SaaS Metrics School

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.”

Does Net Revenue Retention (NRR) really move your company’s valuation multiple? Absolutely — and the difference can be worth tens of millions of dollars. In episode #319, Ben Murray breaks down new data from Meritech Capital and Benchmarkit.ai to show exactly how changes in your NRR directly impact your revenue multiple and SaaS valuation. You’ll also learn why ACV segmentation matters when benchmarking NRR and Gross Revenue Retention (GRR), and how top-performing SaaS companies are using retention metrics to drive investor confidence and higher valuations. What You’ll Learn The link between NRR and valuation multiples — a 7-point jump in NRR can double your multiple. How a $5M ARR company can see a $25M valuation swing from retention improvements. The latest SaaS benchmarks from Ray Rike (Benchmarkit.ai) for NRR and GRR. Why you must benchmark NRR by ACV, not company size or industry averages Why investors prioritize retention when evaluating durability, efficiency, and predictability of revenue.   Why It Matters For SaaS Founders: NRR improvements can directly increase your exit or fundraising valuation. For CFOs & Finance Leaders: Retention trends reveal the sustainability of your revenue model and influence your ARR growth forecast. For Investors: High NRR signals strong customer economics, pricing power, and efficient growth. For Operators: Knowing your NRR by ACV cohort allows smarter resource allocation and customer success planning. Resources Mentioned The SaaS CFO Academy: https://www.thesaasacademy.com/#section-1744932157830 Quote from Ben “A 5X difference in valuation multiple can come down to just a few points in your net revenue retention. That’s the power of strong SaaS metrics.”

Even small errors in your MRR schedule can have a massive impact on your retention metrics, and in due diligence, that can destroy investor confidence. In episode #318, Ben Murray explains why gaps in your monthly recurring revenue (MRR) schedule create inaccurate gross revenue retention (GRR) and net revenue retention (NRR) results — and how poor invoicing and renewal practices are often the root cause. You’ll learn how to identify, fix, and prevent these gaps so your SaaS financial reporting and valuation metrics remain accurate and investor-ready. What You’ll Learn ✅ What causes gaps in your MRR schedule (and how to spot them). ✅ How MRR gaps distort your retention, expansion, and churn calculations. ✅ Why these data issues raise red flags in due diligence. ✅ How to align renewal dates, contracts, and invoicing to eliminate data breaks. ✅ What a clean, accurate MRR waterfall should look like for SaaS and AI companies. ✅ Why you need at least three years of clean retention data before a fundraise or exit. Why It Matters For CFOs & Finance Teams: Gaps cause misleading GRR/NRR trends that erode trust in your data. For Founders & CEOs: Bad MRR data can hurt company valuation and slow down fundraising or acquisition. For Investors: Clean MRR schedules provide transparency into predictable revenue and retention strength. For Accountants: Accurate MRR waterfalls enable stronger financial modeling and forecasting. Resources Mentioned SaaS Metrics Foundation Course: https://www.thesaasacademy.com/the-saas-metrics-foundation Quote from Ben “If there are gaps in your MRR schedule, your retention story falls apart — and investors will notice.”

To build a world-class FP&A process in a SaaS or AI business, you need more than great dashboards—you need clean, reliable data from the right sources. In episode #317, Ben Murray shares the four foundational SaaS finance data sources that power accurate forecasts, meaningful metrics, and board-ready financial models. Drawing on his experience in FP&A across airlines and software, Ben explains how to integrate data from accounting, CRM, subscription management, and HR systems to create a trustworthy SaaS P&L and streamline financial reporting. This is the go-to framework for any finance leader, CFO, or operator seeking to enhance their financial systems and forecasting accuracy. What You’ll Learn The four essential SaaS finance data sources for great FP&A. How each data source powers financial forecasting, SaaS metrics, and Board reporting. Why poor accounting structure creates “data debt” that hurts accuracy and slows decision-making. How to link bookings data to go-to-market efficiency metrics like CAC, LTV/CAC, and CAC payback. Why accurate HR data improves unit economics and organizational efficiency analysis. Why It Matters For FP&A Leaders: Build forecasts grounded in data integrity. For SaaS Founders: Understand Which Data Sources Drive Investor-Ready Reporting. For Investors: Confidence in a company’s data architecture improves valuation and diligence outcomes. For CFOs: A solid finance foundation enables better strategic planning, cash flow forecasting, and profitability tracking. 📎 Resources Mentioned The SaaS Academy: https://www.thesaasacademy.com/#section-1744932157830 Quote from Ben “Without clean financial, bookings, revenue, and HR data, your FP&A process can’t deliver the insights your Board expects.”

Is renewal rate just another way of saying retention? Not exactly. In episode #316, Ben Murray breaks down the difference between renewal rate and the classic retention metrics—gross revenue retention (GRR), net revenue retention (NRR), and customer/logo retention. Ben explains why the renewal rate is the leading indicator of retention, especially when running annual or multi-year contracts, and why investors, private equity buyers, and your board will want to see this number alongside your standard SaaS metrics. If you’re a SaaS or AI operator looking to better understand your unit economics and improve your company’s valuation, this episode will help you put renewal rate into context as part of your financial metrics toolkit. 🧠 What You’ll Learn ✅ The definition of renewal rate and how it differs from retention. ✅ How renewal rate acts as the leading edge of retention performance. ✅ Why renewal rate matters most for SaaS and AI companies with annual or multi-year contracts. ✅ How to track renewal rate by customer count and dollar value. ✅ Why renewal rate is increasingly scrutinized in due diligence and PE-backed exits. ✅ How renewal rate complements ARR growth, gross profit, and retention metrics. 📊 Why It Matters For Finance Teams: Renewal rate shows early signs of churn risk before it hits your GRR/NRR numbers. For Leaders: Renewal performance provides insight into customer satisfaction and product adoption. For Investors & Buyers: Renewal rate is a leading signal of predictable revenue and future valuation. For Boards: Adds confidence in forecasting ARR, revenue growth, and unit economics. 📎 Resources Mentioned 🎓 SaaS Metrics Academy — Courses on SaaS P&L, retention, and financial strategy: https://www.thesaasacademy.com/#section-1744932157830 🧾 Quote from Ben “Renewal rate is the tip of the iceberg. If customers keep renewing at a high rate, your retention story will follow."  

Every Board, investor, and potential acquirer is asking the same question: How are AI initiatives driving revenue? In episode #315, Ben Murray shares insights from his research into public tech companies and how they’re defining and disclosing AI ARR (Annual Recurring Revenue). Using Verint as a case study, Ben explains how companies are leveraging AI-driven ARR, tying it to measurable outcomes, and communicating adoption in a way that resonates with both Wall Street and buyers. You’ll also hear how these disclosures may have supported Verint’s recent multibillion-dollar acquisition by Thoma Bravo. If you’re a SaaS or AI operator, this episode will help you define AI ARR, communicate adoption signals, and position your business model for higher valuation. What You’ll Learn What AI ARR is and how to calculate it. Why public companies like Verint are breaking out AI ARR from total ARR. The mechanics: how finance teams identify AI-influenced products and SKUs. Quantitative + qualitative adoption signals (e.g., number of users leveraging AI features). Why AI ARR disclosures matter for investor metrics and exit valuations. How Thoma Bravo’s acquisition of Verint shows the value of communicating AI initiatives. Why It Matters For SaaS & AI Leaders: Properly defining AI ARR helps show investors where new growth is coming from. For Finance Teams: Accurate reporting requires collaboration across accounting, product, and FP&A. For Investors: AI ARR signals measurable adoption and future revenue growth. For Valuation: Tying AI initiatives to financial outcomes increases credibility in fundraising and exit scenarios. Resources Mentioned Blog Post: How to Define AI ARR: https://www.thesaascfo.com/ai-arr-vs-saas-arr-how-to-define-and-calculate/ The SaaS Metrics Academy: https://www.thesaasacademy.com/ Quote from Ben “Don’t just say you’re building AI into your product — show investors how much ARR it’s driving and what outcomes it’s creating.”