Growth Expectations and Metrics

What growth investors expect, the metrics they use to judge it, and how venture returns follow a power law.

Rules of thumb for growth

Investors use shorthand for what fast growth looks like. The best known is T2D3, from Battery Ventures' Neeraj Agrawal (2015): a software company triples its annual recurring revenue (the annualized value of its subscriptions) for two years, then doubles it for three, a path from a few million dollars toward $100 million. Another is the Rule of 40: revenue growth rate plus profit margin should add up to at least 40%. These are benchmarks for venture-backed software, not requirements, and the exact numbers vary by source. What they show is the expectation: growth that compounds year after year, balanced against how efficiently it is bought.

Metrics investors look at

Once a company has revenue, conversations with investors rely on a set of metrics borrowed from SaaS businesses, whose subscription model produces clear, measurable growth signals. They are worth knowing whether or not the company is SaaS.

ARR (Annual Recurring Revenue): monthly recurring revenue multiplied by 12, the standard headline growth number once a company has meaningful recurring revenue. It is a run-rate, not revenue already collected.
Gross margin: revenue minus the direct cost of delivering the product, as a percentage of revenue. Software businesses often run high gross margins because delivering an additional unit costs little.
Churn and net revenue retention (NRR): churn is the rate at which customers cancel or stop paying. NRR is the percentage of revenue retained from an existing cohort over a year, including upsells and net of downgrades and cancellations. Above 100% means existing customers are spending more than they were a year earlier, before counting any new customers.
CAC (Customer Acquisition Cost) and payback: CAC is the total sales and marketing spend divided by the number of new customers it produced. Payback is the months of gross profit from a new customer needed to recover it. David Skok's SaaS metrics writing calls a payback of 5 to 7 months strong and over 12 months a drag on profitability, and a lifetime value of at least 3x CAC a common benchmark. He calls these guidelines.
Burn multiple: net burn divided by net new ARR over the same period, how much cash it costs to add a dollar of recurring revenue. David Sacks (Craft Ventures) introduced it in a 2020 post and called about 2x reasonable for an early-stage company and 3x or more a warning sign. Lower is better.

These metrics need a mature business to mean anything. Most of them assume a recurring-revenue company with enough customer history to calculate a meaningful churn rate or lifetime value. A pre-seed company with a handful of early customers lacks the data for reliable CAC, LTV, or NRR, and a spreadsheet full of them at a six-person company chasing product-market fit produces false precision. At that stage, retention and usage intensity, covered in the first lesson, tell you more than a ratio built on ten data points.

Unicorns

A unicorn is a private company valued at $1 billion or more (the term comes from investor Aileen Lee's November 2013 TechCrunch article, which counted 39 US-based software companies founded since 2003 and valued above $1 billion, about 0.07% of venture-backed software startups); a decacorn is one valued at $10 billion or more. Both terms describe a private valuation: the number agreed on between a company and its investors in its most recent round. Neither measures revenue or profitability, and startup news often conflates the three. A company can cross a billion-dollar valuation with modest revenue and no profitability, if investors believe the growth trajectory and market opportunity justify that price today.

When two companies with comparable revenue end up with very different valuations, the gap usually comes from market size, growth rate, retention, gross margin, differentiation, defensibility, customer quality, and the team, weighed together. A company growing 150% a year with 95% retention and a defensible technical moat earns a higher multiple on its revenue than one growing 30% with high churn, even when this quarter's revenue matches (illustrative figures).

The power law

Venture capital is built around a power law: a distribution where most outcomes cluster near zero and a tiny handful are so large they dwarf everything else combined. Correlation Ventures' dataset of more than 21,000 financings (reported by investor Seth Levine in 2014, covering through 2013) found that 65% returned less than 1x invested capital, 10% returned 5x or more, and 4% returned 10x or more. A fund's performance depends on a few outcomes covering the rest.

Here is an invented example. A fund writes twenty $1,000,000 checks into twenty seed-stage companies, and the outcomes come out uneven: ten of the twenty return nothing, six return roughly what was put in, two return 3x, one returns 10x, and one returns 100x. That's $122,000,000 back on a $20,000,000 fund, and the single 100x company accounts for $100,000,000 of it, more than four-fifths of the total, from one investment out of twenty.

That single company is what VCs call a fund returner: an investment big enough on its own to return the entire fund, whatever the other nineteen do. Each check is a bet that the company could become one, because the failures and modest wins together will not carry the fund. Plenty of good businesses have no realistic path to that outcome.

Venture capital fits a narrow slice of profitable companies. A profitable consulting firm, a well-run local services business, or a steady, modestly growing software company can all be excellent and still be poorly served by venture funding. The growth pressure that comes with that capital can hurt a company that was better off staying disciplined and profitable on its own terms.

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