SaaS Metrics School

By Ben MurrayBusiness Entrepreneurship Technology Management

SaaS Metrics School episodes

March 213 Ways AI Could Kill Traditional SaaS
Is the “SaaSpocalypse” real—or just another wave of disruption you need to navigate?
If you’re building or scaling a SaaS company, the rapid rise of AI agents, lower barriers to entry, and shifting pricing models could directly impact your growth, revenue predictability, and competitive edge. Understanding these changes isn’t optional—it’s critical to staying relevant and defensible in an AI-driven market. Here's what you'll take away in episode #360 with Ben Murray.
Understand how AI agents are reshaping the traditional SaaS interface and customer interaction
Learn why barriers to entry are dropping fast—and what that means for competition
Discover how evolving pricing models could impact your revenue and forecasting strategy
Tune in to uncover whether SaaS is truly at risk—and what you should do right now to stay ahead.
Resources:
AI defensibility framework: https://www.thesaascfo.com/the-saaspocalypse-ai-agents-vibe-coding-and-the-changing-economics-of-saas/
4 min
March 18CFOs We are Implementing AI Backwards
Are finance teams implementing AI the wrong way?
In episode #359, Ben Murray argues that many CFOs and finance leaders are approaching AI backward—focusing too much on prompts and quick wins rather than building the foundational data infrastructure required for meaningful, repeatable insights.
Drawing from recent AI webinars and his experience building softwaremetrics.ai, Ben explains why SaaS metrics, retention, and cohort analysis should not rely on AI. Instead, these should be computed through structured, deterministic systems first—then enhanced with AI for deeper analysis and pattern recognition.
Resources Mentioned
My new metrics engine: https://softwaremetrics.ai/
My SaaSpocalypse post: https://www.thesaascfo.com/the-saaspocalypse-ai-agents-vibe-coding-and-the-changing-economics-of-saas/
What You’ll Learn
Why prompt-driven AI workflows are not scalable in finance
The difference between deterministic systems and AI-driven analysis
Why you don’t need AI to calculate core SaaS metrics like retention or CAC payback
The importance of structured data and clean data pipelines
How AI should be layered on top of computed financial data—not raw inputs
Why context windows and token usage matter when working with large datasets
How AI can uncover insights (like expansion opportunities) that FP&A teams may miss
Why It Matters
Prompt-based workflows create inconsistency and lack of auditability
Without structured data, AI outputs are unreliable and not repeatable
Finance teams risk “prompt fatigue” without building scalable systems
Deterministic calculations ensure accuracy for critical SaaS metrics and reporting
AI delivers the most value when used for analysis—not basic computation
Efficient data handling reduces token costs and improves performance
6 min
March 12What Started the SaaSpocalypse?
What sparked the recent “SaaSpocalypse” conversation across social media, news outlets, and investor circles?
In episode #358 of SaaS Metrics School, Ben Murray explains how the debate around AI potentially disrupting SaaS began. Ben breaks down what actually started the conversation, the major concerns investors and operators are discussing, and why SaaS founders and CFOs should pay attention to the shift.
Resources Mentioned
Ben’s blog post: The SaaSpocalypse — Bull Case, Bear Case, and How to Assess SaaS Defensibility: https://www.thesaascfo.com/the-saaspocalypse-ai-agents-vibe-coding-and-the-changing-economics-of-saas/
What You’ll Learn
What triggered the “SaaSpocalypse” narrative in early 2026
Why AI coding tools are accelerating the build vs. buy decision for software
How agentic workflows could pressure traditional SaaS products
Why seat-based pricing models may face scrutiny in an AI-driven world
How investors may rethink the durability of SaaS revenue and growth
Why It Matters
AI agents capable of executing workflows could reshape how software is delivered
SaaS pricing models tied to seats may become less durable if AI reduces headcount needs
The build vs. buy equation is shifting as AI coding tools make software easier to create
Investors may begin reassessing SaaS valuations based on AI disruption risk
SaaS operators must stay informed and proactive as AI reshapes the software landscape
4 min
March 03Here's Why AI is Not Killing SaaS
Is AI killing SaaS? Ben argues the opposite.
In episode #357 of SaaS Metrics School, Ben Murray explains why AI isn’t replacing SaaS companies — it’s amplifying subject matter expertise. Drawing on his experience building SoftwareMetrics.ai with AI coding tools, he walks through how he would not be able to create a useful expert without domain knowledge. It doens't just apply to Ben.
Resources Mentioned
Ben's new app at: https://softwaremetrics.ai/
What You’ll Learn
Why AI is not replacing SaaS business models
How subject matter expertise becomes more valuable in an AI-native world
The importance of structured MRR schedules and clean invoice data
How metadata (ACV, geography, vertical, company size) unlocks deeper retention insights
The difference between dashboards and AI-powered revenue intelligence
How AI can identify dormant expansion opportunities within your existing customer base
Why It Matters
AI tools amplify expertise — they don’t replace it
Clean financial and customer data becomes a strategic asset
Revenue intelligence goes far beyond basic retention reporting
SaaS operators who understand their metrics can leverage AI more effectively
Industry-specific knowledge remains a competitive moat in a world of AI tooling
6 min
February 25Top FP&A Solutions Used by Software Companies
In episode #356, Ben shares the results from the FP&A category of his 7th Annual SaaS Tech Stack Survey, highlighting the top financial planning and analysis solutions used in software companies today.
With 37 FP&A solutions named in the survey, this remains one of the most competitive and fast-moving segments in the back-office tech stack. While spreadsheets still dominate usage—by a wide margin—dedicated FP&A platforms are gaining traction, especially as companies scale past $10M+ ARR and investor reporting requirements increase.
Ben also compares this year’s results to prior years and explains how FP&A tool adoption shifts by ARR size.
Resources Mentioned
7th Annual SaaS Tech Stack Survey: https://www.thesaascfo.com/surveys/finance-accounting-tech-stack-survey/
What You’ll Learn
The most widely used FP&A solutions in SaaS and AI companies
Why spreadsheets still dominate financial modeling workflows
Which platforms are gaining momentum (Drivetrain, Mosaic, Aleph, Pigment, Planful, and others)
How FP&A adoption changes as companies scale beyond $10M ARR
Why enterprise-grade tools like Workday appear in larger organizations
How funding and competition are reshaping the FP&A software landscape
Why It Matters
FP&A systems power your forecasting, budgeting, and board reporting
Spreadsheet-based processes eventually break as complexity increases
As ARR grows, investors expect more sophisticated financial modeling and analytics
Selecting the right FP&A tool impacts forecasting accuracy, KPI visibility, and strategic planning
Understanding market adoption trends helps founders and CFOs benchmark their financial systems
5 min
February 20Top Invoicing Solutions Used by Software Companies
In episode #355, Ben breaks down the top invoicing solutions used by SaaS and AI companies based on his 7th Annual Tech Stack Survey.
With 57 different invoicing solutions named in the survey, this category shows far more fragmentation than core accounting. The top five solutions account for 55% of reported usage, but there’s still a long tail of specialized billing and revenue management platforms.
Ben walks through the most widely used tools and explains how invoicing increasingly overlaps with revenue management, subscription billing, and payment processing.
Resources Mentioned
7th Annual SaaS Tech Stack Survey: https://www.thesaascfo.com/surveys/finance-accounting-tech-stack-survey/
Metronome, sponsor of the invoicing category: https://metronome.com/
What You’ll Learn
The top invoicing and billing solutions used in software companies
Why QuickBooks and Stripe remain dominant in early and growth-stage SaaS
Which newer platforms are gaining traction
How fragmented the invoicing and billing landscape has become
Why It Matters
Invoicing is a critical link between bookings, cash flow, revenue recognition, and ARR reporting
Poor billing infrastructure can break your MRR schedules and retention calculations
As pricing models evolve (subscription, usage, hybrid), your invoicing system must handle complexity
Revenue management tools increasingly sit between CRM, payments, and your general ledger
Clean invoicing data is essential for accurate financial modeling, KPI tracking, and due diligence
3 min
February 19Top Accounting Solutions Used by Software Companies
In episode #354, Ben shares the results from his 7th Annual SaaS Tech Stack Survey and reveals the top accounting solutions used by software, SaaS, and AI companies today.
With participation across 22 software categories, this year’s survey highlights both the consistent market leaders and the rise of newer, AI-first ERP platforms. While legacy players continue to dominate, new entrants are gaining meaningful traction.
Ben breaks down the “Power Six” accounting platforms and what their market concentration tells us about the current state of financial systems in tech companies.
Resources Mentioned
7th Annual SaaS Tech Stack Survey: https://www.thesaascfo.com/surveys/finance-accounting-tech-stack-survey/
Light, sponsor of the core accounting category: https://light.inc/
What You’ll Learn
The top accounting and ERP systems used by SaaS and AI companies
How the “Power Six” now dominate the accounting stack landscape
Which newer AI-first ERP platforms are gaining traction
How concentrated is the accounting software market among SaaS companies
Why accounting system selection matters as companies scale ARR
Why It Matters
Your accounting system is the foundation of your financial reporting, SaaS metrics, and KPI tracking
Poor financial systems limit your ability to calculate ARR, revenue retention, and other recurring revenue metrics
As revenue grows, moving from SMB accounting tools to more robust ERP and financial systems becomes critical
Investors and auditors expect scalable accounting infrastructure as companies mature
Understanding market trends helps founders and CFOs evaluate whether their current financial systems can support growth
3 min
February 11Moving Beyond Spreadsheets to Calculate Your SaaS Metrics
Calculating SaaS metrics sounds straightforward—until you actually try to do it. In episode #353, Ben Murray breaks down why SaaS metrics are so difficult to calculate at scale, why spreadsheets eventually break, and what it really takes to produce CFO-grade metrics that stand up in the Boardroom and in due diligence.
Drawing on insights from the 7th Annual SaaS Tech Stack Survey, Ben explains why 58% of companies still rely on spreadsheets and highlights the growing mix of tools aimed at solving the SaaS metrics challenge.
At the core of the issue? SaaS metrics require clean, structured data from four distinct systems—and most companies don’t have that foundation in place.
Resources Mentioned
7th Annual SaaS Tech Stack Survey: https://mailchi.mp/thesaascfo.com/its-here-the-2026-saas-finance-ops-tech-stack-report
Waitlist for Ben's SaaS Metrics app: https://docs.google.com/forms/d/e/1FAIpQLSeMMKm1N6g0PifGBNhFacivqA-lqePH9id93dCGKxNeBOWbFw/viewform?usp=dialog
SaaS Metrics Foundation Course with App: https://www.thesaasacademy.com/the-saas-metrics-foundation
What You’ll Learn
The four key SaaS finance data sources required to calculate accurate metrics
Why SaaS metrics are difficult to automate (and why most companies struggle)
Why spreadsheets are the default starting point—and why they don’t scale
The most common tools companies use today to calculate SaaS metrics
Why understanding the manual process is critical before implementing software
What “CFO-grade SaaS metrics” actually means
Why It Matters
Without structured financial data, your metrics won’t stand up to board or investor scrutiny
Disconnected systems create inconsistencies that undermine trust in your numbers
Spreadsheet-based processes break as transaction volume and complexity grow
Accurate SaaS metrics require integrating financial, bookings, HR, and customer revenue data
If your data foundation isn’t solid, automation tools won’t fix the problem
5 min
February 06Stripe, MRR, and the Retention Metrics Nobody Warned You About
In episode #352 of SaaS Metrics School, Ben explains why SaaS and AI founders need to get control of their Stripe data early — before transaction volume and product complexity make it unmanageable. Drawing on years of fractional CFO experience, he explains how messy Stripe data can undermine revenue accuracy, MRR schedules, retention metrics, and due diligence readiness if the data flow isn’t clearly mapped from day one.
Resources Mentioned
Ben’s 7th Annual Tech Stack Report: https://www.thesaascfo.com/surveys/finance-accounting-tech-stack-survey/
What You’ll Learn
Why Stripe data becomes difficult to manage as transaction volume grows
How Stripe feeds into revenue reporting, MRR schedules, and retention metrics
What a “revenue by customer by month” (customer cube) actually requires
How multiple product IDs and revenue types complicate Stripe reporting
Why mapping payment, fee, and revenue flows early saves major cleanup later
The role Stripe data plays in due diligence and investor scrutiny
Why It Matters
Stripe is often the source of truth for self-serve and PLG revenue
Poorly mapped Stripe data makes MRR waterfalls and retention metrics unreliable
Due diligence requires defensible revenue-by-customer schedules
Fixing Stripe data problems later is far more expensive and time-consuming
Clean Stripe flows enable accurate forecasting and financial clarity as you scale
4 min
February 03The Difference Between Bookings, Invoices, and Revenue
In episode #351 of SaaS Metrics School, Ben breaks down one of the most misunderstood areas of SaaS finance: the difference between bookings, invoices, and revenue. Using the SaaS revenue cycle as a framework, he explains how a signed contract flows through invoicing, revenue recognition, and ultimately cash collection — and why confusing these concepts leads to bad metrics, poor forecasting, and cash flow surprises.
Resources Mentioned
Blog post: https://www.thesaascfo.com/bookings-vs-invoicing-vs-revenue/
SaaS Metrics Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
What You’ll Learn
What a booking actually represents in a SaaS or PLG business
How bookings differ between sales-led and self-service models
Why invoices are not the same as revenue under accrual accounting
How deferred revenue works and why revenue must be recognized over time
The full SaaS revenue cycle: bookings → invoices → revenue → cash
Why understanding this flow is critical for financial modeling, forecasting, and cash flow planning
Why It Matters
Prevents overstating revenue or ARR in Board and investor reporting
Improves accuracy in cash flow forecasting and runway planning
Ensures go-to-market metrics like CAC payback and cost of ARR are built on the right data
Reduces confusion between CRM data and accounting system source-of-truth
Creates better alignment between finance, sales, and leadership teams
4 min

About SaaS Metrics School

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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 and AI metrics, finance, and accounting tactics that drive financial transparency and improved decision-making.