The B2B SaaS Benchmark Corpus

A B2B SaaS benchmark is only comparable when the denominator, the panel, the statistic and the

time basis all match. Run these five checks in order — if a comparison fails any one of them, the

gap you are looking at is measurement, not performance. Most do fail, usually on the first or the third.

The same metric name covers genuinely different formulas. Win rate, NRR, CAC payback and

conversion rate each have three or more live conventions. Settle the formula before the number.

ARR band, ACV band, funding type, GTM motion, geography. A $60K-ACV enterprise seller and a

$600-ACV self-serve product share almost no structural DNA. ACV is the strongest single cut.

Median, mean, upper quartile. The single most common benchmarking error in the wild is comparing

your median against somebody's published top quartile and concluding you're broken.

Sample size collapses when a survey cuts by ACV. A report with n=150 can have n=9 in the band

you care about. Read the per-chart n before you quote the per-report n.

• So what
• Benchmarks answer "are we structurally normal?" They do not answer
• "what should we fix?" For the second question, the only useful comparison is a
• company against its own trailing cohorts — which is also the only comparison where the

definition is guaranteed to be constant.

The definition layer 16 metrics, each with its canonical formula, the variants in the wild, and what each variant does to the number.

Funnel benchmarks Stage conversion, sales cycle by ACV, win rate, pipeline coverage, quota attainment, rep-level metrics.

Retention benchmarks NRR and GRR by ACV and by ARR, quartiles, contract length, and the growth correlation.

Efficiency benchmarks CAC payback, CAC ratio, S&M spend, Rule of 40, ARR per employee, gross margin.

Where sources disagree Five real conflicts between credible panels, and the measurement reason behind each.

Source directory Seven publishers graded on panel, sample, cadence, bias and what each one is actually best for.

The definition layer

This is the part of the corpus that does the work. For each metric: the canonical formula, the

variants that circulate, what each variant does to the resulting number, and which published source

uses which convention. Risk pills flag how often the metric is the actual cause of a mismatch.

• Highest mismatch risk
• a.k.a. close rate, opportunity win rate
• Most common published formula
• closed-won ÷ (closed-won + closed-lost)

— measured on opportunities that reached a terminal outcome in the period.

Decision-only denominator. Only won + lost. Every stalled, no-decision and

indefinitely-slipped deal is excluded.

Created-cohort denominator. All opportunities created in a period, tracked to outcome.

No-decision counts as a loss.

Qualified-only denominator. Starts at SQL or stage 2+, discarding early-stage

disqualification.

Dollar-weighted vs logo-weighted. Weighted by ACV rather than deal count; diverges

sharply when big deals lose more often.

Snapshot vs cohort. Deals closed in the period vs deals created in the period.

The decision-only denominator is the single largest inflator in B2B SaaS benchmarking.

In enterprise, no-decision is frequently the largest loss category — excluding it can

roughly double the reported rate. This is most of the distance between the 43% and the 19% in

the banner above.

• Source conventions — ICONIQ states it explicitly in a footnote:
• (# closed-won ÷ (# closed-won + lost)) × 100 , and reports 43%
• average for sales-sourced opportunities (2026). The Bridge Group reports a 19% median win

rate (2024) on a broader denominator. Neither is wrong; they are not comparable.

"Does your win rate denominator include deals that went nowhere?"

• Highest mismatch risk
• Canonical (cohort basis)
• records that advanced past stage N ÷ records that ENTERED stage N in the period

— tracked forward to outcome, not counted where they sit today.

Snapshot basis. Denominator is records in the stage during the period, including

ones that entered long ago. This is the CRM default and it is wrong.

Skipped stages. Most CRMs let a deal jump stages. A skipped stage silently records

zero entries and inflates that stage's conversion toward 100%.

Open-deal treatment. Are still-open records excluded, counted as failures, or left

in the denominator? Excluding them inflates; counting them as failures deflates.

Stage-to-stage vs stage-to-close. "SQL conversion" may mean SQL→next stage or

SQL→closed-won.

Immature cohorts. A cohort younger than one sales cycle has not had time to convert.

Snapshot conversion is biased optimistic , because the deals that never advance

accumulate in the stage and are counted as denominator only once while winners recycle through.

Immature cohorts bias pessimistic . Together they make period-over-period comparison on

an unstated basis close to meaningless.

Source conventions — Survey-based sources (ICONIQ, Benchmarkit) ask

respondents for a rate and do not enforce a basis, so the published averages blend both conventions.

This is a structural limitation of every funnel benchmark in this corpus and the reason the funnel

section carries wider error bars than the retention section.

"Is that cohort-based or a snapshot? And what happens to open deals?"

• Highest mismatch risk
• marketing / sales-accepted / sales-qualified lead
• There is no industry definition
• These are locally defined thresholds , not standard objects. An MQL is whatever score or

action a given company decided counts.

MQL threshold. A score cutoff set internally. Lowering it raises MQL volume and

lowers MQL→SQL conversion, with zero change in the business.

• SAL vs SQL. SAL = sales accepted (a routing acknowledgement). SQL = sales
• qualified (a judgement after contact). Many companies run only one of the two, so

"MQL→SQL" in one dataset is "MQL→SAL" in another.

Person vs account. Lead-level counts inflate relative to account-level counts wherever

buying committees are large.

Recycling. Does a lead that returns count as a new MQL?

The MQL→SQL rate is primarily a measure of how loose your MQL threshold is , and only

secondarily a measure of lead quality. It is the least portable metric in this corpus.

Benchmark it against your own history, not against anyone else's panel.

Source conventions — Benchmarkit publishes MQL→SAL at a 20% median.

ICONIQ publishes New Lead→MQL at 28% and MQL→SQL at 30% (2026). The stage names do not

refer to the same objects across the two panels.

"What has to be true for a record to become an MQL here?"

• Medium mismatch risk
• Canonical

close date − opportunity created date , median, measured on won deals only.

Start point. First touch, MQL, opportunity creation, first meeting, or qualification.

First-touch-to-close can be 2–3× opportunity-to-close.

End point. Verbal, signature, countersignature, or first payment.

Won-only vs won+lost. Including losses usually shortens the number, since

losses die early — but including no-decisions lengthens it dramatically.

Mean vs median. Cycle-time distributions have a long right tail, so the mean runs

meaningfully above the median.

Business vs calendar days.

Start-point choice is the dominant term. Two companies with identical processes can publish

cycle lengths a factor of two apart purely on where they start the clock. Always convert to

opportunity-created → closed-won, median before comparing.

Source conventions — ICONIQ reports average weeks and does

not publish a start-point definition, so its by-ACV curve should be read as a shape rather than as

absolute values. The Bridge Group reports medians on AE-owned opportunities.

"Does the clock start at opportunity creation or at first touch?"

• Medium mismatch risk
• Canonical

open pipeline for the period ÷ quota (or target) for the period , measured at period start.

Stage inclusion. All open pipeline vs qualified-and-later only. This single choice

routinely moves coverage by 1.5–2×.

Measurement moment. Snapshot at period start vs rolling average through the period.

Raw vs weighted. Probability-weighted pipeline against an unweighted target is a

category error, but common.

Close date in-period only vs all open pipeline regardless of expected close.

Whose quota. New-logo quota, total quota including renewals, or company target.

• The classic "3× coverage" rule is only meaningful with the stage set attached. The right
• coverage number is simply 1 ÷ your own stage-to-close conversion rate , which means a

company with a genuine 25% conversion needs 4×, and one at 33% needs 3×. Borrowing the rule

without the conversion rate behind it is guesswork.

Source conventions — Benchmarkit currently recommends 4:1

against a historical 3:1, and notes coverage requirements correlate strongly with ACV.

"Which stages count as pipeline in that ratio?"

• Medium mismatch risk
• Canonical

reps at or above 100% of quota ÷ total reps , over a full fiscal year.

Ramped-only vs all reps. Excluding ramping reps raises the figure substantially at

any company that is hiring.

Annual vs quarterly. Quarterly attainment is lower and noisier.

Point-in-time roster vs everyone who held the seat. Counting only reps still employed

at year end removes the ones who missed and left.

Attainment of quota vs attainment of a prorated quota.

Ramped-only plus survivor-only can add 10–15 points against an all-reps, all-holders

basis. This explains most of the gap between the two figures cited opposite.

Source conventions — ICONIQ reports the share of ramped AEs

achieving quota: 62% for 2025. The Bridge Group reports 48% for 2026 on a broader rep base.

Both are credible; the ICONIQ figure is the more flattering basis.

"Ramped reps only, or everyone who carried a number?"

• Highest mismatch risk
• Three different metrics, routinely used interchangeably
• ACV = total contract value ÷ contract years ·
• ASP = average value of a closed deal ·
• ARR/customer = total ARR ÷ customer count

Multi-year contracts. A three-year $300K TCV deal is $100K ACV — but it may bill

$150K in year one. ACV, TCV and billings all differ.

New vs installed base. ASP describes new deals; ARR/customer includes years of

accumulated expansion and is therefore always higher in a healthy business.

Ramped deals. Contracts that step up over the term have no single ACV.

Consumption pricing. Committed vs actual consumption produces two defensible ACVs

for the same contract.

• This matters more than it looks, because ACV is the primary segmentation axis in this
• entire corpus . Choosing ARR/customer instead of new-deal ACV can move you a full band

up the table and hand you the wrong benchmark for everything else.

Source conventions — KeyBanc reported a $62K median ACV (2024 survey).

The Bridge Group reported a $47K median ASP (2024) and a $50K median ASP in its 2025 SDR panel.

SaaS Capital and High Alpha both band by ACV as respondents self-report it.

"Is that new-deal ACV, or ARR divided by customers?"

• Highest mismatch risk
• NRR · NDR · net dollar retention · net expansion rate
• Canonical — SaaS Capital's published formula, the clearest in circulation
• MRR in Dec Y2 from customers who were customers in Dec Y1 ÷ total MRR in Dec Y1

Includes upsell, cross-sell, price increases, downgrades and churn. Can exceed 100%.

New customers in the denominator. They must be excluded. Including customers acquired

during the period is the most common outright error and inflates the result.

Churned logos dropped. Churned customers must stay in at $0. Dropping them turns NRR

into an expansion rate and can add 10+ points.

Annual cohort vs monthly annualised. Compounding a monthly rate produces a different

number than an annual point-to-point cohort on identical data.

ARR vs MRR vs recognised revenue basis.

Trailing-twelve-month vs point-in-time snapshot.

Public-company convention. "Dollar-based net expansion rate" in 10-Ks often uses a

trailing-12-month cohort and is not directly comparable to private survey NRR.

The two failure modes both push the same way: up . A company reporting 115% NRR with

new customers in the denominator and churned logos dropped may be running 95% on the canonical

formula. When an NRR figure looks anomalously strong for its ACV band, check these two things

first.

Source conventions — SaaS Capital publishes the formula above

explicitly. High Alpha defines NRR as "annual net revenue retention (after churn, inclusive

of upsells and expansion) seen in cohorts". ICONIQ reports NDR from portfolio operating data

rather than survey self-report, which is why its figures run higher and are published as quartiles.

"Are churned customers still in the numerator at zero, and are new customers out of the denominator?"

• Low mismatch risk
• GRR · gross dollar retention
• Canonical

Same cohort formula as NRR, with each customer's ending value capped at its starting value .

Captures churn and downgrade only. Cannot exceed 100%.

Capping per customer vs in aggregate. Capping only the total lets one customer's

expansion mask another's downgrade — this is the error that produces a "GRR" above 100%.

Downgrades excluded. Some companies count only full churn, which makes GRR a logo

metric wearing a revenue metric's name.

Renewal-base GRR. Measured only against contracts that actually came up for renewal

in the period, rather than the whole book. Materially higher for multi-year books.

Renewal-base GRR is the flattering variant and is common in board decks at companies with

multi-year contracts, because contracts that never came up for renewal cannot churn.

A GRR above 100% is definitionally impossible — if you see one, the cap is being

applied in aggregate.

Source conventions — SaaS Capital and High Alpha both use

the whole-book cohort convention. Both land on ~90–92% as the all-company median, which is the

strongest agreement between any two panels in this corpus.

"Is that against the whole book, or only against what came up for renewal?"

• Highest mismatch risk
• Two different metrics with one name
• Logo churn = customers lost ÷ customers at period start ·
• Revenue churn = revenue lost ÷ revenue at period start

Logo vs revenue. In an SMB-weighted book, logo churn can be double revenue churn,

because the customers who leave are the small ones.

Monthly vs annual, converted wrong. 2% monthly churn is not 24% annually.

It is 1 − 0.98 12 = 21.5% . Linear annualisation overstates.

Denominator timing. Start-of-period, average, or end-of-period base.

Is churn the complement of GRR? Only if downgrades are treated identically in both.

The monthly-to-annual conversion error is small at low churn and large at high churn:

at 5% monthly, linear gives 60% and the correct compounding answer is 46%. Any SMB benchmark

quoted as an annual figure should be checked for which way it was derived.

Source conventions — the sources in this corpus report revenue

retention rather than churn, and on an annual cohort basis. SaaS Capital states plainly that it

considers dollar-based retention the more important metric and surveys on that basis.

"Logos or dollars? And was the annual number compounded or multiplied?"

• Highest mismatch risk
• Canonical — gross-margin-adjusted
• fully-loaded S&M cost to acquire a customer ÷ (new MRR × subscription gross margin)

— expressed in months.

Gross margin omitted. Dividing by raw revenue rather than gross profit understates

payback by roughly the gross-margin haircut — about 20–25% at typical SaaS margins.

New-only vs blended. Including expansion ARR in the denominator shortens payback

substantially and measures a different thing.

Cost scope. Sales only, S&M, or S&M plus onboarding and customer success.

Unallocated founder and support cost. High Alpha flags this explicitly as an

early-stage distortion.

Period lag. Prior-period spend against current-period ARR vs same-period both.

Every common variant pushes payback down . The sub-$1M ARR median of 5 months in the

High Alpha data is not a real 5 months — the publisher itself warns that early-stage companies

under-allocate founder salaries, support costs and onboarding into CAC.

Source conventions — High Alpha defines it as "months of subscription

gross margin to recover the fully-loaded cost of acquiring a customer" — the strict version — and

publishes quartiles by ARR band.

"Is that gross-margin-adjusted, and does the denominator include expansion?"

• Medium mismatch risk
• Three ratios, and they are not interchangeable
• New CAC ratio = total S&M ÷ new customer ARR
• Blended CAC ratio = total S&M ÷ (new customer ARR + expansion ARR)
• Expansion CAC ratio = expansion-attributed S&M ÷ expansion ARR

It converts directly into a budget: $25M of new ARR at a 1.5 New CAC ratio requires a

$37.5M go-to-market budget. Payback period does not do this.

It is denominated in dollars of ARR, not logos, so it is stable across mixed deal sizes.

Blended will always look better than New. A company quoting an unqualified "CAC ratio" is

usually quoting Blended.

• Benchmarkit put the median New CAC ratio at $2.00 — two dollars of sales and marketing
• per dollar of new customer ARR — up 14% year over year, with the fourth quartile at

$2.82 .

Source conventions — Benchmarkit is the source that maintains this

family of definitions most rigorously and segments them by ARR, ACV, GTM motion and VC- vs PE-backed.

"New or blended?"

• Medium mismatch risk
• Canonical
• YoY growth rate (%) + profitability margin (%) ≥ 40

• Which margin. Free cash flow margin, EBITDA margin, or operating margin. FCF and
• EBITDA can differ by many points at companies with heavy deferred revenue or capitalised

development.

ARR growth vs recognised revenue growth. ARR growth leads revenue growth, so the

ARR version reads higher during acceleration and lower during deceleration.

Trailing twelve months vs annualised current quarter.

Companies choose the flattering combination, and it is rarely disclosed. Treat any

single-company Rule of 40 claim as unverifiable unless both terms are stated.

Source conventions — High Alpha defines it as "year-over-year ARR

growth percentage plus last twelve months free cash flow margin or EBITDA margin", explicitly

permitting either margin.

"Growth of what, plus which margin?"

• Medium mismatch risk
• Canonical

function spend including headcount ÷ ending ARR for the period.

Denominator: ending ARR vs recognised revenue vs average ARR. At 30% growth,

ending-ARR and average-ARR denominators differ by roughly 13%.

Is customer success inside S&M? Placement varies and moves several points.

Is RevOps inside S&M, G&A, or split?

Fully-loaded vs cash comp only.

Function-boundary choices dominate. Before comparing an S&M ratio, confirm whether CS

and RevOps sit inside it — that alone can account for the entire apparent gap.

• Source conventions — High Alpha uses spend including headcount as a
• percentage of ending ARR . LeanScale's own
• RevOps investment study works through

the same denominator problem for RevOps specifically and reaches the same conclusion: pick the

denominator before the number.

"Percent of ending ARR or of revenue, and is CS inside the numerator?"

• Medium mismatch risk
• Canonical (quarterly)
• (current-quarter ARR − prior-quarter ARR) × 4 ÷ prior-quarter S&M spend

Net new ARR vs new-customer ARR only. The net version includes expansion and churn

and is the standard.

Same-quarter vs prior-quarter S&M. Prior-quarter is correct — spend leads revenue —

but same-quarter is common.

Gross-margin adjusted or not.

• Magic number and CAC ratio are reciprocals of each other under matching conventions —
• a New CAC ratio of $2.00 is a magic number of 0.5. If a company's two figures do not

reconcile, the conventions differ somewhere.

"Prior-quarter spend, and net new or new-customer ARR?"

• Low mismatch risk
• Canonical
• ending ARR ÷ full-time employees at period end

Contractors and offshore teams. Excluding them is the standard distortion, and it is

growing as offshore delivery scales.

FTE headcount vs FTE-equivalent.

Period-end vs average headcount during a hiring year.

Cleanest metric in the corpus definitionally, and increasingly the one people most want,

because it is the crispest read on whether AI leverage is real.

Source conventions — High Alpha counts full-time employees at

quarter end and publishes medians and upper quartiles by ARR band.

"Are contractors and offshore staff in that headcount?"

• Low mismatch risk
• Canonical
• (subscription revenue − subscription COGS) ÷ subscription revenue

Subscription-only vs total (blended with services). Services drag blended margin

down sharply; the subscription-only figure is the benchmark standard.

What sits in COGS. Hosting, support, customer success, professional services and —

newly material — AI inference cost .

Inference cost is the live issue. High Alpha's 2025 data shows early-stage gross margins

declining year over year while mature-company margins held, consistent with AI-native products

carrying real variable cost of goods.

• "Subscription-only or blended with services, and is inference in COGS?"
• Funnel benchmarks

The strongest by-ACV funnel data available comes from ICONIQ's annual GTM survey. Read every figure

here against the definition cards above — particularly win rate and stage conversion, where the

published averages blend measurement conventions.

Average weeks · ICONIQ Growth , State of Go-to-Market 2026 (Jan 2026 survey, 157 respondents on this chart)

• < $10K
• 6 wks
• $10K–$50K
• 12 wks
• $50K–$100K
• 17 wks
• $100K+
• 24 wks
• Per-band n: 9 · 30 · 35 · 83. The <$10K cell is thin and should be read as

directional only. Shape: the cycle roughly doubles for each ~5× step in ACV.

Overall average cycle fell from 25 weeks (H1 2025) to 19 weeks (H2 2025), against 23 weeks in 2024 —

but over the same window the share of new-logo contracts under one year rose from 2% to 13%.

Customers are signing faster for shorter terms.

• Average · ICONIQ Growth , State of Go-to-Market 2026 · n=147 (2026), n=167 (2025)
• Stage transition 2026 2025 Change
• New lead → MQL 28% 25% +3
• MQL → SQL 30% 27% +3
• SQL → closed-won 28% 25% +3
• Demo → closed-won 38% 36% +2
• Free trial / POC → paid 50% 36% +14
• The POC jump is the largest single-year move in the dataset. ICONIQ

attributes it to POCs being run as a disciplined motion rather than an open trial — support

level scales with ACV, with a dedicated solutions architect on 49% of POCs above $100K ACV

versus 25% below $50K.

Average · closed-won ÷ (closed-won + closed-lost) · ICONIQ Growth · n=145 (2026), n=165 (2025)

• Opportunity source 2026 2025
• Customer success 52% —
• Sales 43% 38%
• Channel / partner 39% 35%
• Marketing 27% 23%
• This denominator excludes no-decision outcomes entirely — see the
• win-rate definition card. Use these figures for the relative ranking by source , which is

robust, rather than as an absolute target.

• Pipeline sourcing
• High-growth companies in the ICONIQ panel derive 60–80% of pipeline from sales and channel

motions against 15–20% from marketing — a materially more seller-led mix than their non-high-growth

peers. "High growth" is defined by ICONIQ as 200%+ YoY at $10–25M revenue, 100%+ at $25–100M,

50%+ at $100–250M, and 30%+ at $250M+.

• Share of reps achieving quota · two sources, two bases
• Basis Figure Source Note
• Ramped AEs, 2025 62% ICONIQ Up from 58% (2024) and 59% (2023)
• SMB AEs 68% ICONIQ n=71
• Mid-market AEs 59% ICONIQ n=113
• Enterprise AEs 64% ICONIQ n=125
• Strategic AEs 61% ICONIQ n=106
• All AEs, 2026 48% Bridge Group Down from 51% (2024), 66% (2022)
• All AEs, high AI engagement 57% Bridge Group vs 39% in the lowest tercile

The Bridge Group — 2026 AE Research (n=158) and 2025 SDR Research (n=351; 83% B2B SaaS, $47M median revenue, $50K median ASP)

• Metric Current Prior Direction
• AE median quota $960K $800K (2024) Quota CAGR ~2.4%
• AE median OTE $200K $190K (2024) · $167K (2022) OTE CAGR ~4.9%
• Quota-to-OTE ratio 4.6× 4.2× (2024) Rising
• AE ramp time 6.2 mo 5.7 mo (2024) Highest in study history
• Experience required at hire 3.7 yrs 2.7 yrs (2022) Rising sharply
• AE win rate 19% 23% (2022) 2024 figure; broader denominator
• SDR : AE ratio 1 : 2.4 1 : 2.4 Flat since 2018
• SDR ramp 3.0 mo — Lowest since 2010
• SDR tenure 1.9 yrs — Highest since early 2010s
• SDR monthly quota (meetings held) 10 — Down ~40% since 2018
• SDR daily activities 112 — 44 phone · 41 email · 19 LinkedIn · 8 other
• SDR quality conversations / day 4.1 — First rebound in study history
• Pipeline generated per SDR $3.78M $2.83M (2022) Rising
• SDR median OTE $80K $80K (2022) 68:32 base:variable
• SDR annual attrition 40% — 13% involuntary · 11% voluntary · 16% promotion
• ACV is the largest single determinant of AE quota in the Bridge Group

data: the gap between a sub-$25K-ACV seller and a $250K+ seller is roughly 2.5× .

Retention benchmarks

Retention is the best-instrumented area in this corpus: two independent panels of 800–1,500

companies, both publishing by ACV, both stating their formulas. Where they agree, confidence is high.

Where they disagree — the top of the ACV range — the disagreement is itself informative.

Median · SaaS Capital , 2023 B2B SaaS Retention Benchmarks (12th annual survey, 1,500+ private B2B SaaS companies, excludes <$1M ARR)

• ACV band NRR — 25th NRR — median NRR — 75th GRR — median
• Less than $12K 93% 100% 105% 90%
• $12K – $25K 96% 102% 108% 90%
• $25K – $50K 97% 103% 111% 92%
• $50K – $100K 98% 105% 113% 93%
• $100K – $250K 101% 107% 118% 93%
• More than $250K 103% 110% 120% 93%
• All-company medians: NRR 102%, GRR 91%. SaaS Capital's own guidance:

below $25K ACV, 90% GRR is the norm; above it, benchmark to 93%. GRR is treated as table stakes —

below 90% and growth falls under the population median.

Why ACV is the right cut. In SaaS Capital's words, companies that share

a similar selling price have the most in common — more than company age, revenue level or industry.

They organise similarly, go to market similarly, and support customers similarly.

• Median · High Alpha , 2025 SaaS Benchmarks Report (9th annual, 800+ respondents)
• ACV band % of panel YoY growth GRR NRR
• Less than $1K 4% 30% 83% 98%
• $1K – $5K 11% 25% 88% 97%
• $5K – $10K 8% 25% 85% 94%
• $10K – $15K 10% 40% 88% 107%
• $15K – $25K 11% 38% 88% 104%
• $25K – $50K 16% 30% 92% 105%
• $50K – $100K 18% 44% 94% 104%
• $100K – $250K 12% 30% 91% 102%
• More than $250K 9% 32% 92% 105%
• High Alpha's reading: performance converges in the mid-market. Companies

between $10K and $100K ACV show the strongest blend — growth above 30%, GRR near or above 90%,

NRR above 104%. Sub-$10K contracts churn and cannot expand; at the top end growth slows as

cycles lengthen and concentration rises.

• Cross-check
• The two panels agree closely on GRR — roughly 90% below $25K ACV rising to 92–94%
• above it — which is the strongest corroboration in this corpus. They
• disagree on the shape of NRR at the top end : SaaS Capital finds NRR rising

monotonically to 110% above $250K, while High Alpha finds it peaking in the $10K–$100K range and

flattening above. Treat the direction (higher ACV, higher retention) as well-established and the

exact top-end value as unsettled.

• Median and quartiles · High Alpha 2025 (n=800+)
• ARR band NRR — lower NRR — median NRR — upper GRR — median
• Less than $1M 78% 100% 116% 92%
• $1M – $5M 91% 104% 110% 92%
• $5M – $20M 95% 103% 115% 88%
• $20M – $50M 98% 103% 110% 90%
• Greater than $50M 101% 101% 108% 88%
• Note the spread, not just the median: sub-$1M companies range from 78%

to 116%, and the range tightens steadily with scale. Early-stage NRR is a weak signal.

• Median · SaaS Capital (n=1,500+)
• Cut Group NRR GRR / other
• Growth rate by NRR NRR below 90% — 20% median growth
• NRR 90–100% — 26%
• NRR 100–110% — 35%
• NRR 110–120% — 40%
• NRR 120–130% — 49%
• NRR above 130% — 70%
• Contract length Month-to-month 100.0% 89.5%
• Annual 101.0% 90.0%
• Multi-year 105.5% 95.0%
• Funding Bootstrapped 100% 91%
• Equity-backed 103% 91%
• Product shape Horizontal 102% 90%
• Vertical 101% 92%
• Company age Under 3 years 102% 92%
• 3–5 years 103% 94%
• 6–14 years 101–102% 90%
• Population median growth in that survey was 34%. Two cautions:
• young-company GRR is artificially elevated because customers have not yet had a chance to

churn — the decline from 94% to 90% between years 3–5 and 6+ is a measurement artefact maturing,

not performance decaying. And the multi-year retention premium may carry the same artefact:

contracts that have not come up for renewal cannot churn.

Most recent readings

SaaS Capital 2026 (bootstrapped, $3–20M ARR, 1,000+ companies): median growth 15% — down from

20% — with 42.3% at the 90th percentile; NRR 103% median, 117.9% at p90; GRR 91% median, 100% at p90.

KeyBanc / Sapphire, 16th annual (Nov 2025): ARR growth expected to accelerate from 15% in 2024 to

20% in 2025; gross retention recovering toward 90% from 86% in 2023; net retention above 100%.

ICONIQ : top-quartile net dollar retention in the ~110–120% range across revenue bands, from

portfolio operating data rather than survey self-report.

Efficiency benchmarks

Median [lower quartile – upper quartile] · High Alpha , 2025 SaaS Benchmarks Report (n=800+)

• Metric <$1M ARR $1–5M $5–20M $20–50M >$50M
• YoY growth rate 100% [29–300] 50% [24–100] 31% [15–72] 30% [16–41] 16% [10–29]
• CAC payback (months) 5 [2–8] 8 [5–14] 14 [8–22] 20 [11–27] 17 [13–22]
• Gross revenue retention 92% [80–100] 92% [83–95] 88% [82–95] 90% [85–95] 88% [84–90]

Net revenue retention 100% [78–116] 104% [91–110] 103% [95–115] 103% [98–110] 101% [97–108]

• S&M spend (% of ARR) 28% [20–50] 30% [20–50] 30% [22–53] 29% [24–34] 25% [20–40]
• R&D spend (% of ARR) 43% [23–76] 38% [24–50] 31% [20–54] 32% [23–40] 30% [25–40]
• Software gross margin 74% [60–80] 77% [60–85] 80% [70–86] 78% [71–84] 79% [70–83]
• Rule of 40 46% [25–98] 33% [10–80] 20% [−3–35] 24% [11–41] 30% [15–38]
• Employees (median) 9 [5–12] 22 [15–35] 66 [48–92] 131 [100–223] 361 [263–729]
• ARR per employee — median $55,556 $136,364 $166,667 $268,235 $277,778
• ARR per employee — upper quartile $100,000 $200,000 $220,588 $350,000 $396,635

Panel: ARR <$1M 23%, $1–5M 27%, $5–20M 31%, $20–50M 10%, >$50M 9%.

69% US. ICP: enterprise 37%, mid-market 35%, SMB 19%. 50% of respondents were CEO or founder.

CAC payback caution from the publisher itself: early-stage companies frequently fail to

allocate founder salaries, support costs and onboarding into CAC, artificially lowering the

reported payback period.

• CAC ratio
• Benchmarkit's median New CAC ratio is $2.00 — two dollars of sales and marketing spend per

dollar of new-customer ARR — up 14% year over year, with the fourth quartile at $2.82 .

This is the most directly plannable efficiency metric in the corpus: it converts straight into a

budget. $25M of new ARR at a 1.5 ratio requires a $37.5M go-to-market budget.

RevOps investment

LeanScale's own reconciliation of eleven published sources puts RevOps at 5–10% of go-to-market

headcount (median 7%), or roughly one RevOps head per $21M of ARR — and about 0.9% of

revenue, not the 5–10% of revenue the rule of thumb is usually misquoted as. Full working at

leanscale-revops-investment.netlify.app .

Reconciliation

Each of these is a real conflict between reputable panels. In every case the disagreement resolves

to measurement rather than to one source being wrong — which is exactly why the definition layer

exists.

• 43% ICONIQ · sales-sourced · 2026
• 19% Bridge Group · median · 2024

ICONIQ's published formula excludes every deal that did not reach a won/lost decision. In enterprise

sales, no-decision is routinely the largest single loss category, so removing it lifts the rate

substantially. The Bridge Group measures on a broader opportunity base closer to what a CRO

experiences on a forecast call.

Panel composition compounds it: ICONIQ's respondents skew to $100K+ ACV growth-stage companies

with mature qualification, and 42% of the panel sits in the $100K–$500K ACV band.

Use: ICONIQ for relative comparisons between opportunity sources.

Bridge Group for an absolute expectation of what a rep converts. Never compare your own number to

either without first establishing which denominator you compute on.

• 62% ICONIQ · ramped AEs · 2025
• 48% Bridge Group · all AEs · 2026

ICONIQ measures ramped AEs only. At a company hiring into growth, a meaningful share of the rep

base is ramping at any moment and structurally cannot attain — excluding them raises the figure.

The two also cover different years, and the trend is downward.

Use: the ramped-only figure when assessing whether your tenured

reps are performing; the all-rep figure when modelling capacity and forecast coverage.

• 102% SaaS Capital · median · all
• 103% High Alpha · median · $5–20M
• 110–120% ICONIQ · top quartile

This is not a disagreement at all — it is the most common benchmarking error in circulation.

• SaaS Capital and High Alpha publish medians across their whole panel . ICONIQ publishes
• top-quartile net dollar retention from portfolio operating data. Comparing your median

against a published top quartile will always make you look broken.

SaaS Capital's own top quartile reaches 118–120% above $100K ACV — which reconciles cleanly with

the ICONIQ figure once you compare like with like.

Use: match the statistic first. If a source does not say whether a figure

is a median or a quartile, do not use it.

• Yes SaaS Capital · 110% above $250K
• No High Alpha · peaks $10–100K

A genuine, unresolved disagreement between two large panels on the same cut. SaaS Capital finds NRR

rising monotonically with ACV; High Alpha finds it peaking in the $10K–$100K range and flattening or

dipping above. Both agree GRR rises with ACV.

Plausible reconciliations: different survey years and macro conditions; High Alpha's panel skews

earlier-stage, so its high-ACV cell may capture young enterprise sellers rather than mature ones;

and per-band sample sizes at the top end are small in both.

Use: treat "higher ACV, higher retention" as well-established through

$100K. Above $100K, hold the estimate loosely and weight your own data more heavily.

• −6 wks ICONIQ · 25→19 wks, H1→H2 2025
• Longer Bridge Group · majority report increases

ICONIQ's average cycle fell six weeks across 2025. The Bridge Group's 2026 AE research reports that

near-majorities saw increases in stakeholder count, cycle length, discounting pressure and

deal slippage against Q1 2025.

The likely reconciliation sits in ICONIQ's own data: over the same period the share of new-logo

contracts under one year rose from 2% to 13%, and three-year contracts fell from 36% to 23%. Shorter,

smaller, more reversible commitments close faster. That is a change in what is being bought, not

necessarily an improvement in how it is sold.

Use: never read a cycle-time improvement without checking contract length

and deal size alongside it. Cycle time falling while contract duration falls is a mix shift.

Source directory

Every figure in this corpus traces to one of these. All seven are free at time of writing.

Cite the publisher, the edition year and the sample — never this page alone.

• The State of Go-to-Market · annual
• Edition March 2026, from a January 2026 survey
• Sample 150+ B2B software GTM executives (CRO, Head of Sales, CEO, Head of RevOps)

Panel $10M–$500M+ revenue. ACV: 42% at $100K–$500K, 22% at $50–100K, 20% at $10–50K.

• 62% sales-led, 31% hybrid, 7% PLG
• Segments by ACV, revenue band, growth rate, motion
• Best for: sales cycle and funnel conversion by ACV. The only source publishing

a clean by-ACV cycle-time curve.

Bias: portfolio-adjacent and upmarket. Flatters anyone below $25K ACV.

Per-chart n falls as low as 9 in the lowest ACV band. Publishes averages, not medians, for

funnel metrics.

iconiq.com/growth/reports/state-of-go-to-market-2026

• Annual survey + retention research briefs
• Edition Retention Brief 28 (12th annual); 2026 spending benchmarks
• Sample 1,000–1,500+ private B2B SaaS companies, largest of its kind
• Panel Private B2B SaaS incl. bootstrapped; excludes <$1M ARR from most cuts
• Segments by ACV, ARR, age, funding type, contract length, vertical/horizontal
• Best for: retention by ACV. The only source with enough n to publish NRR

quartiles by ACV band, and it states its formula explicitly.

Bias: a growth-debt lender, so the respondent pool skews toward companies

with real revenue and reasonable retention. Self-reported.

saas-capital.com/research

• SaaS Benchmarks Report · annual · 9th edition
• Edition 2025 (published late 2025)
• Sample 800+ respondents; ~5,000 companies cumulatively over nine years
• Panel 23% <$1M ARR, 27% $1–5M, 31% $5–20M, 10% $20–50M, 9% >$50M. 69% US. 50% CEO/founder
• Segments by ARR, ACV, GTM channel, pricing model
• Best for: the full operating picture at the early and growth stages , with

quartiles on every metric and an explicit definitions page.

Bias: earlier-stage and PLG-weighted; the natural complement to ICONIQ's

upmarket panel. This is the continuation of the OpenView benchmarks — Kyle Poyar took the report

to High Alpha after OpenView wound down.

highalpha.com/saas-benchmarks

• AE and SDR Metrics research · biennial · since 2007
• Edition 2026 AE research (10th); 2025 SDR research (10th)
• Sample 158 companies (AE); 351 companies (SDR)
• Panel 83% B2B SaaS, 78% North America, $47M median revenue, $50K median ASP
• Segments by ACV band, segment, motion
• Best for: rep-level economics. Quota, ramp, attainment, OTE, SDR:AE ratio,

activity levels — nothing else covers this ground, and the time series runs to 2007.

Bias: the most conservative panel here; its win rate and attainment figures

run well below the VC-published surveys. Arguably the most representative of an ordinary company.

bridgegroupinc.com/research

• SaaS Performance Metrics + B2B Marketing Benchmarks · annual
• Edition 2025 performance metrics; 2026 marketing benchmarks
• Sample Not consistently disclosed per chart
• Segments by ARR, ACV, GTM motion, target customer, product category, VC- vs PE-backed
• Best for: definitional rigour on efficiency metrics. Maintains the

new/blended/expansion CAC ratio family properly and has an interactive filter by company profile.

Bias: per-chart sample sizes are the least transparent of the seven.

Strong on finance metrics, thinner on funnel.

benchmarkit.ai

• Private Company SaaS Survey · annual · 16th edition
• Edition November 2025
• Sample Several hundred private SaaS companies; median ACV $62K in the 2024 edition
• Segments by ACV, growth rate, ARR, GTM motion
• Best for: the P&L context around the funnel — CAC ratio, magic number,

S&M as a share of revenue, retention, and the longest-running private SaaS operating time series.

Bias: an investment bank's survey; respondents skew toward companies of

banking interest. Headline findings are public; the full detail requires requesting the report.

key.com · SaaS survey

• Field studies from a delivery panel of 40–65 B2B software companies
• Editions GTM Tech Stack (50+ cos), AI Workflows in GTM (40+ cos), RevOps Investment
• (11 reconciled sources)
• Method Provenance-verified sweeps of delivery records, customer calls and shared
• Slack channels — observed behaviour rather than self-report
• Best for: what companies actually run , as opposed to what they report on a

survey. The only non-self-reported panel in this corpus.

Bias: LeanScale's own customer base — growth-stage B2B software that has

engaged a RevOps partner. Smaller n than the survey houses.

• knowledge.leanscale.team
• Methodology

01

No LeanScale customer data underlies the benchmark figures on this page. Every

number is attributed to a named third-party publisher, edition and sample. Where LeanScale's own

measurement appears it is labelled as such.

02

Figures were taken from the publishers' own PDFs, research briefs and press

releases. Search results for "SaaS benchmarks" are now dominated by AI-generated aggregator sites

that invent precise-sounding numbers with no survey behind them; none were used, and none should be.

03

Survey panels are opt-in, and companies having a bad year do not fill out the

survey. Assume a consistent upward bias across all of it. Billing-data sources read low for the

opposite reason; bracketing the two is better than trusting either.

04

SaaS Capital, High Alpha and ICONIQ publish formulas; those are quoted. Where a

publisher does not define a metric, the definition card says so and the figure is flagged as

convention-blended rather than presented as precise.

05

Where a publisher discloses per-chart n, it is carried through — including

where it is uncomfortably small, such as the nine companies behind the sub-$10K ACV sales-cycle

figure.

06

Cite the original publisher, edition year and sample — for example: "ICONIQ

Growth, State of Go-to-Market 2026 (January 2026 survey, n=157)". This corpus is a finding aid and

a definition layer, not a primary source.

• The standing recommendation
• Use this corpus to answer "are we structurally normal for our price point?"
• For "what should we fix?", compute your own stage conversion on an entered-cohort

basis and compare the company against its own trailing quarters. That comparison is the only one

where the definition is guaranteed constant — which is the whole argument of this page.

LeanScale

LeanScale is a revenue operations partner for growth-stage B2B software companies. We build the

GTM systems, reporting and process that turn a sales motion into a repeatable machine.

Reference corpus compiled August 2026. Benchmark figures belong to their publishers

and are reproduced here with attribution for comparison and definitional reconciliation. Editions

change annually — check the source before quoting a figure in a client deliverable.

• ICONIQ Growth · State of Go-to-Market 2026
• SaaS Capital · Retention Benchmarks & annual survey
• High Alpha · 2025 SaaS Benchmarks Report
• The Bridge Group · AE & SDR Metrics research
• Benchmarkit · SaaS Performance Metrics
• KeyBanc Capital Markets + Sapphire Ventures
• LeanScale field studies
• www.leanscale.team