SaaS Metrics School

Ben Murray
  • 4.6 (11)
  • Management
  • Updated Weekly

Ben Murray brings you actionable SaaS metrics lessons that he has learned through years of being in the SaaS CFO trenches. Whether you are new to SaaS or a SaaS veteran, learn the latest SaaS and AI metrics, finance, and accounting tactics that drive financial transparency and improved decision-making. Ben’s SaaS metrics blog consistently rates a 70+ NPS, and his templates have been downloaded over 100,000 times. There is always something to learn about SaaS and AI metrics.

  1. Sep 26

    What Public SaaS Comps Reveal About Earning a Premium Valuation Multiple

    Only 9% of public software companies trade above 10x revenue — do you know which metrics separate them from the 68% stuck below 5x? In episode #389, Ben Murray breaks down what public comps reveal about how premium SaaS valuations are actually created. You can't value a private SaaS business straight off public multiples, but the correlations between metrics and enterprise value tell you exactly what buyers reward — and if you're a founder or CFO eyeing an exit, these are the numbers that will decide whether you land the index median or the premium multiple. The real distribution of public software multiples — 68% below 5x revenue, 23% at 5–10x, and just 9% above 10x — and what it takes to reach the cream of the crop. How net revenue retention maps to valuation: NRR below 100% earns a 3.1x EV-to-revenue multiple, the index median sits at 5.7x, and companies above 120% NRR command 9.3x. Why retention sits at the top of the valuation pyramid and drives premium multiples in bear markets and bull markets alike. Why two companies hitting the same Rule of 40 get different valuations — and why 30% growth + 10% EBITDA beats 30% EBITDA + 10% growth. How to pressure-test your own exit readiness: if you can't confidently enter your metrics into a valuation calculator, your finance data foundation isn't ready for due diligence. Tune in to see where your SaaS would land on the valuation curve — before a buyer runs the numbers for you. Resources Mentioned Ben's SaaS Exit Readiness blog post (four pillars + valuation framework):  Contact Ben for help on preparing for an exit: https://www.thesaascfo.com/contact/

  2. Sep 24

    Founders, Are You Exit Ready?

    Founders, if a buyer asked for your metrics tomorrow, could your data prove your financial performance or would holes in it kill the deal? In episode #388, Ben Murray breaks down the metrics acquirers use to underwrite your SaaS business — and why so many exits fail before they start. Due diligence is about de-risking the acquisition, and buyers with deep bench strength will pour through your data looking for weaknesses. If you can't control the financial narrative with accurate, defensible metrics, they'll write it for you — and your valuation will pay the price. The four metric pillars buyers scrutinize in due diligence — retention quality, growth, capital efficiency, and margin architecture — and why retention is still king. The GRR threshold many private equity firms treat as a hard floor (hint: it's 90%) and why the gap between GRR and NRR matters for every recurring revenue stream. Why two companies with the same Rule of 40 score get very different valuations — and which composition earns the premium. The capital efficiency metrics on the exam — burn multiple, CAC payback, ARR per FTE — and how go-to-market efficiency changes how much capital a buyer must invest post-acquisition. Why AI-native margins are rotating back to 70–80% software expectations, and how a correctly structured SaaS P&L lets you explain your margin by revenue stream. The minimum runway Ben recommends for exit prep — 6 months of data foundation work — so you hand buyers numbers you're confident in. Tune in before your next investor conversation — because if you're eyeing an exit in the next year or two, the data prep starts now. Resources Mentioned Ben's SaaS Exit Readiness blog post: https://www.thesaascfo.com/saas-exit-readiness-score/ Contact Ben for exit-ready services: https://www.thesaascfo.com/contact/

  3. Sep 16

    Your Dev Team's AI Bills Are Hitting the Wrong Line on Your P&L

    Is your dev team's AI spend buried in the wrong part of your P&L — quietly distorting your gross margin and making your AI ROI impossible to measure? In episode #387, Ben Murray tackles one of the most pressing accounting questions hitting SaaS CFOs and controllers right now: how to properly classify AI development costs across your chart of accounts. With dev teams racking up daily charges from multiple AI providers, getting these expense codes wrong doesn't just create accounting noise — it misrepresents your gross margin, obscures your true AI economics, and leaves you unable to answer board questions about AI ROI. The right GL structure makes all the difference. The single most important question to answer first: is the AI cost production-facing (customer-serving inference) or internal engineering use — because the answer determines whether it hits COGS or OpEx, and your gross margin depends on getting this right. A full breakdown of the five AI cost categories SaaS companies are facing today — production inference, dev/testing inference, model training and fine-tuning, GPU compute for production serving, and vector database infrastructure — and exactly where each one belongs on the P&L. Why model training and fine-tuning costs may need to be capitalized rather than expensed, just like other qualifying software development costs under existing accounting guidance. Why internal AI tool spend (Copilot, ChatGPT, Claude, etc.) needs its own dedicated GL account — separate from internal-use software — so you can actually measure efficiency gains and answer the AI ROI question when the board asks. Why this isn't optional housekeeping: as AI costs grow, the difference between properly coded and miscoded AI expenses will show up directly in your gross margin and in how investors read your unit economics. Tune in to get the GL coding framework SaaS CFOs are building now — before AI expenses get too big to untangle. Resources Mentioned Ben's AI COGS blog post (detailed GL coding guidance): https://www.thesaascfo.com/what-should-be-included-in-ai-cogs/

  4. Aug 27

    Why AI-Powered SaaS Dashboards Are Making ERP Reporting Obsolete

    Is your ERP dashboard actually built on data that matters — or is it just a chart of accounts dressed up to look useful? In episode #386, Ben Murray breaks down why traditional ERP dashboards are losing ground to AI-generated, prompt-built SaaS reporting and what that means for CFOs and finance leaders right now. If your team is still relying on static dashboards anchored to your general ledger, you're missing three out of four key SaaS data sources before you even start the analysis. The gap between what ERP dashboards can show and what modern AI-native metrics engines can produce is widening fast  and the CFOs who close that gap first will be the ones driving the board conversations. Why ERP dashboards are fundamentally limited to chart-of-accounts data — and the three additional SaaS data sources (HRIS, bookings, and customer/revenue data) that actually drive metrics like CAC payback, LTV to CAC, NRR, and Rule of 40. How Ben vibe-coded a full SaaS metrics dashboard in minutes using Claude — covering ARR trajectory, EBITDA margin, gross margin, revenue per FTE, and cash balance — and why a prompt-built report on a deterministic engine beats any canned dashboard. Why controlling the period of measurement matters: the example of setting CAC payback on a six-month sales cycle basis — something a standard ERP dashboard simply can't do. Where AI actually belongs in the FP&A process: not at the beginning, but at the end — writing board narratives, flagging dormant customers ripe for expansion via a RevIntel engine, and generating insights that traditional FP&A could never surface. Why agent-friendly APIs matter: how Saster's API grading tool surfaces whether your SaaS stack is actually exposing the data AI needs to take action — not just technically having an API. Tune in to understand exactly where your ERP dashboard ends and where a closed-loop, AI-powered metrics engine takes over — before your next board meeting. Resources Mentioned Ben's LinkedIn post (vibe-coded SaaS metrics report): https://www.linkedin.com/posts/benrmurray_saas-activity-7498039803582689280-7Ckt?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAOOEO8Bf5aRLyU0jjrGXvPD2odJNDer6KU Ben's deterministic SaaS metrics engine: https://softwaremetrics.ai Ben's Five Pillar SaaS Metrics Framework: https://www.thesaasacademy.com/saas-metrics-implementation-sprint-sept-2026

  5. Aug 22

    How AI Is Writing 84-Data-Point Board Reports — And Why CFOs Can Trust Them

    What if AI could produce a better board memo than any CFO — and you could trust every data point in it? In episode #385, Ben Murray breaks down how he is using AI to generate complete 5-page financial board reports, and more importantly, why the outputs are reliable. This isn't AI hype — it's a working FP&A process Ben is running today inside his fractional CFO practice. If you're still manually assembling dashboards, PDFs, and narrative summaries before every board meeting, this episode reframes what's actually possible right now. Why a deterministic metrics engine — not AI — is the non-negotiable foundation that makes AI-written board reports trustworthy (and how Ben built one backed by 35 pages of documentation) The exact structure of a SaaS financial board report: executive overview, metrics vs. benchmarks, ARR growth, customer retention, GTM efficiency, financial capacity, data anomalies, and top priorities — all generated by AI How Ben identified 84 unique data points in a single AI-written board memo using ChatGPT — and why that number changes how you think about QA The MCP connection to SoftwareMetrics.ai that makes this a repeatable monthly process — and how Replit is now building it as a native app feature What's coming in October: Ben's SaaS Metric Sprint, a live walkthrough of building the data foundation, calculating metrics, and connecting MCP so you can run this for your own company Tune in to see how Ben is turning month-end close into a board-ready narrative in minutes — and how you can build the same process for your SaaS company. Resources Mentioned Ben's app: https://softwaremetrics.ai/ SaaS Metric Sprint (October 6th): https://www.thesaasacademy.com/saas-metrics-implementation-sprint-sept-2026

  6. Aug 19

    Should AI Run Your Board Meetings? A CFO's Framework for AI-Prepped Board Packages

    Is your board meeting time being wasted on reporting instead of judgment and quality discussion? In episode #384, Ben Murray addresses how AI can transform board meeting prep for SaaS finance leaders. If your board decks are packed with data but the important issues still get buried, and board members show up with wildly different levels of prep, you already know the problem. Every hour spent reviewing numbers that should have been read beforehand is an hour not spent on the judgment calls that actually move the business forward. Understand the core frustration behind Jason Lemkin's "AI board member" post and why it resonates with CFOs building out their FP&A process See how AI can do a first analytical pass through your financials, metrics, and benchmarks before the meeting ever starts Learn how to use AI to set a focused board agenda: the 3 issues that matter, the 5 metrics that don't need discussion, and the questions still unanswered Get Ben's real-world example of using an AI agent to identify top 3 board priorities and pull follow-up ownership from meeting transcripts Discover why a deterministic data engine, not just a chatbot, is the real key to accurate AI-written financial narratives and agendas Tune in to see exactly how Ben is putting Jason Lemkin's AI board member idea into practice, before your next board meeting rolls around. Resources Mentioned Jason Lemkin's SaaStr post on AI and board meetings: https://www.saastr.com/the-ai-board-member-why-yours-should-chair-the-next-meeting-for-real/? What I'm using: https://softwaremetrics.ai/ CFO courses: https://www.thesaasacademy.com/

  7. Aug 8

    How to Vibe Code Finance Dashboards for Your SaaS Metrics

    Can you actually trust the numbers when AI writes your board report? In episode #383, Ben Murray breaks down how to vibe code finance dashboards that hold up to CFO standards. Every finance leader is being sold the same promise: that AI will do your analysis for you, but the hype skips the part that decides whether the output is usable. If you are putting AI-written numbers in front of your board or investors, the difference between a trusted report and an embarrassing one comes down to work most CFOs never do. Why the data foundation, not a magic prompt, decides whether your AI dashboards can be trusted How a deterministic metrics engine keeps AI away from your calculations while it writes the narrative on top The Cisco playbook for letting AI draft 80 to 90 percent of your board commentary before you finish it off How to turn an LLM-generated HTML dashboard into a live, refreshable report in about 5 minutes Which model, ChatGPT, Claude, or Gemini, actually produces the best-looking finance dashboards Tune in to get the exact process CFOs are using to put AI-written reports in front of their boards with the numbers they can defend. Resources Mentioned Webinar: How I Vibe Code Finance Dashboards, plus templates: https://www.thesaasacademy.com/pl/2148817040 SaaS Metrics Sprint, October cohort: https://www.thesaasacademy.com/saas-metrics-implementation-sprint-sept-2026 Tech CFO community: https://docs.google.com/forms/d/e/1FAIpQLSfP4uwvwEoc92Qc_rS8eu-9EzV6shivPbBhaNcPqsy5sNVNNg/viewform?usp=dialog

  8. Aug 7

    The 2026 ARR per Employee Benchmarks: Where Top-Quartile SaaS Actually Lands

    Seeing the millions-per-employee AI headlines and wondering where your SaaS company actually stands? In episode #382, Ben Murray covers the latest ARR per FTE benchmarks from Ray Rike's Benchmarkit data. Social media is full of ARR per employee hype, but almost none of it tells you how the number was defined, whether contractors are counted, or how your company compares once you cut the data the way it actually matters. If you are benchmarking efficiency for a board deck, a raise, or a headcount plan, the aggregate number can quietly send you the wrong signal. This episode grounds the metric in real survey data so you know what good looks like for a company your size, in your region, with your pricing model. Know the headline numbers: bottom quartile at 127K, median at 193K, and top quartile at 279K of ARR per employee across the full SaaS population. See how pricing model changes everything, from usage-based leading at 291K down to subscription plus usage hybrids at 136K. Understand why efficiency can drop in the 50 to 100 million ARR band instead of climbing, and what that says about your next phase of growth. Compare the cuts that actually move the number: North America versus EMEA, and horizontal B2B versus vertical SaaS. Learn why aggregate benchmarks can be dangerous to your SaaS health, and why size and pricing bands beat the total-population average every time. Tune in to see where your ARR per employee really stands before you use it in your next board deck or fundraise. Resources Mentioned Benchmarkit (Ray Rike) - benchmarkit.ai Ben Murray's blog post with the full data cuts: https://www.thesaascfo.com/arr-per-employee-benchmarks/

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About

Ben Murray brings you actionable SaaS metrics lessons that he has learned through years of being in the SaaS CFO trenches. Whether you are new to SaaS or a SaaS veteran, learn the latest SaaS and AI metrics, finance, and accounting tactics that drive financial transparency and improved decision-making. Ben’s SaaS metrics blog consistently rates a 70+ NPS, and his templates have been downloaded over 100,000 times. There is always something to learn about SaaS and AI metrics.

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