Revenue portfolio benchmarking is the discipline by which a PE or VC Operating Partner compares its portfolio companies against each other on a consistent set of commercial and operational metrics, in order to extract cross-portfolio patterns, identify at-risk underperformers, and feed every CEO conversation with an actionable reference grid. It is the most underused lever of the OP function: most funds collect metrics company by company without ever putting them side by side, missing out on 80% of the value their portfolio could generate as signal.
In funds that support 6 to 15 B2B scale-ups between €5M and €150M ARR, each portfolio company produces around ten structuring metrics every quarter. Cross-referenced properly, these metrics form a strategic asset: they let the OP spot in two minutes an anomaly in a portfolio company that would go unnoticed in its own internal reporting. They give the CEO a mirror they have nowhere else, since public benchmarks are too generic to be useful. And they transform the OP's posture, from observer to advisor armed with proprietary data.
This guide details the 15 revenue metrics to systematically benchmark in a B2B portfolio, the normalization logic that allows comparison of portfolio companies at different stages and with different models, the four quadrants of an OP scorecard usable in IC, the quarterly portfolio review cadence to put in place, the four risks of a poorly designed benchmark, and a ready-to-use grid you can apply starting with your next investment committee.
Key Takeaways
- 15 core metrics cover 90% of the useful signal: ARR growth, NRR, GRR, CAC payback, magic number, Rule of 40, LTV/CAC, sales efficiency, pipeline coverage, win rate, quota attainment, productivity by role, ACV, forecast accuracy, stack cost.
- Normalization is 80% of the work: a raw metric compared between two portfolio companies at different stages means nothing. The cohort a company belongs to determines the interpretation.
- Three cohort axes: stage (seed, Series A, B, growth, late), segment (SMB, mid-market, enterprise), model (PLG, sales-led, hybrid). Each portfolio company belongs to exactly one cohort on each axis.
- Scorecard in 4 quadrants: top, upper mid, lower mid, bottom. Each metric positions the portfolio company, and the aggregated pattern shows whether the company is advancing or holding back the thesis.
- Non-negotiable quarterly cadence: a 2-hour portfolio review, 1 slide per portfolio company, 1 slide on cross-portfolio patterns, 1 slide on IC alerts. Nothing survives without cadence.
- The benchmark is a mirror, never a judgment: the standard phrasing is not "you're in the bottom quartile" but "here's how 12 comparable portfolio companies rank on this metric, what do you read into this gap?"
- Patterns matter more than gaps: what differentiates a top-quartile company from a bottom-quartile one is almost never a single metric, it's a combination of 3 to 5 reinforcing signals.
"The portfolio managers who create the most value are not the ones who know the most things about each portfolio company. They are the ones who know the right things about the whole portfolio and deliver them at the right time to the right CEO."
McKinsey & Company, Private Equity Operating Partner Report (2024 edition)
Why the Portfolio Benchmark Is a Strategic OP Asset
An Operating Partner who supports 10 portfolio companies has an observation base that no CEO, no consultant, and no board-member-only investor can replicate. That base is precisely the sum of the metrics that pass through their hands every month. And yet, in most funds we observe, these metrics live in 10 separate decks, never consolidated, never normalized, never interpreted in relative terms. This is the structuring anomaly that the benchmark corrects.
The Pattern Library: The Fund's Real Differentiating Product
In the most disciplined funds, the portfolio benchmark is not a one-off exercise: it's a living asset, updated quarterly, that feeds both the investment thesis for future portfolio companies and the value creation plans in progress. This pattern library is what distinguishes a mature fund from one that manages company by company. Our Revenue Health Score diagnostics conducted with B2B scale-ups show that portfolio companies supported by funds with a structured pattern library outperform by an average of 15 to 25 points on the fund's target MOIC at exit, at equivalent stage and segment.
Early Signal on Underperformers
An underperformer never reveals itself abruptly. It drifts, quarter after quarter, on two or three metrics that no one connects. The portfolio benchmark acts as an early warning system. When a portfolio company slides from top quartile to upper mid on NRR, then on win rate, over two consecutive quarters, the OP has a signal the CEO won't see alone. Acting at that moment, twelve months ahead of when the gap becomes structural, is exactly the OP's role.
Credibility in CEO Conversations
A CEO who receives an abstract recommendation from their OP can brush it aside by saying "you don't understand my reality." A CEO who receives the same recommendation backed by a portfolio benchmark can no longer dismiss it as easily, because the reference point is tangible. Portfolio data is the OP's silent weapon: it builds legitimacy without ever overplaying it. See B2B Revenue KPIs: CEO Indicators for the common vocabulary to establish in every portfolio company.
The Effect on Ongoing Diligences
A mature portfolio benchmark also feeds ongoing diligences. An OP who sees a scale-up coming in claiming a 130% NRR can, by cross-referencing 12 comparable portfolio companies, assess within two hours whether the figure is plausible, whether the underlying assumptions hold up, and whether the announced trajectory is achievable. This rapid assessment capability is what distinguishes funds that win the right deals from those that overpay for the wrong ones.
| What the Benchmark Produces | What Its Absence Produces |
|---|---|
| Early signal on drifting underperformers | Late discovery, often at the board where the gap becomes political |
| Credibility in CEO conversations | Advice perceived as abstract or theoretical |
| Accelerated diligence assessment | Due diligences that redo the same work every time |
| Pattern library capitalized over the fund's lifetime | Knowledge scattered in the OP's head |
| OP time prioritization by portfolio company | Time allocated to the loudest, not the riskiest |
| Relative reading of metrics | Absolute interpretation, often misleading |
The 15 Core Revenue Metrics to Benchmark
The classic trap is wanting to benchmark too many metrics. A portfolio that compares 40 KPIs across companies produces noise, not signal. The discipline is to select 15 robust, precisely defined metrics, and to stick with that selection over time. These 15 metrics cover the three structuring dimensions of a B2B revenue engine: growth, efficiency, execution.
The 5 Growth Metrics
Growth is the dimension the fund monitors most closely, because it determines exit valuation and market perception.
| Metric | Definition | Source | Measurement Frequency |
|---|---|---|---|
| ARR growth rate | YoY ARR growth at constant scope | CFO / Reporting | Monthly |
| NRR | (Starting ARR + expansion - downgrade - churn) / Starting ARR, on a 12-month cohort | CS + Finance Reporting | Quarterly |
| GRR | (Starting ARR - downgrade - churn) / Starting ARR, excluding expansion | CS + Finance Reporting | Quarterly |
| ACV evolution | Change in average new-logo deal size over a trailing 12 months | CRM | Quarterly |
| Pipeline coverage | Qualified pipeline / sales quota for the current quarter | CRM + RevOps | Weekly |
For a rigorous benchmark, NRR must be recalculated using a single methodology across all portfolio companies: same horizon (12 months), same segmentation (by signature cohort, not calendar), same treatment of discounts and commercial concessions. Without this standardization, a reported 115% NRR in one portfolio company can correspond to a real 102% NRR in another.
The 6 Efficiency Metrics
Efficiency tells you whether growth is sustainable or whether it consumes more than it produces. It's the dimension most correlated with exit valuation, and the one most often poorly measured internally.
| Metric | Definition | Formula | Top-Quartile Target |
|---|---|---|---|
| CAC payback | Months needed to recover CAC via gross margin | CAC / (New ARR × gross margin / 12) | < 12 months |
| Magic number | Quarterly sales & marketing efficiency | (New ARR Q × 4) / (S&M spend Q-1) | > 1 |
| Rule of 40 | Sum of ARR growth + EBITDA margin (or FCF) | Growth% + Margin% | > 40 |
| LTV/CAC | Customer value / acquisition cost ratio | (ARR × gross margin × 1/churn) / CAC | > 3x |
| Sales efficiency ratio | New ARR / direct sales cost | Net new ARR / Sales direct cost | > 0.6 |
| Stack cost % ARR | Total cost of revenue tools / ARR | Sum(tool licenses) / ARR | < 3% |
The B2B CAC methodology must be uniformly enforced: full-loaded (including marketing, sales, BDR, tools, events), not just paid media. A CAC payback compared between two portfolio companies that don't calculate CAC on the same basis produces noisy signal.
The 4 Execution Metrics
Execution measures the day-to-day quality of the sales machine. These metrics move faster than growth metrics and are the best predictors of quarterly metrics 6 months out.
| Metric | Definition | Alert Threshold |
|---|---|---|
| Win rate | Deals won / qualified deals over a trailing 12 months | < 20% |
| Quota attainment | % of AEs hitting their quarterly quota | < 50% |
| Forecast accuracy | Absolute variance between forecast and actual over 4 quarters | > 15% |
| Productivity by role | ARR generated per AE, BDR, CSM | Depends on stage |
Forecast accuracy is the execution metric most revealing of a structural problem. A portfolio company with a forecast accuracy variance above 20% almost always has a deeper pipeline hygiene or qualification problem.
Normalization: 80% of the Benchmarking Work
Benchmarking without normalizing is the mistake that discredits the exercise in a single session. A 60% ARR growth rate can be remarkable for a Series B portfolio company at €25M ARR, and weak for a seed-stage company at €3M ARR. Comparing the two without separating them by cohort produces noise that discourages CEOs and discredits the OP.
The 3 Cohort Axes
Each portfolio company simultaneously belongs to a cohort on each of the following three axes. The intersection defines the relevant comparison group for that company on each metric.
| Axis | Cohorts | Classification Criterion |
|---|---|---|
| Stage | Seed, Series A, Series B, Growth, Late | ARR + last round raised |
| Segment | SMB, Mid-market, Enterprise, Mixed | Median ACV |
| Model | Pure PLG, Pure Sales-led, Hybrid, Channel-first | Revenue acquisition mix |
Cohort Logic by Stage
Key metrics don't have the same thresholds across stages. 150% ARR growth is expected at seed, exceptional at Series B, and suspicious at late stage. The table below gives the orders of magnitude observed in our diagnostics and in the sector's reference studies.
| Stage | Typical ARR | Target Growth | Target NRR | Target Magic Number |
|---|---|---|---|---|
| Seed | €0 to €2M | 200%+ | 100-110% | N/A (noise) |
| Series A | €2M to €10M | 100-150% | 105-115% | 0.8-1.2 |
| Series B | €10M to €30M | 80-100% | 110-120% | 1.0-1.4 |
| Growth | €30M to €80M | 50-80% | 115-125% | 0.9-1.3 |
| Late | €80M+ | 30-50% | 110-120% | 0.7-1.1 |
An OP who applies the same thresholds to all portfolio companies, regardless of stage, produces false conclusions that destroy their credibility from the very first review.
Cohort Logic by Segment
Segment determines the thresholds for CAC payback, win rate, and pipeline coverage. An SMB portfolio company with an 8-month CAC payback is average. An enterprise portfolio company with the same CAC payback is remarkable.
| Segment | Median ACV | Typical Win Rate | Typical CAC Payback | Typical Cycle |
|---|---|---|---|---|
| SMB | < €10K | 25-35% | 3-9 months | 2-6 weeks |
| Mid-market | €10K to €100K | 20-30% | 9-18 months | 2-4 months |
| Enterprise | > €100K | 15-25% | 18-30 months | 6-12 months |
| Mixed | Variable | To be analyzed by sub-segment | To be separated | To be separated |
Cohort Logic by Model
The acquisition model radically changes how BDR, win rate, and pipeline coverage metrics should be read.
| Model | Target Pipeline Coverage | BDR Contribution | PLG Contribution | Typical Inbound Win Rate |
|---|---|---|---|---|
| Pure PLG | 2x (via signup) | 0% | 80%+ | 40-50% |
| Pure Sales-led | 3-4x | 40-60% | < 10% | 15-25% |
| Hybrid | 3x | 20-30% | 30-50% | 25-35% |
| Channel-first | 2-3x | 10-20% | 10-20% | 20-30% |
Sector Adjustment
Within the same stage, segment, and model, the industry can still introduce bias. Highly regulated verticals (healthcare, banking, insurance) mechanically have longer cycles and lower win rates. A refined benchmark systematically notes the portfolio company's vertical and applies a qualitative adjustment coefficient. See 20 B2B Revenue Standards for the sector reference framework.
The Operating Partner Scorecard: 15 Metrics × 4 Quadrants
Once normalization is done, each portfolio company positions itself on each of the 15 metrics within one of the four quadrants of its cohort. The scorecard aggregates this information into a single view the OP can read in 30 seconds before any board meeting or IC.
The 4 Quadrants
| Quadrant | Definition | Signal |
|---|---|---|
| Top | Top 25% of the cohort | Best practice to spread across the portfolio |
| Upper mid | 25-50% | Solid, limited short-term leverage |
| Lower mid | 50-75% | Priority improvement zone |
| Bottom | Bottom 25% | Structural risk, immediate action |
The Aggregated Reading
The scorecard's real value doesn't come from a single metric but from the combination of the 15 positions. A typical alert pattern looks like: ARR growth upper mid, NRR lower mid, CAC payback bottom, win rate bottom, forecast accuracy bottom. This cluster almost always reflects a sales hygiene problem combined with erosion of the installed base, a situation that becomes structural within two or three quarters if left unaddressed.
Our Revenue Health Score diagnostics conducted with B2B scale-ups reveal four recurring clusters in the bottom quartile: (1) the broken acquisition engine (growth + pipeline coverage bottom), (2) the leaking base (NRR + GRR + CSM expansion bottom), (3) collapsed sales productivity (win rate + quota attainment + AE productivity bottom), (4) degraded financial efficiency (CAC + magic number + Rule of 40 bottom).
The Scorecard Template
The format used by mature funds is a table with 1 row per portfolio company, 15 metric columns, each cell coded T/UM/LM/B plus a quarterly trend arrow. The table fits on an A3 sheet, covers 10 to 15 portfolio companies, and summarizes the entire portfolio in a single image.
| Metric | Portfolio Company A | Portfolio Company B | Portfolio Company C | Portfolio Company D |
|---|---|---|---|---|
| ARR growth | T ↑ | UM = | LM ↓ | B ↓ |
| NRR | T = | UM ↑ | B ↓ | LM = |
| GRR | UM ↑ | T = | LM ↓ | B ↓ |
| CAC payback | UM = | T ↑ | B ↓ | LM = |
| Magic number | T = | UM = | B ↓ | B = |
| Rule of 40 | T ↑ | UM = | B ↓ | LM = |
| Win rate | UM = | T ↑ | LM ↓ | B ↓ |
| Forecast accuracy | T = | T = | B ↓ | LM ↓ |
This format lets the OP and CIO spot in seconds which portfolio companies are slipping, which are accelerating, and which metrics move in correlated ways across the portfolio.
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Faire le quiz gratuit →The Quarterly Portfolio Review Cadence
A benchmark that isn't reviewed quarterly in a disciplined format dies within two quarters. Cadence is what turns a spreadsheet into a living management tool.
The Recommended Format
The format that works at mature funds is a 2-hour quarterly portfolio review, held within 15 days of quarter close. The typical agenda runs in three blocks.
| Block | Duration | Content | Deliverable |
|---|---|---|---|
| Portfolio update | 60 min | 1 slide per portfolio company, 15-metric scorecard | Updated Q scorecard |
| Cross-portfolio patterns | 30 min | 3-5 patterns observed across the portfolio | Pattern library note |
| Alerts and IC decisions | 30 min | Portfolio companies on alert, proposed actions | Decisions recorded |
The Participants
The review brings together the OPs, the CIO, possibly the Managing Partner, and, depending on the fund, an analyst who maintains the scorecard. Do not include the portfolio companies' CEOs: this review is an internal fund exercise, and its value comes precisely from the candor allowed by their absence.
Preparation Discipline
Each OP prepares their block one week before the review. They update the scorecard, identify quadrant movements since the previous quarter, and write a 5-line note for each drifting portfolio company. This structured preparation is non-negotiable. An OP who shows up without prework turns the review into a descriptive roundtable that produces no decisions.
Traceability
Each review produces three artifacts archived in the fund's knowledge system: the quarter's scorecard, the cross-portfolio patterns note, and the record of IC decisions. The accumulation of these artifacts over 8 to 12 quarters progressively forms the backbone of the fund's pattern library.
The 4 Risks of a Poorly Designed Benchmark
The benchmark is not without risk. Poorly designed, it can destroy the CEO-OP relationship, demotivate sales teams, or push portfolio companies to dress up their reporting. Four risks are systematically observed.
False Equivalence
Comparing two portfolio companies that aren't in the same cohort produces false conclusions that discredit the OP from the very first session. This risk is prevented through normalization discipline (stage, segment, model) and by explicitly refusing any out-of-cohort comparison in readouts. An OP who tells a CEO "your magic number of 0.8 is weak" without specifying "for a sales-led Series B company like yours" loses all technical credibility in 30 seconds.
Management Demotivation
A management team that receives a quadrant verdict every quarter can become demotivated if the communication is clumsy. The rule is that the benchmark is never delivered as a judgment. It's delivered as a mirror to fuel the conversation, never as a grade. The standard phrasing is not "you're bottom quartile on CAC payback," it's "here are 12 comparable portfolio companies: 3 have a CAC payback below 15 months, 6 between 15 and 24 months, 3 above, you're at 26 months, what do you read into this gap?"
Metric Gaming
If CEOs know the benchmark feeds IC decisions, the temptation to dress up metrics is real. This risk is prevented through two measures: the OP recalculates metrics from raw data (not CEO reporting), and definitions are locked down by a single glossary shared with every portfolio company from day one. See CRM Data Quality: The Cost for the data discipline that underpins the benchmark's reliability.
Over-Granularity
A benchmark that's too detailed loses its value. Funds that track 40 metrics produce illegible scorecards and make worse decisions than those that discipline themselves to 15. The temptation toward granularity often comes from a junior OP who wants to "miss nothing." A senior OP knows that missing nothing usually means seeing nothing. See Revenue Reporting: Essential Metrics for the selection discipline.
Using the Benchmark in CEO Conversations
The benchmark only exists if it's shared back. And the readout is the most delicate exercise in the cycle: a well-done readout builds OP legitimacy for the next 12 months, a poorly-done one destroys it in a single session.
The Mirror Principle
The readout always takes the form of a mirror. The OP doesn't tell the CEO what to do. They show the CEO where they stand and ask an open question. "Here's where you stand on the 15 metrics, here's how 12 comparable portfolio companies rank, which 3 metrics do you see the most at stake on this year?" This posture lets the CEO arrive at the priorities themselves, and that's exactly what an OP is aiming for.
The Information Asymmetry
The OP has information the CEO doesn't: the behavior of the 9 to 14 other portfolio companies. This asymmetry is a double-edged sword. Used well, it feeds the CEO signal they won't find anywhere else. Used poorly, it makes the CEO feel watched. The discipline is to share aggregated patterns, never another portfolio company's named metrics. "Among comparable portfolio companies, we observe that those maintaining an NRR above 115% invest an average of 8 to 10% of their ARR in the CS function."
Readout Frequency
The CEO readout doesn't happen every quarter. It happens twice a year: once at the start of the annual cycle (January or February), to frame the year's priorities, and once mid-year (July) to adjust. In between, the OP can use the benchmark in bilateral conversation when a specific topic comes up, but never imposes an additional formal readout.
The Link to the Value Creation Plan
Every lever in the value creation plan must be traceable to a benchmarked metric. A pricing lever connects to ACV evolution and Rule of 40. A CSM expansion lever connects to NRR. A sales productivity lever connects to AE productivity and quota attainment. This traceability between levers and metrics is what lets the OP objectively measure whether the plan is working.
Top-Quartile vs Bottom-Quartile Patterns
The benchmarking exercise, repeated quarter after quarter, surfaces structural patterns that distinguish performing portfolio companies from those getting stuck. These patterns go beyond simple quantitative reading.
The Top-Quartile Cluster
Sustainably top-quartile portfolio companies share a combination of signals. NRR above 115% maintained over 6 consecutive quarters. Forecast accuracy variance below 10%. A win rate that's stable or improving, quarter after quarter. AE productivity consistent with the cohort or above it. A magic number above 1 even during sector slowdowns. This cluster is almost never explained by a single factor: it reflects end-to-end execution discipline, backed by reliable data governance and an established revenue culture.
The Bottom-Quartile Cluster
Sustainably bottom-quartile portfolio companies also share cross-cutting signals. Silent NRR erosion quarter after quarter, often invisible in aggregated reporting. A CAC payback that keeps stretching out due to lack of marketing discipline. Forecast accuracy that deteriorates because the pipeline is no longer kept hygienic. Dependence on one or two top performers capturing 30 to 50% of revenue, masked by team averages. See Top Performer Dependence: The Risk for the specific assessment grid.
Evolution Patterns
The benchmark over 8 to 12 quarters also surfaces evolution patterns. A portfolio company can move from bottom to upper mid in 2 quarters if a structural lever is activated with discipline. Conversely, a top company can slide to lower mid in 3 quarters if a poorly prepared CRO transition breaks the sales cadence. These dynamics are themselves a valuable signal: they measure how fast a portfolio company can recover or collapse, and feed OP time-allocation decisions.
Leading Indicator Metrics
Some metrics are leading indicators. BDR productivity typically moves 2 quarters before pipeline coverage. Forecast accuracy typically deteriorates 1 quarter before quota attainment. NRR by signature cohort deteriorates 2 to 3 quarters before aggregated NRR. An OP who monitors these leading indicators can act 6 to 9 months ahead of the OP who only looks at aggregated metrics, see Silent NRR Erosion: The Risk.
Template: Ready-to-Use Portfolio Benchmark Grid
This roadmap summarizes the method in a format ready to use for your next portfolio review. It serves both a fund starting its benchmark and a fund looking to discipline an existing exercise.
14-Week Implementation Roadmap
| Week | Action | Expected Deliverable |
|---|---|---|
| W1 | Define the 15 metrics and the single glossary | Glossary v1 shared with IC |
| W2 | Classify portfolio companies on the 3 cohort axes | Validated cohort table |
| W3 | Raw collection of Q-1 portfolio company data | Consolidated raw dataset |
| W4 | Recalculate metrics with a single methodology | Normalized Q-1 metrics |
| W5 | Build the 15-column scorecard | Scorecard v1 ready |
| W6 | Define quadrants by cohort | Validated quadrant thresholds |
| W7 | Position each portfolio company within the quadrants | Complete scorecard |
| W8 | Identify 3-5 cross-portfolio patterns | Pattern library note v1 |
| W9 | Pre-review scorecard with CIO and Managing Partner | Final Q-1 scorecard |
| W10 | Quarterly portfolio review (2h, disciplined format) | Decisions recorded, IC alerts |
| W11 | CEO readout for the 2-3 priority portfolio companies | Aligned action plan |
| W12 | Update the fund's knowledge system | Artifacts archived |
| W13 | Prepare data collection for the current quarter | Validated collection calendar |
| W14 | Move to a recurring quarterly cadence | Cadence active |
The 6 Quality Control Gates
At each quarterly cycle, the OP checks the following 6 gates before publishing the scorecard. A single missed gate invalidates the scorecard and delays the review.
| Gate | Check | Validation Criterion |
|---|---|---|
| 1. Definitions | The 15 metrics are calculated identically everywhere | Glossary signed off by each portfolio company's CFO |
| 2. Sources | Metrics come from raw data, not CEO reporting | OP access to direct data extracts |
| 3. Cohorts | Each portfolio company is correctly placed on the 3 axes | Cohort review by CIO |
| 4. Normalization | Quadrant thresholds account for stage and segment | Threshold documentation by cohort |
| 5. Trends | Trend arrows compare to Q-1 at constant scope | Cross-check against Q-1 |
| 6. Readout | The CEO message takes the mirror form, not judgment | Readout scripts prepared |
The 5 Fatal Mistakes to Avoid
Five mistakes come up systematically at funds that attempt a benchmark without methodological discipline. Anticipating them is the best prevention.
| Mistake | Manifestation | Consequence |
|---|---|---|
| Too many metrics | 30 to 50 KPIs tracked | Illegible scorecard, diluted decisions |
| No normalization | Raw cross-stage comparison | OP discredited, CEOs shut down |
| Readout as judgment | "You're bottom quartile" | CEO relationship broken |
| No cadence | Annual or ad-hoc benchmark | The tool dies within 2 quarters |
| CEO data, not raw | Metrics sourced from reporting | Systematic metric gaming |
Further Reading
To go deeper on the structuring elements covered in this article, we recommend the following reads from our knowledge hub:
- 100-Day Portfolio Plan: OP Method: the 100-day sequence in which the first post-closing benchmark takes root
- Revenue Due Diligence: OP Method: the primary source of metrics before entering the portfolio
- Revenue Red Flags: OP Detection: the alerts generated by the scorecard
- NRR: Net Revenue Retention: the central metric to normalize in the benchmark
- B2B CAC: Customer Acquisition Cost: the single CAC methodology to enforce across the portfolio
- Revenue Financial Control: Unit Economics: the unit economics framework that complements the benchmark
- Sales Forecast: Accuracy: the most revealing execution metric
- Pipeline Management: Hygiene and Forecast: the discipline that determines data reliability
- B2B Revenue KPIs: CEO Indicators: the common vocabulary to establish
- BDR Performance: KPIs: the leading indicators on the top of the funnel
- Revenue Expansion: CSM and Upsell: the NRR lever in a value creation plan
- Silent NRR Erosion: The Risk: the weak signal to monitor quarterly
- Revenue Reporting: Essential Metrics: the discipline for selecting the 15 metrics
- 20 B2B Revenue Standards: the sector reference framework
- Our Revenue Diagnostic Methodology: the ACROSS method applied to PE and VC portfolios
Sources Cited
- McKinsey & Company, Private Equity Operating Partner Report (2024 edition)
- OpenView Partners, SaaS Benchmarks Report (annual edition)
- Scale Venture Partners, Scaling Enterprise SaaS (publication series)
- KeyBanc Capital Markets, SaaS Survey (annual edition)
- Proprietary ACROSS INSIGHT data from our Revenue Health Score diagnostics conducted with B2B scale-ups between €5M and €150M ARR, including portfolio companies supported by PE and VC funds
Article written by Charles-Alexandre Peretz, co-founder of ACROSS INSIGHT, based on the analysis of our Revenue Health Score diagnostics conducted with B2B companies in hypergrowth, including PE and VC portfolio companies supported by Operating Partners. Last updated: August 30, 2026.