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SaaS Metrics

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SaaS Metrics: The MFM Guide to the Numbers That Actually Matter

The country of Bhutan does not measure GDP. It measures Gross National Happiness. For decades, economists dismissed this as a quirky policy from a small Himalayan kingdom. But Shaan Puri sees something in it that most people miss. “Countries are just big companies,” he observed on the podcast. “What’s our main metric? It’s not revenue, it’s happiness.”

The observation sounds like a throwaway line. It is not. It cuts to the deepest question in SaaS: which number should you actually care about? Revenue is the obvious answer, the GDP of any software company. But the best SaaS operators---the ones who build businesses worth billions---often measure something else entirely. They measure the rate at which customers stay.

This distinction between vanity metrics and real metrics, between numbers that look impressive in a pitch deck and numbers that predict survival, runs through nearly every business conversation on My First Million. The hosts have interviewed bootstrapped founders who built quietly to hundreds of millions in revenue and venture-backed rockets that compressed a decade of growth into eighteen months. The metrics they use to evaluate these businesses tell you more about how wealth actually works in software than any finance textbook.

The Core SaaS Metrics

There is a language that SaaS founders speak fluently and that outsiders find impenetrable. The vocabulary is smaller than it appears. Five or six numbers explain most of what matters.

MRR and ARR are the foundation. Monthly Recurring Revenue is the predictable income a SaaS company collects each month from subscriptions. Multiply by twelve and you get Annual Recurring Revenue. The distinction from total revenue matters because one-time payments, services revenue, and implementation fees do not compound the way subscriptions do. When Andrew Wilkinson describes Tiny’s portfolio, he leads with the recurring number: “We have 65 million of ARR. We do over 200 million fund. Over 300 million in revenue across 30 businesses.” The ARR figure comes first because it is the one that determines valuation.

Churn is the silent killer. It measures the percentage of customers who cancel their subscriptions each month or year. A SaaS company with 5% monthly churn loses half its customer base in a year. Even 3% monthly churn means a company must replace a third of its revenue annually just to stay flat. The best SaaS businesses achieve negative net revenue churn---existing customers expand their usage faster than departing customers reduce the base. This is the metric that separates companies worth ten times revenue from companies worth three times revenue.

LTV/CAC is the ratio that determines whether growth is profitable or suicidal. Lifetime Value divided by Customer Acquisition Cost tells you how many dollars you earn for every dollar you spend acquiring a customer. A ratio below one means you are paying more to get customers than they will ever be worth. A ratio of three or above is generally considered healthy. Below that, growth accelerates losses rather than compounding value.

The Rule of 40 combines growth rate and profit margin into a single benchmark. If a company grows at 60% annually with a negative 20% profit margin, the combined score is 40. If it grows at 20% with 20% margins, the score is also 40. Both are considered acceptable. Below 40 raises questions. Above 40 signals a business that is both growing and generating cash, which is rarer than most people assume.

The AI Disruption of SaaS Timelines

For twenty years, the trajectory of a successful SaaS company followed a recognizable curve. Getting to 10 million took four or five. The journey to $100 million in ARR was a seven-to-ten-year affair, and only the elite companies made it at all.

Artificial intelligence is compressing these timelines so dramatically that the old benchmarks are becoming artifacts. On the podcast, the hosts discussed the new generation of AI-native SaaS companies with something close to disbelief. “Do you know these SaaS metrics of how long to get to 100 million or whatever?” one noted. “The AI apps---and I would say Magic School is on that trajectory---is just like straight up.” The growth curve is not a hockey stick. It is a vertical line.

The evidence extends beyond any single company. Siqi Chen, a Silicon Valley veteran who appeared on MFM, made the point even more forcefully when discussing the competitive landscape: “There’s that graph for YC and the fastest growing SaaS companies. I think Cursor is up there. I am fairly convinced that ElevenLabs is actually faster than all of them.” The implication is startling. Companies built on AI infrastructure are not merely growing faster than their predecessors. They are rewriting the definition of what fast means.

This creates a paradox for metrics. The traditional SaaS benchmarks were calibrated to a world where customer acquisition happened through sales teams, where product adoption required training and onboarding, where switching costs were high because integration was painful. AI products often acquire users through viral loops, require no onboarding, and deliver value in minutes. The metrics still matter---churn is churn, revenue is revenue---but the timelines that once signaled exceptional performance now signal mediocrity. A company that takes five years to reach $100 million in ARR is no longer impressive. It may be falling behind.

Bootstrapped vs. Venture-Funded: Two Different Games

The metrics that define success look different depending on how you fund the journey. This is a point that Sam and Shaan return to repeatedly, and it is more nuanced than the simple narrative of bootstrap-good, venture-bad.

Zapier is the bootstrapped archetype. The company built an automation platform connecting thousands of software applications, grew without venture capital, and reached hundreds of millions in revenue. The valuation, as discussed on the podcast, sits somewhere between five and ten billion dollars. “Zapier is a business that was bootstrapped to hundreds of millions in revenue and is worth five or ten billion dollars,” the hosts observed.

The metrics that matter in a bootstrapped SaaS company are fundamentally about efficiency. Profitability is not optional. Growth must be funded from cash flow, which means CAC must be recovered quickly, churn must be low, and margins must be wide enough to reinvest while still paying the founders and early employees. The Rule of 40 is less relevant here because the bootstrap constraint naturally enforces it. You cannot spend more than you make when no one is writing you checks.

Venture-funded SaaS operates on different math. The game is to grow as fast as possible, capture market share before competitors, and worry about profitability later. The metrics shift accordingly. Growth rate becomes the primary number. Burn rate becomes acceptable as long as it purchases growth. LTV/CAC ratios can be temporarily negative if the unit economics improve at scale.

The risk is obvious. Many venture-funded SaaS companies never reach profitability. They grow into a wall where customer acquisition becomes expensive, churn accumulates, and the fundraising environment shifts. The ones that succeed---the Slacks, the Zooms, the Shopifys---do so because the underlying unit economics eventually work. The ones that fail often had metrics that looked impressive on a slide deck but concealed fatal problems in retention or margin.

The Portfolio Approach: Wilkinson’s Multi-SaaS Metrics

Andrew Wilkinson represents a third path that is neither pure bootstrap nor pure venture. His holding company, Tiny, owns stakes in dozens of businesses, many of them SaaS. The metrics he tracks are those of a capital allocator, not an operator.

The numbers he shared on the podcast paint a picture of what disciplined SaaS portfolio management looks like at scale: 40 million in EBITDA, more than 40 million in EBITDA on $65 million in ARR implies margins that most venture-backed SaaS founders would consider impossible.

The trick is selection. Portfolio operators like Wilkinson do not need to build companies that grow at 100% annually. They need companies that grow modestly, retain customers reliably, and throw off cash that can be redeployed into the next acquisition. The critical metric is not growth rate. It is free cash flow yield---how much cash the business generates relative to the price paid to acquire it. A SaaS company growing at 15% with 40% margins and 95% annual retention is, in Wilkinson’s framework, more valuable than one growing at 80% with negative margins and 85% retention. The first compounds quietly. The second might not survive.

What Sam and Shaan Actually Look For

Across hundreds of episodes, a pattern emerges in how the hosts evaluate SaaS businesses. The metrics they emphasize reveal a philosophy that is less about any single number and more about the relationship between numbers.

Retention above all. A SaaS company with 95% annual retention can survive mediocre marketing, slow feature development, and management mistakes. A company with 80% retention cannot outrun the leak no matter how fast it grows. The hosts consistently return to this point. Revenue growth is a choice. Retention is a verdict.

Revenue per employee. This metric rarely appears in textbooks but surfaces constantly on MFM. A SaaS company doing 10 million with 200 employees. The first has optionality. The second has overhead. When AI tools allow small teams to build and maintain products that once required engineering armies, revenue per employee becomes perhaps the most important SaaS metric of the next decade.

Time to value. How quickly does a new user experience the benefit of the product? Products like Cursor and ElevenLabs compress this to minutes. Traditional enterprise SaaS might take months of implementation. The faster the time to value, the lower the acquisition cost and the higher the retention. This is why AI-native SaaS companies are breaking the old growth curves. They are not better at marketing. They are better at delivering immediate results.

The “would I use this” test. Perhaps the most unscientific metric on the list, but one the hosts apply constantly. Shaan Puri in particular evaluates products through personal experience. If a product is so useful that he reaches for it daily, the retention metrics are almost certainly strong. If he has to remind himself to use it, the churn data will eventually reflect the same indifference.

The Metrics That Mislead

Not every number that looks important is important. The podcast has surfaced several metrics that founders obsess over but that experienced operators discount.

Total users is perhaps the most dangerous vanity metric in SaaS. A product with ten million free users and ten thousand paying customers is not a successful business with a conversion problem. It is an unsuccessful business with a large audience. The distinction matters because the instinct is to celebrate the large number and assume the small number will grow. It usually does not.

Gross revenue without context is meaningless. A SaaS company that generates 60 million acquiring those customers is not a $50 million business. It is a machine that converts investor capital into customer usage at a loss. The Bhutan analogy applies here. GDP---or revenue---tells you the size of the economy. It tells you nothing about whether anyone is happy, or in SaaS terms, whether the business actually works.

Growth rate in isolation is equally deceptive. A company growing at 200% annually from 50 million. The first has not yet proven that its model works at scale. The second is a phenomenon. Yet both can claim the same growth rate.

The Future of SaaS Metrics

The fundamental metrics---retention, unit economics, cash flow---are not changing. What is changing is the speed at which they become visible. AI-native SaaS companies reach the inflection points faster, which means the metrics that once took years to reveal themselves now emerge in months.

This acceleration has a counterintuitive consequence. It makes patience more valuable, not less. When every AI startup can show explosive early growth, the differentiator becomes sustainability. The companies that win will be those whose metrics improve as they scale rather than deteriorating. Revenue growth that comes with improving retention and expanding margins is real. Revenue growth that comes with worsening churn and rising acquisition costs is a countdown timer.

The small nation of Bhutan understood something that the SaaS industry is still learning: the most important metric is not the one that impresses outsiders. It is the one that tells you, honestly and without flattery, whether the thing you are building will endure.

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This article is part of the MFM Wiki, documenting ideas, frameworks, and people discussed on the My First Million podcast.

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