What Benchmarks Should RevOps Use?
A stage-aware benchmarking kit for funnel health, speed, accuracy, efficiency, and cost—complete with formulas, ranges, and a printable checklist.
Set benchmarks where they drive decisions: funnel conversion & velocity, data accuracy & sync health, operational efficiency, forecast quality, and unit economics. Anchor each metric to a clear formula, stage-appropriate range, and a promotion/rollback rule so teams know when to ship changes—or stop.
Core RevOps benchmarks (with formulas & stage ranges)
| Category | Metric | Formula | Typical Range (PLG/SMB → Enterprise) | Notes |
|---|---|---|---|---|
| Funnel | Lead→MQL Conversion | MQL ÷ Leads | 10–25% → 5–15% | Tighter ICP lowers volume but raises quality. |
| Funnel | MQL→SQL (or SAL) | SQL ÷ MQL | 25–45% → 15–30% | Guard with SLA on response time. |
| Velocity | Speed to Lead | Median minutes to first touch | < 10m → < 1h | Use alerts + round-robin; track after-hours. |
| Velocity | Cycle Time | Close date – create date | 14–45d → 60–120d | View by segment & deal size. |
| Accuracy | Forecast Accuracy | 1 – |Forecast – Actual| ÷ Actual | ±5–10% (late) / ±10–20% (mid) | Gate stage promotions on criteria. |
| Data Quality | Field Completeness (core) | Non-null ÷ eligible | ≥ 98% | Dictionary + write rules required. |
| Integration | Cross-System Variance ($) | |CRM – Finance| ÷ Finance | ≤ 1–2% monthly | Reconcile by cohort & currency. |
| Efficiency | MTTR (RevOps incidents) | Median resolve time | Trending down | Instrument severity & alerts. |
| Adoption | Active Users / Eligible | Active ÷ eligible users | 60–80% | Segment by role; require >70% at GA. |
| Unit Economics | CAC Payback | Sales & Mktg spend ÷ Net new gross margin | 6–18 months | Use gross margin, not revenue. |
| Retention | Net Revenue Retention (NRR) | (Starting ARR + Expansion – Churn – Contraction) ÷ Starting ARR | 100–120% (SaaS best-in-class) | Cohort by segment & product. |
How to set targets (and avoid “benchmark theater”)
- Baseline first, then benchmark: measure your last 3–6 months by segment; set targets at baseline + trend lift.
- Context matters: PLG/SMB motions convert higher, enterprise cycles longer—tune by ACV, region, and product.
- Gate launches: define promotion/rollback criteria (e.g., “ship if MQL→SQL ≥ baseline and no latency regression”).
- Publish a one-page scorecard: metric, owner, formula, target, current, trend, next action.
Printable checklist
- Metric has a formula and an owner
- Target tied to stage/segment and SLA
- Baseline + 3-month trend visible to leaders
- Promotion/rollback criteria defined
- Weekly review: actions attached to misses
Frequently Asked Questions
Should we use public benchmarks or internal baselines?
Use both. Public ranges give context; internal baselines set realistic targets and help you prove lift over time.
How often should targets change?
Quarterly for most metrics; monthly for operational SLAs (speed to lead, sync errors). Lock annual guardrails for CAC payback and NRR.
What if Marketing and Sales definitions differ?
Adopt a single data dictionary with stage entry/exit criteria, provenance, and allowed writers. No shared dictionary = unreliable benchmarks.
How do we benchmark across regions or products?
Use cohort views—separate scorecards per region/product with common formulas. Roll up only after segment-level targets are healthy.
Related resources & next steps
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