Big Arms and Skinny Legs
7/14/24 Benchmarks for Operators
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My wife says I don’t listen, but readers would beg to differ.
Just take it from reader Zane S. who encouraged me to add back in the FinTech sector. You’ll see it reflected in all the charts below.
Fintech is back baby!
The companies included within Fintech:
Affirm
Bill.com
Blend
Block
Clearwater Analytics
Coinbase
Flywire
Intuit
Lightspeed POS
Marqeta
Money Lion
PayPal
Remitly
Robinhood
Shopify
Zuora inc
I’m currently EXCLUDING
SoFi - they are also a bank, and the cash deposits throw off the metrics
NU, Adyen, and Wise - they are international and don’t report at the same frequency or at the same depth for comparability.
The P&L for Fintechs is in many ways inverse to traditional software models…
They have heavy COGS, which burdens their gross margins more than typical SaaS models (61% median gross margin for FinTechs vs 75% Median gross margin across the 109 tech co’s we track).
BUT they don’t require nearly as much OPEX. S&M and R&D are thinner on the P&L. In fact, once you get past the COGS line, Fintechs RIP at scale.
There are heavy tolls paid in the form of bank, brokerage, licensing, origination, and payment processing fees, but they need less people to generate revenue once the core infrastructure is in place and network effects start to kick in.
How do I know? Revenue per head for FinTech’s is 1.5x that of the larger basket of companies we track, approaching $700k per employee, and their CAC Payback Period is under a year.
I guess skipping leg day can work out.
TL;DR: Multiples are DOWN week-over-week.
Top 10 Medians:
EV / NTM Revenue = 13.4x (-0.6x w/w)
CAC Payback = 18 months
Rule of 40 = 49%
Revenue per Employee = $502K
Figures for each index are measured at the Median
Median and Top 10 Median are measured across the entire data set, where n = 109
Population Sizes:
Security: 17
Database and Infra: 14
Backoffice: 15
Marcom: 16
Marketplace: 15
Fintech: 16
Vertical SaaS: 16
If you’d like the company level metrics used in these reports, upgrade to paid and you can download the excel sheet at the bottom of this post
Revenue Multiples
Revenue multiples are a shortcut to compare valuations across the technology landscape, where companies may not yet be profitable. The most standard timeframe for revenue multiple comparison is on a “Next Twelve Months” (NTM Revenue) basis.
NTM is a generous cut, as it gives a company “credit” for a full “rolling” future year. It also puts all companies on equal footing, regardless of their fiscal year end and quarterly seasonality.
However, not all technology sectors or monetization strategies receive the same “credit” on their forward revenue, which operators should be aware of when they create comp sets for their own companies. That is why I break them out as separate “indexes”.
Reasons may include:
Recurring mix of revenue
Stickiness of revenue
Average contract size
Cost of revenue delivery
Criticality of solution
Total Addressable Market potential
From a macro perspective, multiples trend higher in low interest environments, and vice versa.
Multiples shown are calculated by taking the Enterprise Value / NTM revenue.
Enterprise Value is calculated as: Market Capitalization + Total Debt - Cash
Market Cap fluctuates with share price day to day, while Total Debt and Cash are taken from the most recent quarterly financial statements available. That’s why we share this report each week - to keep up with changes in the stock market, and to update for quarterly earnings reports when they drop.
Historically, a 10x NTM Revenue multiple has been viewed as a “premium” valuation reserved for the best of the best companies.
Efficiency Benchmarks
Companies that can do more with less tend to earn higher valuations.
Three of the most common and consistently publicly available metrics to measure efficiency include:
CAC Payback Period: How many months does it take to recoup the cost of acquiring a customer?
CAC Payback Period is measured as Sales and Marketing costs divided by Revenue Additions, and adjusted by Gross Margin.
Here’s how I do it:
Sales and Marketing costs are measured on a TTM basis, but lagged by one quarter (so you skip a quarter, then sum the trailing four quarters of costs). This timeframe smoothes for seasonality and recognizes the lead time required to generate pipeline.
Revenue is measured as the year-on-year change in the most recent quarter’s sales (so for Q2 of 2024 you’d subtract out Q2 of 2023’s revenue to get the increase), and then multiplied by four to arrive at an annualized revenue increase (e.g., ARR Additions).
Gross margin is taken as a % from the most recent quarter (e.g., 82%) to represent the current cost to serve a customer
Revenue per Employee: On a per head basis, how much in sales does the company generate each year? The rule of thumb is public companies should be doing north of $450k per employee at scale. This is simple division. And I believe it cuts through all the noise - there’s nowhere to hide.
Revenue per Employee is calculated as: (TTM Revenue / Total Current Employees)
Rule of 40: How does a company balance topline growth with bottom line efficiency? It’s the sum of the company’s revenue growth rate and EBITDA Margin. Netting the two should get you above 40 to pass the test.
Rule of 40 is calculated as: TTM Revenue Growth % + TTM Adjusted EBITDA Margin %
A few other notes on efficiency metrics:
Net Dollar Retention is another great measure of efficiency, but many companies have stopped quoting it as an exact number, choosing instead to disclose if it’s above or below a threshold once a year. It’s also uncommon for some types of companies, like marketplaces, to report it at all.
Most public companies don’t report net new ARR, and not all revenue is “recurring”, so I’m doing my best to approximate using changes in reported GAAP revenue. I admit this is a “stricter” view, as it is measuring change in net revenue.
Operating Expenditures
Decreasing your OPEX relative to revenue demonstrates Operating Leverage, and leaves more dollars to drop to the bottom line, as companies strive to achieve +25% profitability at scale.
The most common buckets companies put their operating costs into are:
Cost of Goods Sold: Customer Support employees, infrastructure to host your business online, API tolls, and banking fees if you are a FinTech.
Sales & Marketing: Sales and Marketing employees, advertising spend, demand gen spend, events, conferences, tools
Research & Development: Product and Engineering employees, development expenses, tools
General & Administrative: Finance, HR, and IT employees… and everything else. Or as I like to call myself “Strategic Backoffice Overhead”
All of these are taken on a Gaap basis and therefore INCLUDE stock based comp, a non cash expense.
Want to build your own comp set?
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