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Reliable data about private growth-stage software companies is extremely hard to find. In our experience, what’s available is typically self-reported (therefore noisy), and often lags by 2 quarters or more. Data on public software companies is more easily accessible, but is generally of limited utility for growth-stage companies and also lags by several months.
We believe that quality data is essential to helping software companies scale, which is why we make our own internal consolidated metrics available to founders each month. These numbers are aggregated from hundreds of private software companies that RAC reviews across our funds, using only primary sources, validated by our investment team. We exclude companies that are below $2.5 million of ARR.
The May metrics by growth cohort:
The May metrics by Rule of 40 cohort:
To learn more about the Private Software Growth Index and how it was constructed, please see the disclosure at the bottom of this post.
Our observations on the May data:
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We’re seeing a general trend of the ‘best’ companies getting ‘better’. For example, the companies that are above Rule of 40 are growing even faster compared to last month—and they’re doing so with less burn, quicker payback periods, and better retention. We could point to other examples in the data as well. We think it’s likely that AI tooling is amplifying the things that work well in high-performing companies, allowing them to further break away from the pack.
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Looking at faster vs. slower-growing cohorts, the difference in sales & marketing spend is not meaningful (33% v. 30% as a percent of revenue). The major difference is the level of spending on product/R&D, which accounts for nearly the entire delta in run-rate burn between the two groups. Our data suggests that the faster-growing cohort is spending at least 10 percentage points more on product compared to slower-growing companies.
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Software remains very sticky, with gross and net retention ticking up across almost all cohorts compared to last month.
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Gross margins are also continuing a general upward trend, up about 3 percentage points vs. a year ago. We suspect that AI tooling in customer success functions is largely behind this improvement.
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