Keeping Up with ARR in a Variable Pricing World

Join Ben Murray and Ray Rike in this exclusive masterclass focused on accurate ARR calculations and key SaaS metrics for Usage-Based Pricing models. This session will dive into actionable best practices, real-world insights, and strategies to refine your financial modeling and optimize revenue growth. Perfect for SaaS leaders and finance teams looking to enhance pricing models and improve forecasting accuracy in today’s dynamic market.

What You’ll Learn

• ARR Calculation Best Practices in a Usage-Based Pricing Environment: Understand the methodologies to calculate ARR accurately.
• The Difference Between CARR and Variable ARR (VARR): Learn how these metrics impact financial strategy and business growth.
• Calculating CAC Payback Period and CAC Ratio: Discover how to compute these essential metrics in a Usage-Based Pricing context.
• Using the Cohort Method for NRR: Learn how to accurately calculate NRR using the cohort method and adapt to usage-driven revenue changes.

Why Attend?

• Gain Practical Insights on ARR: Understand how to apply best practices for ARR calculation in Usage-Based Pricing.
• Unlock the Power of CARR & VARR: Learn how these metrics drive financial strategy and growth in your business.
• Optimize CAC Metrics: Discover how to accurately calculate CAC Payback Period and CAC Ratio in a Usage-Based model.
• Enhance NRR Forecasting: Learn how to use the cohort method to better predict NRR in a usage-driven revenue model

Who Should Attend?

• Finance Leaders in SaaS: Learn how to refine your ARR and key SaaS metrics in a Usage-Based Pricing environment.
• SaaS Executives and Product Managers: Gain insights into optimizing pricing models and improving financial forecasting.
• CFOs, VPs of Finance, and Financial Analysts: Get actionable strategies to enhance your financial processes and drive better decision-making.
  

About the Speakers

Ben Murray‍

Founder of The SaaS CFO, Ben has over a decade of experience helping SaaS businesses optimize financial modeling, ARR calculations, and revenue forecasting. He is a recognized expert in SaaS financial strategy and metrics.

Ray Rike

‍Founder of Benchmarkit, Ray is a seasoned SaaS financial strategist with extensive experience advising companies on Usage-Based Pricing models, scaling, and optimizing SaaS financial processes. His insights help SaaS businesses navigate complex pricing strategies and accelerate growth.

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Webinar Summary

1. How are public companies defining ARR today, and what are the most common calculation methods?

An analysis of 167 public tech SEC filings and 92 press releases reveals four ARR definition categories: pure subscription (92 companies), subscription plus variable/usage (22), subscription plus managed services (10), and all revenue streams lumped together (2). Notably, 105 of the 167 SEC filings had no formal ARR definition at all.

The most popular calculation method is MRR × 12. The second is QR × 4 (quarterly revenue times four). Some companies use an unspecified revenue run rate snapshot at a measurement date, while others build ARR from contractual value rather than GAAP revenue recognition. For multi-year ramp contracts, a common approach is total contract value divided by the contract term for a blended figure. Each method reflects a different revenue recognition approach and must be disclosed clearly.

2. How should companies handle variable (usage/consumption) revenue in their ARR?

The recommended approach is to annualize the previous 90 days of actual usage. MongoDB takes trailing 90-day consumption and adds it to MRR × 12 for subscriptions. Confluent does the same. Taking just one month's usage-based revenue is too short a window unless it is highly predictable.

The emerging best practice is splitting ARR into contracted ARR and variable ARR as separate line items. Investors want to know how much is truly committed versus extrapolated. A common mistake is combining subscription and metered billing overage on a single invoice line — this breaks retention calculations and undermines accurate revenue forecasting.

3. How should renewals, grace periods, and churn be handled in ARR?

Nearly all companies assume contracts up for renewal will renew, even during active negotiation. One company disclosed a six-month grace period before removing a customer from ARR. The recommendation: establish a consistent policy (e.g., 90 days), apply it uniformly, and don't hide known churn in your ARR number.

For seasonal businesses, QR × 4 will mislead — use a 6-month or trailing-12-month window instead. Net revenue retention (NRR) captures the net impact, but only if the underlying ARR inputs are clean.

4. How are companies disclosing AI ARR, and why does it matter?

Companies like Verint now break out AI ARR — committed SaaS revenue plus usage-based revenue tied to AI features, multiplied by four. This proves to investors that AI is being monetized, not just marketed.

Despite the hype, outcome-based pricing is nearly nonexistent. Only one company out of 200+ filings explicitly uses it. Salesforce's AgentForce filings reference only subscription and consumption — no outcome-based language. Most "outcome-based" pricing is an outcome wrapper around usage-based billing. The rise of agentic AI pricing adds complexity — CFOs need SKU-level tracking and AI-powered billing infrastructure to report this accurately.

5. How do variable revenue models impact SaaS metrics like CAC payback, retention, and gross margin?

If 70% of revenue is subscription and 30% is usage, ignoring the usage component will severely overstate CAC payback. GRR, NRR, and logo retention must each be calculated separately by revenue stream before combining.

AI add-ons on third-party LLMs can have 40–60% gross margins versus 75–85% for core SaaS — segment them separately. Pilot revenue should never count as ARR; with 35–40% of AI companies starting on pilots and only 48% converting, inflation risk is real. Accurate CLTV, ARPU, and unit economics depend on a SaaS billing platform that segments revenue streams and applies the correct revenue recognition rules to each.