Justifying investment in customer success is far harder than justifying spend in sales and marketing. In episode #350, Ben walks through a practical framework for evaluating the ROI of customer success and retention programs by tying customer success investment directly to ARR, MRR, and revenue retention performance. Instead of relying on vague qualitative benefits, this episode outlines how finance and SaaS leaders can quantify retention improvements and translate them into real financial impact.

Resources Mentioned

Blog post on quantifying customer success and retention ROI: https://www.thesaascfo.com/quantifying-investments-in-customer-success-and-retention/

SaaS Metrics Course: https://www.thesaasacademy.com/the-saas-metrics-foundation

What You’ll Learn

• Where customer success should be classified on the SaaS P&L (COGS vs. Sales)
• Why customer success ROI is harder to quantify than CAC or go-to-market efficiency
• How to use MRR and ARR waterfalls as the foundation for retention analysis
• The difference between gross revenue retention and net revenue retention in ROI modeling
• How expansion, contraction, and churn act as independent levers in retention
• A scenario-based approach to estimating ARR impact from retention improvements

Why It Matters

• Helps justify customer success spend with real revenue and ARR impact
• Improves financial modeling and long-term financial strategy decisions
• Connects retention performance to unit economics and scalability
• Avoids over-investing in customer success without measurable outcomes
• Provides a clearer framework for board and investor discussions

Many SaaS teams try to use their CRM to report ARR and MRR, but this creates serious risks—especially in forecasting, retention analysis, and due diligence. In episode #349, Ben explains why your CRM is rarely the correct source of truth for recurring revenue and where ARR should actually come from to ensure financial accuracy and credibility with investors and acquirers.

Resources Mentioned

• How to Disclose ARR: https://www.thesaascfo.com/cfos-guide-to-disclosing-headline-arr-numbers/
• Ben's SaaS Metrics Course: https://www.thesaasacademy.com/the-saas-metrics-foundation

What You’ll Learn

• Why CRM-based ARR reporting is often inaccurate and easy to break
• The difference between bookings data and revenue-based ARR
• What qualifies as a true source of truth for ARR and MRR
• How invoicing, revenue recognition, and the general ledger fit together
• Why CRM-reported ARR frequently fails under due diligence scrutiny
• When (and only when) a CRM can be trusted for recurring revenue metrics

Why It Matters

• Prevents misleading ARR, MRR, and revenue metrics
• Ensures your financial systems can support investor and buyer diligence
• Reduces risk when calculating retention, CAC payback, and unit economics
• Improves confidence in Board reporting and long-term financial strategy

In episode #348 of SaaS Metrics School, Ben Murray responds to a thoughtful LinkedIn comment that challenged a common assumption: that a well-structured SaaS P&L tells the whole story. While a properly built chart of accounts and SaaS P&L are foundational, Ben explains where hidden risks can still exist beneath clean financial statements.

Using real-world examples from SaaS founders and finance teams, this episode explores how revenue commingling, misclassified expenses, role overlap, and customer concentration can quietly distort decision-making—despite an “immaculate” P&L.

Resources Mentioned

• LinkedIn SaaS P&L Post: https://www.linkedin.com/posts/benrmurray_saas-activity-7418308514533552128-l2eG/
• SaaS P&L Blog Post:
• SaaS Metrics Course:

What You’ll Learn

• Why a clean SaaS P&L can still hide structural business risk
• How revenue commingling and miscoding undermine financial clarity
• When and how to reclass employee costs across departments
• Why materiality matters more than perfection in early-stage accounting
• How customer concentration risk often surfaces late in due diligence

Why It Matters

• A SaaS P&L is only as useful as the assumptions behind it
• Poor expense classification can distort margins and unit economics
• Misunderstanding departmental cost ownership leads to flawed decisions
• Customer concentration can materially impact valuation and investor confidence
• Strong financial systems require both structure and experienced oversight

In episode #347 of SaaS Metrics School, Ben Murray explores the lesser-discussed nuances behind ARR (Annual Recurring Revenue) disclosures. Building on the prior two episodes on ARR definitions and common disclosure mistakes, this discussion dives into the assumptions and gray areas that often underlie headline ARR numbers.

Drawing on extensive research across public tech company filings, Ben explains how assumptions about renewals, timing, and grace periods can materially affect how ARR is interpreted by boards, investors, and acquirers.

Resources Mentioned

• Blog post: In-depth analysis of ARR definitions and disclosure practices: https://www.thesaascfo.com/cfos-guide-to-disclosing-headline-arr-numbers/
• SaaS Metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation

What You’ll Learn

• Why most ARR definitions assume full renewal of existing contracts
• How ARR disclosures typically avoid assumptions around expansion, contraction, or churn
• Why ARR is almost always a point-in-time metric rather than a forecast
• Common disclaimers used to separate ARR from GAAP revenue and financial guidance
• How grace periods for contract renewals can materially affect reported ARR—and how some public companies quantify that risk

Why It Matters

• ARR assumptions directly influence how investors assess revenue durability
• Poorly explained ARR nuances can create confusion during due diligence
• Grace periods can inflate perceived recurring revenue if not disclosed properly
• Transparent ARR disclosures strengthen credibility with boards and potential buyers
• A defensible ARR definition supports better financial strategy and valuation discussions

In episode #346 of SaaS Metrics School, Ben Murray breaks down the most common mistakes SaaS and AI companies make when disclosing their ARR (Annual Recurring Revenue). Building on the prior episode about the five questions every ARR definition must answer, this discussion focuses on where ARR disclosures go wrong—and why unclear definitions can damage credibility with investors, boards, and acquirers.

Drawing from extensive research on public tech company filings and press releases, Ben explains how vague ARR definitions, hidden mechanics, and inconsistent methodologies create confusion and risk during fundraising, valuation discussions, and due diligence.

Resources Mentioned

• Prior episode: The 5 Questions Your ARR Definition Must Answer
• SaaS Metrics Course: https://www.thesaasacademy.com/the-saas-metrics-foundation
• Blog post on ARR: https://www.thesaascfo.com/cfos-guide-to-disclosing-headline-arr-number

What You’ll Learn

• Why a company’s pricing model does not always match its ARR model
• The importance of clearly defining which revenue streams are included in ARR
• Common issues with vague annualization periods (monthly vs. quarterly vs. trailing periods)
• How poor disclosure of usage-based or variable revenue creates misleading ARR numbers
• Why ARR definition changes and restatements require clear explanation and transparency

Why It Matters

• Clear ARR disclosure builds trust with investors, boards, and business leaders
• Poorly defined ARR can undermine company valuation and fundraising conversations
• Inconsistent ARR definitions make benchmarking and financial modeling unreliable
• Transparent ARR mechanics reduce follow-up questions during due diligence
• Strong financial strategy starts with defensible, repeatable revenue metrics

Defining ARR is getting harder—not easier—as SaaS, AI, usage-based pricing, and hybrid business models evolve. In episode #345 of SaaS Metrics School, Ben Murray breaks down the five critical questions every ARR definition must answer to hold up with Boards, investors, and during due diligence.

Drawing on extensive research into how public tech companies disclose ARR in press releases and SEC filings, Ben explains why ARR is not “dead” but why vague or inconsistent ARR definitions undermine credibility, comparability, and company valuation. This episode provides a practical framework to help SaaS leaders, CFOs, and founders clearly define ARR in a way that supports accurate metrics, financial modeling, and investor trust.

Resources Mentioned

• Blog post on ARR definitions and disclosure best practices: https://www.thesaascfo.com/cfos-guide-to-disclosing-headline-arr-numbers/
• Ben's SaaS Metrics training: https://www.thesaasacademy.com/the-saas-metrics-foundation

You’ll Learn

• The five questions every ARR definition must answer to be investor-ready
• Which revenue types belong in ARR—and which should be excluded
• The difference between revenue-based, contract-based, and hybrid ARR calculations
• How public SaaS and AI companies annualize subscription and usage-based revenue
• Common approaches for handling variable, consumption, and usage revenue in ARR
• Why vague ARR definitions create confusion in fundraising and due diligence

Why It Matters

• Clear ARR definitions improve credibility with investors and business leaders
• Poorly defined ARR can negatively impact company valuation
• Consistent ARR logic enables better KPI tracking and benchmarking
• Transparent ARR disclosures reduce friction during fundraising and M&A
• Accurate ARR supports stronger financial strategy and forecasting
• Well-defined revenue categories improve accounting and financial systems

In episode #344 of SaaS Metrics School, Ben Murray shares insights from his research into how public tech companies define and disclose ARR in press releases and SEC filings. By analyzing U.S. and global public companies, Ben identifies common ARR “buckets” and explains how different revenue models influence what gets included in ARR.

Rather than debating whether ARR is “dead,” this episode focuses on how companies are actually reporting ARR today—and what private SaaS and AI companies can learn from those disclosures.

Resources Mentioned

• Subscribe to Ben’s SaaS newsletter: https://mailchi.mp/df1db6bf8bca/the-saas-cfo-sign-up-landing-page
  Verint (example of detailed SaaS and AI ARR disclosures): https://www.thesaascfo.com/ai-arr-vs-saas-arr-how-to-define-and-calculate/

What You’ll Learn

• The most common ARR buckets used by public SaaS and tech companies
• How pure subscription revenue is typically defined in ARR
• How companies handle variable revenue such as usage, transactions, and overages
• When managed services revenue is included in ARR—and when it isn’t
• Why purely usage-based companies rarely report ARR
• How revenue models and pricing structures shape ARR definitions
• What ARR disclosures signal to investors and the public markets

Why It Matters

• ARR definitions directly impact how investors interpret growth
• Clear ARR buckets improve transparency and credibility
• Mixed revenue models require thoughtful ARR construction
• Public company disclosures set expectations for private companies
• Poor ARR definitions can confuse metrics, forecasting, and valuation
• Understanding ARR structure helps align finance, accounting, and reporting

In episode #343 of SaaS Metrics School, Ben Murray demystifies SaaS revenue by breaking down the core revenue types that software, SaaS, and AI companies should be modeling on their P&L. Rather than focusing on labels, Ben explains why pricing models and revenue streams are the real drivers of financial clarity.

He walks through the most common revenue categories—subscriptions, variable usage-based revenue, professional services, managed services, hardware, and other emerging models—and shows how proper revenue segmentation becomes the foundation for accurate retention metrics, forecasting, unit economics, and due diligence readiness.

Resources Mentioned

• SaaS Metrics School framework: https://www.thesaascfo.com/scaling-with-confidence-the-ultimate-saas-metrics-playbook/
• Concepts covered in Ben’s SaaS Metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation
• MRR schedules & MRR waterfalls: https://www.thesaasacademy.com/offers/rJhZ6VdM/checkout

What You’ll Learn

• The core revenue categories every SaaS, software, and AI company should track
• How subscription and usage-based revenue differ financially
• Why overages must be separated from subscription revenue
• How revenue segmentation enables accurate MRR schedules and waterfalls
• Why retention should be calculated separately by revenue stream
• How revenue structure impacts forecasting accuracy
• How different revenue streams change CAC payback and LTV to CAC calculations
• Why clean revenue categorization simplifies due diligence

Why It Matters

• Revenue segmentation is the foundation of accurate SaaS metrics
• MRR schedules and retention calculations depend on clean revenue data
• Forecasts are more reliable when built from revenue waterfalls
• Mixed revenue streams require adjusted CAC payback calculations
• Clear revenue structure improves investor and acquirer confidence
• Proper setup reduces friction during fundraising and exits