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SaaS Metrics School
SaaS Metrics School
Author: Ben Murray
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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 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 metrics.
339 Episodes
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In episode #339 of SaaS Metrics School, Ben explains how change of control provisions in customer contracts can quietly derail due diligence, fundraising, or a future company exit. Drawing from real-world CFO experience and a recent webinar with a SaaS-focused tech attorney, Ben breaks down why seemingly standard legal language can introduce major risk into a SaaS company’s recurring revenue profile.
Ben highlights how buyers and investors scrutinize customer contracts during due diligence—and why poorly structured MSAs can threaten valuation, increase churn risk, or even kill a deal outright.
What You’ll Learn
What a change of control provision is and why it matters
How customer contracts are reviewed during SaaS due diligence
Why change of control clauses can open the door to customer churn after an acquisition
How procurement teams and customer legal teams typically push for these provisions
When to push back, escalate, or seek alternative contract language
Why contract structure is part of strong SaaS financial and operational readiness
Why It Matters
Customer contracts directly impact company valuation during an exit or fundraise
Change of control provisions can trigger immediate churn risk post-acquisition
Buyers want confidence in the durability of recurring revenue
Poor legal hygiene can delay, discount, or kill a transaction
Proactive contract review reduces future due diligence friction
Strong back-office processes support long-term financial strategy and investor trust
Resources Mentioned
Webinar replay with Omid (tech attorney) on legal readiness for SaaS exits: https://www.thesaasacademy.com/pl/2148384654
SaaS Metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #338 of SaaS Metrics School, Ben explains how to quickly sanity-check your sales and marketing forecast for the upcoming year using one high-signal SaaS metric: the Cost of ARR. As founders and CFOs finalize budgets, Ben shows how mismatches between projected bookings and planned go-to-market spend can reveal unrealistic assumptions before they turn into missed targets.
Using simple examples, Ben walks through how the Cost of ARR connects sales and marketing spend, net new ARR bookings, and historical performance—making it one of the most effective tools for validating SaaS and AI company forecasts during budget season.
What You’ll Learn
How to use the Cost of ARR to validate your sales and marketing budget
The relationship between sales and marketing spend and net new ARR bookings
How to identify unrealistic growth assumptions in your forecast
The difference between blended the Cost of ARR, Cost of New ARR, and Cost of Expansion ARR
Why historical performance should anchor forward-looking forecasts
How benchmarking by ACV and sales motion improves forecast accuracy
Why It Matters
Sales and marketing forecasts often fail because spend and bookings assumptions are disconnected
Cost of ARR provides a mechanical reality check before committing to a budget
Overly aggressive ARR targets can be identified early and corrected
Underspending on go-to-market becomes visible when bookings expectations are too conservative
Benchmarking against peers helps validate whether forecast assumptions are realistic
Strong financial modeling and forecasting discipline improves board and investor confidence
Resources Mentioned
Cost of ARR metric framework: https://www.thesaascfo.com/saas-cac-ratio/
Benchmarking data from Ray Rike at Benchmarkit.ai
Concepts from SaaS FP&A forecasting and go-to-market efficiency analysis: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #337 of SaaS Metrics School, Ben breaks down why software revenue categorization is a foundational requirement for strong finance, accounting, and SaaS metrics. He explains the core revenue types every SaaS, AI, or software company should separate on their P&L—and why commingling revenue creates downstream issues in MRR tracking, retention metrics, forecasting, and company valuation.
Ben walks through the major recurring and non-recurring revenue categories, then shows how clean revenue segmentation enables accurate MRR schedules, retention analysis, cash flow forecasting, and smoother due diligence with investors and acquirers.
What You’ll Learn
The core revenue categories every SaaS or AI company should clearly define
The difference between subscription, usage, overage, services, managed services, and hardware revenue
Why overages must be separated at both the SKU and general ledger level
How revenue categorization feeds directly into MRR schedules and waterfalls
Why recurring and variable revenue must be forecasted differently
How clean revenue data improves retention metrics and go-to-market efficiency analysis
Why investors and acquirers expect revenue clarity during fundraising and due diligence
Why It Matters
Accurate MRR and ARR tracking depends on clearly defined revenue streams
Retention metrics (GRR and NRR) break when revenue types are mixed together
Revenue forecasting and financial modeling require different assumptions by revenue type
Cash flow forecasting becomes unreliable without segmented recurring revenue data
Company valuation is directly impacted by the perceived quality of recurring revenue
Investors and acquirers expect detailed revenue schedules during fundraising and due diligence
Strong financial systems and accounting discipline reduce friction in audits and exits
Resources Mentioned
Ben’s SaaS revenue hierarchy framework: https://www.thesaascfo.com/the-saas-revenue-hierarchy-why-defining-your-revenue-streams-matter/
SaaS Metrics course at The SaaS Academy: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #336, Ben Murray breaks down his top three go-to-market efficiency metrics that every SaaS and AI operator should master. He explains when each metric becomes meaningful, how they differ across go-to-market motions, why ACV-based benchmarking matters, and how these metrics become forward-looking tools through forecasting. Ben also highlights the importance of having fully burdened sales and marketing expenses in place so these efficiency metrics are accurate and defensible.
What You’ll Learn
The three most important go-to-market efficiency metrics and why they matter
How ACV—not ARR—should drive your benchmarking
Why these metrics are proactive when used in forecasting, not just historical
How revenue types (subscription vs. usage vs. platform/overage) influence metric design
The foundational role of fully burdened sales and marketing expenses
Why It Matters
Enables operators to measure the true efficiency of sales and marketing investments
Provides clarity on the health and scalability of the go-to-market motion
Helps leadership benchmark realistically against peers using ACV-based expectations
Allows finance teams to forecast forward-looking efficiency, not just track history
Ensures efficiency metrics remain accurate as product pricing and revenue models evolve
Prevents major errors caused by incomplete or misallocated CAC inputs
Resources Mentioned
Ben’s SaaS Metrics Framework (Pillar 5: Go-to-Market Efficiency): https://www.thesaasacademy.com/the-saas-metrics-foundation
Ray Rike's benchmarking data at benchmarkit.ai
Blog posts on modifying metrics for subscription + usage revenue models: https://www.thesaascfo.com/how-to-calculate-cac-payback-period-with-variable-revenue/
In episode #335, Ben answers a common operator question: Should Customer Success be included in the cost of customer acquisition (CAC)? He explains how Customer Success should be coded based on responsibilities, when it belongs in COGS vs. Sales, and when CS expenses should be included in expansion efficiency metrics.
What You’ll Learn
Why CAC applies only to acquiring new customers.
How Customer Success roles differ between adoption, retention, renewals, and expansion.
When Customer Success expenses should be included in the cost of expansion ARR.
How to allocate Sales, Marketing, and CS expenses between new and existing revenue.
Why proper allocation is foundational for CAC payback, LTV to CAC, and Cost of ARR.
Why It Matters
Prevents inflated or misleading CAC and go-to-market efficiency metrics.
Ensures expansion ARR economics are calculated accurately.
Helps leaders understand the true cost structure behind revenue growth.
Supports cleaner financial models, better forecasting, and stronger investor discussions.
Aligns internal teams (CS, Sales, Finance) on roles and financial impact.
Resources Mentioned
SaaS Metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #334, Ben Murray breaks down how leading public SaaS and tech companies are reporting AI-driven value creation across their earnings calls. After analyzing more than 130 public tech earnings transcripts, Ben identifies five consistent themes in how incumbents communicate AI monetization, margin impact, revenue growth, and operational transformation to Wall Street.
These insights are critical for private SaaS and AI founders who want to understand how to position their own AI value story for Boards, investors, and future fundraising. As AI moves beyond the hype cycle, companies must clearly demonstrate monetization, adoption, and financial impact—not just vision and roadmap.
Why It Matters
Understanding how public companies frame AI value creation helps private founders avoid vague positioning and instead adopt investor-grade communication. These themes influence:
Board reporting
Fundraising narratives
ARR and revenue forecasting
Financial modeling
Unit economics and cost structure decisions
Long-term valuation strategy
As AI transitions from hype to monetization to full transformation, founders must adapt how they report AI’s contribution to performance and financial outcomes.
Resources Mentioned:
Reporting AI ARR: https://www.thesaascfo.com/ai-arr-vs-saas-arr-how-to-define-and-calculate/
SaaS Metrics Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #333, Ben answers a foundational SaaS metrics question: Should expansion revenue be included in your Lifetime Value (LTV) calculation? Ben walks through the correct LTV formula and highlights how misalignment between LTV and CAC can distort your LTV:CAC ratio. He also covers when expansion should be included.
The episode provides a practical framework for SaaS founders, CFOs, and operators to ensure they calculate LTV accurately, compare it properly to CAC, and model unit economics using consistent, reliable inputs.
Key Topics Covered
The correct LTV formula using average new-customer MRR × subscription gross margin
Why the churn input should align with dollar-based metrics using 1 – Gross Revenue Retention (GRR)
Why expansion revenue is deliberately excluded from LTV in most SaaS models
How including expansion artificially inflates the LTV:CAC ratio
The cost mismatch between acquiring new customers (CAC) and generating expansion revenue
When PLG motions justify including limited, time-bound expansion revenue in LTV
How organic upgrades differ from sales-assisted expansion
How SaaS+ businesses must adjust their LTV formula to account for usage revenue
The role of gross margin in determining true unit economics
The importance of aligning metric definitions when evaluating customer profitability
Why This Matters
This episode is essential for:
SaaS founders calculating LTV for budgeting, pricing, and forecasting
CFOs, controllers, and FP&A leaders managing unit economics and CAC payback
Finance teams modelling customer profitability and revenue expansion
Operators working in PLG environments assessing organic expansion patterns
Investors reviewing LTV:CAC ratios in diligence and portfolio monitoring
Anyone building SaaS Plus (subscription + usage) revenue models
Resources Mentioned
Ben’s deep dive on SaaS+ LTV: https://www.thesaascfo.com/how-to-calculate-ltv-with-variable-revenue/
SaaS Metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #332, Ben Murray explains why AI companies with high inference costs and lower gross profit margins must scale dramatically faster—up to 6x larger—to match the financial performance of a comparable SaaS business. Using simple financial modeling and the core principles of SaaS economics, Ben breaks down how AI margins, variable COGS, and TAM expansion interact to shape the financial trajectory of AI-native companies.
This episode builds on a recent blog post and downloadable Excel model, both linked in the show notes.
Key Topics Covered
Why SaaS metrics still apply to AI companies, but with different economic inputs
The impact of AI inference costs on gross margin and scalability
Comparing a SaaS company at 80 percent gross margin vs. an AI company at 55 percent
Why an AI company needs 6x the revenue to generate the same EBITDA
How lower gross profit changes cash flow, EBITDA, and company valuation
Why larger TAM and higher ACV potential in AI may offset lower margins
How attacking labor budgets expands revenue opportunity for AI products
The myth that SaaS metrics are “broken” for AI companies
Understanding how COGS scale in SaaS vs. AI and why the math still works
Evaluating OPEX profiles when modeling scale scenarios
How to use the downloadable template to test scenarios for your own AI or SaaS business
Why This Matters
This episode is critical for:
AI founders modeling their unit economics
SaaS founders embedding AI and needing to understand margin changes
CFOs, controllers, FP&A leaders, and finance teams navigating AI cost structures
Investors assessing the scalability and valuation profile of AI companies
Operators planning cash runway, revenue forecasts, and growth investment
Understanding these financial dynamics early ensures you can forecast accurately, raise capital more effectively, and prepare for due diligence with confidence.
Resources Mentioned
Full blog post on AI vs. SaaS economics: https://www.thesaascfo.com/the-real-economics-of-saas-versus-ai-companies/
SaaS Metrics Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #331, Ben breaks down the true financial and economic differences between a SaaS company and an AI company. Inspired by a tweet claiming that “SaaS metrics are broken” and that AI companies generate more absolute profit per customer, Ben puts the theory to the test using real financial modeling.
This episode walks through detailed revenue, gross margin, EBITDA, pricing power, TAM dynamics, and unit economics scenarios to determine whether AI companies actually outperform SaaS businesses.
What This Episode Covers
Why investors are questioning traditional SaaS metrics when evaluating AI companies
The importance of recurring revenue fundamentals, whether the company is SaaS or AI
A side-by-side comparison of a $1M SaaS company versus a $1M AI company
Gross margin profiles: 80 percent SaaS vs. 55 percent AI
How EBITDA changes when OpEx is held constant
The revenue scale required for an AI company to match SaaS gross profit
The revenue scale required for an AI company to match SaaS EBITDA
Why AI companies need a TAM that is 6x larger
How pricing power tied to labor displacement can shift AI unit economics
Modeling ARPA increases to see when AI gross profit matches SaaS
Why the underlying P&L structure does not change, but the inputs do
How founders should think about forecasting and financial strategy when building AI-native products
Why This Matters
Founders embedding AI into SaaS products
AI-native startups modeling their financial future
CFOs and FP&A leaders forecasting revenue, cash, and margins
Investors evaluating early-stage AI companies
Operators building long-term company valuation strategies
Ben emphasizes that the P&L, revenue streams, cost structure, and core KPI’s still apply. What changes are the inputs—gross margin profile, pricing power, TAM, ACV, and scalability assumptions.
Resources Mentioned
Full blog post with financial modeling examples: https://www.thesaascfo.com/the-real-economics-of-saas-versus-ai-companies
SaaS metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation
In episode #330, Ben explains one of the most common and costly SaaS finance mistakes: failing to allocate CAC between new and existing customers. This oversight leads to misleading KPI’s, inaccurate CAC payback, flawed LTV to CAC ratios, and unreliable unit economics. Ben walks through exactly how to allocate CAC the right way, how to segment sales and marketing expenses, and why this matters for accurate revenue efficiency metrics and due diligence.
Key Topics Covered
Why fully burdened sales and marketing expenses are required for accurate CAC
The danger of pushing all sales and marketing expenses into CAC without allocation
How to allocate CAC between new customer acquisition and expansion
How to segment sales teams (hunters vs. farmers) and avoid co-mingled headcount
Allocating marketing spend based on acquisition channels
Typical allocation benchmarks for sales (60-80% to new) and marketing (80-90% to new)
Why accurate CAC is essential for CAC payback, LTV to CAC, and cost of ARR
How the Cost of ARR provides a blended benchmark without requiring allocation
Using allocation methods for businesses with multiple product lines or motions
What You’ll Learn
How to correctly calculate CAC using fully burdened sales and marketing expenses
How to evaluate marketing economics and sales efficiency with proper allocation
Why unallocated CAC leads to distorted financial strategy and misleading KPI’s
How CAC allocation flows into CAC payback period, LTV to CAC, and ARR efficiency
How to build a repeatable, defensible go-to-market metrics framework that withstands due diligence
Who This Episode Is For
SaaS founders scaling beyond early customer acquisition
CFOs, FP&A leaders, and finance teams who own KPI modeling
Operators who need accurate CAC, CAC payback, and LTV calculations
Investors or advisors assessing revenue efficiency and go-to-market economics
Related Resources
SaaS Metrics Foundation course covering CAC, LTV, ARR, and unit economics: https://www.thesaasacademy.com/the-saas-metrics-foundation
Coaching resources on building an accurate, SaaS-specific chart of accounts: https://www.thesaasacademy.com/saas-cfo-coaching
In episode #329, Ben Murray, The SaaS CFO, breaks down the growing debate around SaaS economics versus AI economics. A recent post claimed that “SaaS metrics are broken” and that traditional KPIs no longer apply to AI companies.
Ben challenges this idea and walks through why recurring revenue metrics still matter, how revenue models differ across SaaS and AI, and what CFOs need to understand about gross margin, unit economics, and total addressable market.
Key Topics Covered
Why claims that SaaS metrics are “broken” are inaccurate
The difference between SaaS economics and AI economics
Why recurring revenue metrics still apply to AI companies
How subscription versus usage revenue impacts KPI calculation
Gross margin expectations for SaaS vs. AI companies
Whether AI companies truly generate more profit per customer
The role of absolute profit versus per-customer economics
How AI may expand TAM by targeting labor budgets, not just software budgets
How Agentic AI affects financial modeling and cost structures
Using ROSE (Return on Software Employees) to evaluate AI-driven ROI
What You’ll Learn
Why SaaS metrics still matter for both SaaS and AI companies
How CFOs should evaluate margins, ARR, and revenue quality in AI models
The difference between rate-based economics (ARPA, ACV) and volume-based economics (absolute profit)
How to think about financial strategy when transitioning from a pure SaaS model to an AI-embedded product model
How to assess realistic AI unit economics instead of relying on hype
Who This Episode Is For
SaaS CFOs and finance leaders evaluating AI investments
Founders embedding AI into their product and adjusting their financial models
Operators who want a grounded understanding of real AI economics
Investors assessing how AI shifts revenue models and margins
Related Resources
Ben’s upcoming deep-dive blog post on SaaS vs. AI economics: TheSaaSCFO.com
SaaS Metrics Foundation course for mastering KPI’s, ARR, MRR, and unit economics: https://www.thesaasacademy.com/the-saas-metrics-foundation
ROSE metric framework for analyzing AI-driven productivity and financial systems: https://www.thesaascfo.com/saas-rose-metric/
At what point should a founder stop running finance and accounting and hand the numbers to an expert?
In episode #328, Ben Murray walks through the inflection points when SaaS founders should consider hiring a bookkeeper and/or fractional CFO to protect data accuracy, improve forecasting, and strengthen company valuation. You’ll learn the warning signs that your financial systems and reporting are holding back growth—and how to build a finance function that scales with your business.
What You’ll Learn
When to hire help by ARR stage
Monthly close discipline: Why closing your books every month—accurately—is critical for investor trust.
Accrual vs. cash accounting: How switching methods reveals true business performance.
COGS clarity: Setting up a SaaS P&L that separates revenue streams, COGS, and OPEX for real gross-margin insight.
Retention readiness: Why your MRR schedule (revenue by customer by month) is worth its weight in gold.
Cash-flow forecasting: How to move beyond the bank-balance mentality to proactive cash planning.
Investor presentation: Ensuring your metrics, slide deck, and financial statements tie together cleanly.
Why It Matters
For Founders: Delegating finance isn’t failure—it’s a strategic step toward sustainable scaling and higher valuation.
For CFOs and Advisors: Knowing these trigger points helps you coach founders on financial readiness.
For Investors: A disciplined monthly close and clean P&L build confidence in revenue quality and forecasting accuracy.
Key Takeaways
Growth dictates urgency: the faster you scale, the earlier you need finance expertise.
A bookkeeper should close the books by mid-month to avoid costly cleanup later.
Move to accrual accounting to show economic performance and support fundraising.
Create an accurate MRR schedule to prove retention and ARR health to investors.
Build a basic forecast to manage cash runway and hiring decisions with confidence.
Resources Mentioned
SaaS Metrics Foundation Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
Finance 101 for Founders: https://www.thesaasacademy.com/finance-101-for-saas-founders
Quote from Ben
“Just like I couldn’t go in and code your product, most founders can’t scale as CFO. At some point, finance needs a specialist so the business can keep growing on solid data.”
Your gross margin might not be telling the truth.
In episode #327, Ben Murray exposes the seven “dirty secrets” that distort SaaS gross margins — from incorrect COGS coding to missing allocations for shared resources and misclassified expenses. Whether you’re a CFO, finance lead, or operator, you’ll learn how to clean up your P&L and get accurate unit economics that reflect your true performance and valuation.
What You’ll Learn
The 7 big offenders that make SaaS gross margins misleading.
How to correctly code payment processing fees (Stripe, ACH, wire) under DevOps in COGS.
The difference between internal-use software and third-party apps embedded in your product.
How to classify customer success — adoption-focused vs. account management.
Why demo and test environments must be allocated properly between departments.
How to ensure fully burdened expenses (wages, taxes, benefits, bonuses) are coded correctly.
The impact of co-mingled headcount on margins by revenue stream.
Why department leaders belong in the departments they manage.
Why It Matters
For Founders: Clean accounting drives higher (or preserved) company valuation and investor confidence.
For Finance Teams: Accurate COGS and gross profit ensure your SaaS metrics are reliable.
For Operators: Clear expense allocation helps identify efficiency opportunities in support, services, and DevOps.
For Investors: Properly structured financial systems and accounting practices make due diligence faster and cleaner.
Key Takeaways
Misclassified expenses can make your gross margin appear stronger or weaker than it really is.
Always differentiate between OpEx and COGS — the foundation of credible financial modeling.
Track margins by revenue stream (subscription, usage, services) for true business insight.
Ensure your P&L reflects fully burdened costs per department — including contractors.
Clean financial data = higher trust from investors and buyers.
Resources Mentioned
SaaS Metrics Foundation Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
Quote from Ben
“Your P&L doesn’t lie — but bad coding does. If your COGS and OpEx aren’t clean, your gross margin isn’t either.”
Thinking about raising capital or selling your SaaS company? Your legal readiness can make or break the deal.
In episode #326, Ben Murray breaks down what investors and acquirers look for during due diligence — and why preparing your cap table, contracts, IP, and financial systems at least six months in advance is essential to protect your company's valuation and ensure a smooth process.
What You’ll Learn
Cap Table Management: Why tracking every issued share, option, and agreement matters — and how to avoid “email equity surprises.”
IP Protection: The critical role of signed IP assignment agreements for employees, contractors, and vendors.
Customer & Vendor Contracts: Why detailed MSAs, renewal clauses, and change-of-control provisions are required for investor confidence.
Accounting Readiness: How clean, timely accounting — especially a complete MRR schedule (revenue by customer by month) — helps prove the health of your recurring revenue and ARR growth.
Sales Tax Compliance: Why sales tax exposure can derail your exit process.
Due Diligence Prep: How to build your data room, organize key documents, and present your SaaS business model with clarity.
Why It Matters
For Founders: Legal gaps can reduce your valuation multiple and slow down the exit timeline.
For CFOs: Solid financial systems and clean documentation protect your cash flow and reputation with investors.
For Investors: A well-prepared company signals operational maturity and reduces transaction risk.
For Operators: Legal readiness supports strategic growth and prevents “deal fatigue” during M&A or fundraising.
Resources Mentioned
Ben’s Blog Post: “SaaS Legal Readiness Checklist” : https://www.thesaascfo.com/why-legal-readiness-can-make-or-break-your-saas-exit/
SaaS Metrics Foundation Course – Learn how to align your financial reporting and recurring revenue metrics for due diligence success.
Upcoming Webinar: “Legal Readiness for SaaS Founders — How to Prepare for an Exit or Raise” (details via newsletter)
💬 Quote from Ben
“You can’t fix legal readiness in a week. Start six months early, or you’ll be scrambling during due diligence when investors start asking for data you don’t have.”
“SaaS metrics are dead.” You’ve probably seen that post on LinkedIn or X lately. In episode #325, Ben Murray cuts through the noise to explain why SaaS metrics aren’t broken — they’re just evolving to match modern recurring revenue business models.
Whether you’re running a SaaS, AI, software, or managed services company, the same financial principles apply. The key is understanding your revenue types — subscription, usage, consumption, or transaction — and applying the right metrics framework for each.
What You’ll Learn
Why SaaS metrics still work — and why the confusion exists.
The difference between SaaS as a delivery model and recurring revenue as a financial model.
Why the most important question isn’t “Are you SaaS?” but “What are your revenue types?”
How financial systems and P&L design should reflect these revenue categories for accurate unit economics and valuation.
Why It Matters
For Operators: The framework for recurring revenue metrics applies whether you sell software, data, or AI services.
For Finance Teams: You can’t manage what you don’t measure — ensure your financial modeling captures all recurring components.
For Investors: Strong recurring revenue visibility (ARR, NRR, margins) still drives valuation multiples — regardless of your label.
For Founders: Stop worrying about the buzz — focus on measuring what matters for your business model.
Key Takeaways
SaaS metrics = recurring revenue metrics.
Focus on revenue types, not just labels like “SaaS” or “AI.”
A clear chart of accounts and a well-designed financial system enable accurate SaaS metrics.
The fundamentals of finance, accounting, and valuation haven’t changed — only the packaging has.
Resources Mentioned
🧾 The SaaS Metrics Foundation Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
Quote from Ben
“SaaS metrics aren’t broken — they’ve just outgrown the acronym. These are recurring revenue metrics that apply to most modern business models.”
Your implementation and professional services teams could be quietly eroding your gross profit margin — and most SaaS leaders don’t even realize it.
In episode #324, Ben Murray explains how unclear COGS structure, mispriced services, and untracked internal resources can distort your unit economics and lower your overall SaaS valuation.
If your service margins are negative or your gross profit doesn’t match expectations, this episode shows you exactly where to look — and how to fix it.
What You’ll Learn
Why implementation teams often kill gross profit without you noticing.
How to calculate services margins by setting up clean revenue streams and COGS cost centers.
The right services gross margin target.
Why doing “free” onboarding work can destroy your unit economics.
How underpricing services or blending resources (support, CS, services) skews your financial reporting.
The balance between protecting ARR and monetizing implementation revenue.
How to fix your SaaS P&L for visibility into margins by revenue stream.
Why It Matters
For CFOs & Founders: Misclassified or underpriced services directly lower gross profit, cash flow, and company valuation.
For Finance Teams: Clean COGS and OPEX separation creates accurate financial modeling, ARR margins, and retention-linked profitability.
For Investors: Understanding margins by revenue stream signals financial discipline and scalability.
For Operators: Properly scoped and priced services keep customer onboarding efficient and profitable.
Key Takeaways
Every SaaS company should know gross margin by revenue stream (subscription, usage, services).
Services losing 20–30% gross margin dilute your financial performance and cash flow forecasting.
Accurate classification drives better SaaS metrics, including CAC payback, Cost of ARR, and LTV:CAC.
A well-structured financial system is your best defense against margin erosion.
Resources Mentioned
Episode 323: Should Professional Services Be COGS or OPEX?
SaaS Metrics Foundation Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
Quote from Ben
“If you don’t know your margins by revenue stream, you can’t manage them — and services might be the silent killer of your gross profit.”
Where do professional services belong on a SaaS P&L—COGS or OPEX? In episode #323, Ben clarifies how to code implementation, onboarding, custom integrations, and the tricky custom development work that sometimes blurs the line with R&D. You’ll learn how correct classification protects gross profit, keeps investor metrics credible, and supports a higher company valuation.
- What You’ll Learn
What counts as Professional Services
When custom dev is OPEX (R&D) vs. COGS
How to handle integrations
Why coding accuracy matters
Practical P&L structure
- Why It Matters (Finance & Investor Lens)
Gross Profit Integrity: Correct COGS ensures reliable margins by revenue stream (subscription, services, usage) that investors expect.
Credible SaaS metrics: Clean separation supports accurate CAC payback (GM-adjusted), Cost of ARR, and LTV:CAC.
Valuation: Transparent accounting and financial systems reduce diligence friction and improve confidence in revenue quality.
Operator Clarity: Treat Professional Services as a self-sustaining business unit with clear targets for utilization and margin.
- Quick Checklist
Distinct GLs for subscription, usage, services revenue
Fully burdened Services COGS (wages, taxes, benefits, travel, tools)
Separate custom dev tracking (R&D vs. billable services)
Clear DevOps/hosting in COGS for delivery costs
CS in COGS only if non-selling (no quota/commission)
- Resources Mentioned
Guide: How to Structure a SaaS P&L (COGS vs. OPEX, margins by stream): https://www.thesaascfo.com/how-to-structure-your-saas-pl/
Course: SaaS Metrics Foundation: https://www.thesaasacademy.com/the-saas-metrics-foundation
- Quote from Ben
“Code services where the work and dollars actually live. If you blur R&D and Services, you’ll either hurt gross profit—or your OpEx profile. Either way, investors will notice.”
Raising a Series A? Your story matters—but your SaaS metrics may close the deal. In episode #322, Ben outlines the investor-ready metrics founders must prepare. You’ll learn what each metric signals to investors, how it ties to valuation, and where founders slip on accounting and financial systems.
Why It Matters (Investor Lens)
Investor metrics translate your story and traction into company valuation (multiples tied to growth + retention quality).
Clean financial modeling depends on accurate accounting (COGS vs OPEX), solid financial systems, and reliable unit economics.
Segmented metrics (by ACV/product/segment) de-risk assumptions and speed due diligence.
Resources Mentioned
Blog: Essential Series A Metrics (+ deep dives for each metric): https://www.thesaascfo.com/essential-saas-metrics-for-a-series-a-fundraise/
Course: SaaS Metrics Foundation: https://www.thesaasacademy.com/the-saas-metrics-foundation
Quote from Ben
“In Series A, the story still matters—but the metrics support the story that investors underwrite.”
Is the traditional LTV formula giving you misleading results when you have multi-year SaaS contracts?
In episode #321, Ben Murray unpacks a listener’s question about how Lifetime Value (LTV) should be calculated when customers sign multi-year agreements. Using real-world finance and accounting logic, he breaks down how multi-year contracts can inflate your aggregate revenue retention (GRR) and distort LTV:CAC ratios — and how to fix it.
You’ll learn when to adjust your LTV calculation to use cohort retention, renewal rate, or aggregate GRR, depending on your business model and contract structure. The Retention Triangle!
What You’ll Learn:
The correct LTV formula for SaaS
Why multi-year contracts can artificially boost retention and lifetime value.
When to use aggregate GRR, renewal rate, or cohort retention in your LTV calculation.
How to interpret the “triangle of retention”: aggregate, renewal, and cohort retention.
Why LTV is a point-in-time metric, not a cumulative one.
How to explain your retention assumptions clearly during due diligence or a fundraising process.
Why It Matters:
For SaaS CFOs & Finance Teams: Using the wrong retention assumption can lead to overestimated LTV:CAC ratios, poor financial modeling, and investor skepticism.
For Founders & Operators: Understanding how contract length impacts SaaS economics helps you make better pricing and renewal decisions.
For Investors & Buyers: Accurate LTV and retention analysis provide confidence in the predictability of future revenue.
For Accounting Leaders: Aligning your LTV calculation with your revenue recognition and retention tracking ensures accurate SaaS reporting.
Resources Mentioned:
No Fluff Series – The SaaS Academy: https://www.thesaasacademy.com/pl/2148384654
Quote from Ben:
“Multi-year contracts can make your LTV look great — until investors realize it’s inflated by locked-in customers. That’s why understanding retention dynamics is critical.”
At what stage should SaaS companies start segmenting their metrics? In episode #320, Ben Murray breaks down when and how to segment your SaaS metrics — from revenue segmentation to go-to-market efficiency metrics — so your data actually reflects how your business operates.
Ben explains how segmentation becomes essential as you scale past $10M ARR or diversify product lines (for example, enterprise vs. SMB or PLG vs. sales-led models). He also shares how finance and ops teams can collaborate to align their chart of accounts, cost centers, and customer metadata to get meaningful insights that improve valuation and decision-making.
What You’ll Learn
When to start segmenting SaaS metrics (typically around $10M ARR, but earlier for multi-product businesses).
The difference between revenue segmentation and financial metric segmentation.
How to align your chart of accounts and cost centers for accurate CAC, CAC payback, and LTV:CAC by segment.
Why aggregate CAC or payback metrics are misleading without segmentation.
The importance of metadata consistency between systems (HubSpot, CRM, accounting, billing).
How clean segmentation improves your company valuation and investor confidence during fundraising or exit.
Why It Matters
For CFOs & Finance Teams: Segmentation reveals where efficiency and retention differ by product line or customer cohort.
For Founders & Operators: Understanding metrics by segment helps you scale profitably and target the right growth motion.
For Investors: Segmented financial reporting and SaaS metrics reduce uncertainty and strengthen valuation models.
For Accounting Leaders: Accurate cost allocation enables better financial modeling and Board reporting.
Resources Mentioned
The SaaS Metrics Foundation Course: https://www.thesaasacademy.com/#section-1744932157830
Quote from Ben
“You can’t say your CAC payback is 12 months when it combines enterprise and SMB customers — that data is worthless.”




