and you're probably qualifying too loosely. This number should be stable — wild swings indicate inconsistent lead generation or forecasting.
3. Lead-to-Opportunity Conversion Rate
Benchmark: 13%–25% depending on source and segment
The handoff metric. When this drops, it's usually a qualification problem (Marketing and Sales disagree on what "qualified" means) or a response time problem. Track by source to identify which channels produce real pipeline vs noise.
4. Stage-to-Stage Conversion Rates
Don't just track top and bottom of funnel. Measure conversion at every pipeline stage. The stage with the biggest drop-off is your biggest leverage point. Most companies find it's Stage 2→3 (initial interest → serious evaluation) where deals die quietly.
5. Marketing Qualified Lead (MQL) to SQL Rate
Benchmark: 25%–40%
The peace treaty between Marketing and Sales. When this rate is too low, Sales ignores marketing leads. When it's too high, the bar is so strict that Marketing can't hit volume targets. RevOps owns the definition and the measurement.
Revenue KPIs
6. Win Rate
Benchmark: 20%–30% for enterprise SaaS, 10%–15% for SMB high-volume
Closed won / (closed won + closed lost). Exclude stale or disqualified deals — they inflate the denominator and mask real performance. Track by rep, segment, source, and deal size to find patterns.
7. Average Deal Size (ACV)
Track the trend, not just the number. Rising ACV with stable win rates = healthy upmarket motion. Rising ACV with declining win rates = your team is chasing deals they can't close.
8. Net Revenue Retention (NRR)
Benchmark: 100%–130% for best-in-class SaaS
Revenue from existing customers including expansion minus churn, divided by starting revenue. This is the KPI that VCs and board members care most about. Below 100% means you're leaking revenue faster than you can close new deals.
9. Customer Acquisition Cost (CAC)
Formula: Total sales + marketing spend / new customers acquired
Include everything: salaries, tools, advertising, events, content. RevOps is uniquely positioned to calculate this accurately because you see the full cost picture. Track CAC payback period (months to recoup acquisition cost) alongside it.
10. Revenue Per Rep (Productivity)
Annual revenue / number of quota-carrying reps. This is the efficiency metric leadership watches. Compare against compensation data — if you're paying reps $150K OTE and they're producing $400K, the math doesn't work long-term.
Sales Efficiency KPIs
11. Sales Cycle Length
Benchmark: 30–60 days (SMB), 90–180 days (enterprise)
Measure from opportunity creation to close. Track by segment, not just overall average — one large enterprise deal can skew the number. A lengthening cycle often signals competitive pressure or a buying committee problem.
12. Forecast Accuracy
Target: Within 10% of actual results
Commit vs actual, measured monthly and quarterly. This is a RevOps credibility metric — if your forecasts are consistently off, leadership loses trust in the numbers. Track accuracy by category (commit, best case, pipeline) to calibrate each.
13. Quota Attainment Distribution
What percentage of reps hit quota? The distribution matters more than the average. If 30% of reps carry 70% of revenue, you have a hiring, enablement, or territory problem — not a market problem.
14. Activity-to-Outcome Ratios
Calls per meeting, meetings per opportunity, proposals per close. These connect leading indicators (activity) to lagging indicators (revenue). When the ratios shift, you catch problems before they hit the forecast.
15. Speed to Lead
Target: Under 5 minutes for inbound demo requests
Time from lead submission to first sales contact. Research consistently shows response time is the #1 predictor of conversion for inbound leads. If your average is over 30 minutes, you're losing deals before they start.
Customer & Retention KPIs
16. Gross Revenue Churn
Revenue lost from cancellations and downgrades, expressed as a monthly or annual rate. Track the absolute number and the trend. Sudden spikes usually trace back to a specific cohort, product issue, or competitive threat.
17. Expansion Revenue Rate
Revenue from upsells, cross-sells, and seat expansions as a percentage of starting revenue. This is where the post-sale ops function earns its keep. If your expansion rate is below 10% annually, you're leaving money on the table.
18. Time to Value
Days from contract signed to customer achieving their first meaningful outcome. This bridges the Sales-to-CS handoff. A long time to value predicts churn — customers who don't see results in the first 90 days are 3x more likely to leave.
19. Customer Health Score
Composite score combining product usage, support tickets, NPS/CSAT, billing status, and engagement signals. RevOps builds the model; CS acts on it. The best health scores predict churn 60+ days out, giving CS time to intervene.
Data Quality & Operational KPIs
20. CRM Data Completeness
Percentage of required fields populated across all pipeline stages. If your Stage 3 opportunities are missing next steps, close dates, or decision-maker contacts, your forecast is fiction. Set a target (95%+) and report on it weekly.
21. Duplicate Rate
Percentage of duplicate records in your CRM (accounts, contacts, leads). Above 10% and you're sending mixed signals to prospects, miscounting pipeline, and confusing attribution. Most CRM tools have native dedup features — use them.
22. Integration Uptime
Percentage of time your key integrations (CRM ↔ MAP, CRM ↔ billing, data warehouse sync) are functioning. When integrations break silently, data stops flowing and nobody notices until the monthly report looks wrong. Monitor proactively.
23. Tool Adoption Rate
Percentage of licensed users actively using each tool in your tech stack. If you're paying for 100 Gong seats and 40 reps log in monthly, that's a $60K/year problem. Track weekly active users for every tool with a per-seat license.
24. Process Compliance Rate
How often do reps follow the defined process? Stage progression rules, required fields, activity logging, next steps documentation. Low compliance usually means the process is too burdensome, not that reps are lazy.
25. Report/Dashboard Usage
Which reports are people actually looking at? If you built 50 dashboards and 5 get viewed regularly, the other 45 are maintenance burden with zero value. Kill them.
Building Your RevOps Dashboard
Don't track all 25. Pick the 8-12 that matter most for your business stage and GTM motion. A practical framework:
- Early-stage (seed/Series A): Pipeline velocity, win rate, sales cycle length, CAC, lead conversion rate. Keep it simple — you're learning what works.
- Growth (Series B/C): Add forecast accuracy, quota attainment distribution, NRR, speed to lead, CRM completeness. You're scaling what works.
- Scale (Series D+/Public): Full suite including tool adoption, integration uptime, process compliance, expansion revenue. You're optimizing the machine.
Every KPI should have an owner, a target, and a cadence. If nobody's accountable for a metric, stop tracking it.
Common KPI Mistakes
- Vanity metrics. Total pipeline created sounds great in an all-hands. But if 60% of it is unqualified, you're celebrating fiction. Weight metrics by quality.
- Lagging-only dashboards. If every metric you track is a result (revenue, churn, win rate), you're driving by looking in the rearview mirror. Mix in leading indicators (pipeline created, activity ratios, speed to lead).
- No context. "Win rate is 22%" means nothing without the trend, the segment breakdown, and the competitive context. Always present KPIs with comparison data.
- Too many metrics. If your weekly pipeline review deck has 40 slides, nobody's reading past slide 5. Ruthlessly cut to the metrics that drive decisions.
For more on the RevOps function and how metrics fit into the broader role, see What Is RevOps? and the career path guide. Check our salary data to benchmark Director-level and VP-level comp for roles where KPI ownership is a core responsibility.