Live · Bench Open Issue 218 · 2026-04-30 · 15:42 UTC Coverage: 144 public SaaS · 28 private rounds tracked research@yourbusiness.com
SNOWNDR128%+2.1pp| DDOGRoF53.4+4.8| MDBEV/NTM9.4x−0.6| CRWDARR YoY28%+1.4| NETMagic0.94flat| ZSFCF Mgn26.1%+3.2| HUBSNDR104%−1.2pp| PANWRoF42.0+0.6| OKTAARR YoY14%−2.1| TEAMEV/NTM11.2x+0.8| VEEVNDR107%+0.4pp| SHOPGMV YoY31%+5.2| ZMFCF Mgn39.4%+1.1| DOCNMagic0.62−0.08| SNOWNDR128%+2.1pp| DDOGRoF53.4+4.8| MDBEV/NTM9.4x−0.6| CRWDARR YoY28%+1.4| NETMagic0.94flat| ZSFCF Mgn26.1%+3.2| HUBSNDR104%−1.2pp| PANWRoF42.0+0.6| OKTAARR YoY14%−2.1| TEAMEV/NTM11.2x+0.8| VEEVNDR107%+0.4pp| SHOPGMV YoY31%+5.2| ZMFCF Mgn39.4%+1.1| DOCNMagic0.62−0.08
Issue 218 / 2026·Q2 / Subscriber Bench

SaaS public-comp research,
published like a terminal.

A working analyst bench. We track 144 public SaaS companies and 28 private rounds across NDR, ARR growth, Rule of 40, magic number, and forward EV/Revenue multiples. Subscribers receive the weekly research and the live bench data. Three reports are open to the public.

> search:research_archive | filter:tier=enterprise_saas | cohort:$1B+_ARR | as_of:2026-04-30
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Bench Snapshot · 144 covered

Median SaaS public-comp metrics.

As of 2026-04-30 · refreshed Mon 06:00 UTC
Median NDRNDR
112%
▲ +2.4ppprior 109.6%
Median ARR YoYARR
22%
▼ −1.8ppprior 23.8%
Median Rule of 40RoF
38.4
▲ +3.6prior 34.8
Median Magic NumberMAGIC
0.84
▲ +0.06prior 0.78
Median EV / NTM RevEV/NTM
8.6x
▼ −0.4xprior 9.0x
Median FCF MarginFCF
21.2%
▲ +2.1ppprior 19.1%
Public-Comp Bench

Top twelve names by NTM revenue.

All Tiers $1B+ ARR Vertical SaaS DevTools SecOps Data Infra
Ticker / Name ↕NDR ↕ARR YoY ↕RoF ↕Magic ↕EV/NTM ↕Status
01SNOWSnowflake — Data Infra128%+27%52.40.9412.4xOpen
02DDOGDatadog — Observability114%+25%53.41.0214.6xOpen
03MDBMongoDB — Data Infra119%+22%38.60.789.4xWatch
04CRWDCrowdStrike — SecOps115%+28%48.01.1015.2xOpen
05NETCloudflare — Edge / Net112%+27%31.60.9416.1xWatch
06ZSZscaler — SecOps116%+30%56.11.1812.8xOpen
07HUBSHubSpot — Marketing104%+18%36.00.718.2xWatch
08PANWPalo Alto — SecOps110%+16%42.00.8811.4xOpen
09OKTAOkta — Identity106%+14%26.40.465.8xCaution
10TEAMAtlassian — DevTools112%+19%34.80.8411.2xOpen
11VEEVVeeva — Vertical SaaS107%+13%38.20.6210.1xOpen
12DOCNDigitalOcean — Cloud103%+11%23.40.624.2xCaution
showing 12 of 144 covered names → open the full bench (subscribers)

Featured ResearchThree open · the rest gated

All Featured Subscriber-only Free
RPT-2182026-04-30
● Open · No Paywall

The Rule of 40 broke this quarter, and three names didn't tell you.

Median Rule of 40 across the bench rose 360 bps to 38.4 — the largest single-quarter expansion in five years. But the median masks a real bifurcation between AI-native infra names and legacy app SaaS.

We name three companies whose disclosed numbers conceal compounding net-revenue churn that would, if surfaced, drop them out of the band entirely.

By Priya Iyer22 min read
RPT-2172026-04-23

Magic Number, after the AI-credit accounting normalises.

Net new ARR in Q1 carried a meaningful contribution from prepaid AI consumption credits. We strip those out of nine bench names and recompute the magic number on a normalised basis — the picture changes.

Three names move from healthy (≥0.75) to caution (≤0.50) once credits are excluded. One name moves the other direction.

🔒 Subscribers · $89/mo
By Marcus Chen34 min read
RPT-2162026-04-16

EV/NTM compression in vertical SaaS, by sub-vertical.

Vertical SaaS multiples compressed 80 bps faster than horizontal SaaS over the last twelve months. We disaggregate the bench by sub-vertical (legal, healthcare, construction, accounting) and find the compression is concentrated in two of those four.

Detailed regression on TAM, NDR, and gross margin against forward multiple, with a one-page screener for institutional subscribers.

🔒 Subscribers · $89/mo
By Devon Park41 min read
Open full archive →
Methodology

Every metric, defined in code.

We publish the math we use, line by line. The bench is rebuilt every Monday at 06:00 UTC from filed-quarter data. No hand-wavy heuristics. If the number isn't reproducible from the formula on the right, we don't publish it.

  •  Reproducible from filings + ARR triangulation
  •  Refreshed weekly Mon 06:00 UTC
  •  Corrections logged in a public errata
  •  Sample n ≥ 30 for any cohort statistic
Read full methodology →
01# rule_of_forty.py
02# growth + fcf margin, trailing four quarters
03
04def rule_of_40(arr_yoy, fcf_mgn):
05    return arr_yoy + fcf_mgn
06
07# magic_number.py
08# sales-efficiency: net new ARR / s&m spend, lagged one
09
10def magic_number(arr_q, arr_q_prior, sm_spend_q_prior):
11    net_new = (arr_q - arr_q_prior) * 4
12    return net_new / sm_spend_q_prior
13
14# bench refresh: cron 0 6 * * MON UTC
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