Today's issue is brought to you by Abacum.
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New Jobs: Managers + Directors
Yo, it's CJ! My recruiting arm, Mostly Talent, has been retained to fill the following roles directly from our readership:
Senior Manager, FP&A (Boston based, Public B2B SaaS): R&D Business Partner. Must have cloud forecasting and ideally LLM forecasting experience.
Senior Director, FP&A (Remote, Public Consumer Fintech): Consumer focused. Work directly with CFO to plan new product lines and allocate marketing spend.
Senior Manager, FP&A (Remote, Public Consumer Fintech): Consumer focused. Build and own long term forecast. Must have public company experience.
Director, Strategic Finance (SF, Pre-IPO AI SaaS Applications): GTM focused. Build long term company forecast across multiple product lines and GTM motions.
Director, FP&A (SF, Series C hypergrowth B2B AI SaaS Applications): Partner directly with VP of finance to own operating plan and drive future fundraises.
These are the types of jobs I wish I could have worked on my path to CFO.
NGL, I’m kinda jealous!
If you need to hire and want to work with Mostly Talent, go here.
Why Customer Count Can Be a Misleading Metric
The average age of an American who wears diapers is 22 years old. That stat sounds absurd until you realize it's because adult incontinence products outnumber baby diapers in the US. The average is technically correct. It just tells you nothing useful. In fact, if anything, it’s even more misleading.
Customer count works the same way.
It looks like a simple number. Psyyych.
Customer count feels like the one metric you can take at face value. In a world where you can just “say things” these days, you’d think this would be really straight forward. It’s supposed to be void of revenue recognition judgment calls, debates about what qualifies as "recurring," and any crazy ebitda adjustments. It’s just the straight up count of how many customers you have. Give it to me straight, doc!
But I've come to think of customer count as one of the most context-dependent numbers in the business, and the CFOs I respect most treat it accordingly.
"For some businesses, you need to be really careful about customer count metrics. Especially active customers. For some businesses it makes sense. For other businesses it doesn't make sense."
For context, Faire is a B2B marketplace with a wide funnel driven by power law revenue dynamics. A relatively small percentage of accounts drives the majority of what matters. So while they monitor customer count as a way to gauge reach, they've never treated it as a core performance metric. Putting the raw number in a board deck would flatten all of the story (and distributino) into a single figure that feels super clean but doesn't reflect how the business actually operates.
Square’s Power Law
Prior to Faire, Jason ran FP&A at Square for Jack Dorsey. At one point the team looked closely at customers with one order in the last year versus customers with ten orders in the last year. The difference in customer count between those two groups was significant. A massive jump. But the difference in revenue was almost nothing.
That's the (dangerous) trap.
If your revenue follows a power law, the average customer is fictitious.
You have a handful of accounts that drive the business, and a long tail that barely registers.
Reporting total customer count treats all of them as equivalent, which means the number grows in ways that have no relationship to whether the business is actually healthier.
Get this - there’s a world where you increase customer count and your business achieves less revenue. There’s also a world where you chop off a ton of your customers but are able to increase total revenue by focusing on the ones that matter.
That’s why at Faire, the internal framing is that customer count is a check metric - something you monitor to confirm the funnel is working, not something you optimize toward or staff against.
The definition of “customer” is usually soft AF
Compounding all of this is the fact that "customer" isn't a standardized term, and the bar for "active" tends to be lower than most people realize. One login… One purchase... One order placed in a twelve-month window. That's often all it takes to qualify. So congrats, you're the weakest strong man at the circus.
Companies also have real incentives to draw that line wherever the resulting metrics look most favorable. Tighten the definition of active and churn goes down, net dollar retention goes up, and average deal size increases, simultaneously. There are some perverse incentives at play, and they don't always get disclosed in the footnotes.
Mark McCaffrey, CFO of GoDaddy, made the point when we spoke: one subscriber can carry four subscriptions.
And GoDaddy has 22 million customers. McCaffrey will be the first to tell you the raw number doesn't tell you whether the business is growing. ARPU and attach rate are what actually show you the trajectory, not total or active customers.
Product-led growth made all of this messier. Self-serve funnels and usage-based pricing bring customers in at lower initial spend than a traditional seat-based model, which means the line between "prospect" and "paying customer" blurs earlier in the journey. And as a result, companies have gotten more liberal with how they count, partly because the model evolved, and partly because a bigger number reads better.
What the best operators track instead
When you're analyzing any business, the right starting assumption is that anyone who paid you in the last twelve months is a customer, and then you work backwards from there to understand what got excluded and why.
We can also look at the big dogs. CrowdStrike stopped disclosing total customer count entirely. What they report now is customers above $100K and $1M in ARR. Many of the other cybersecurity companies followed suit. These businesses live and die by it’s enterprise customers.
What they’re essentially implying is the smaller accounts don't drive the business in any meaningful way, so anchoring to a number that includes them creates more confusion than clarity for investors and operators alike.
Don’t even pay attention to them (sorry).
In fact, some companies with a ton of free prosumers don’t even start counting a customer until it crosses a certain threshold, like Gitlab, which starts at $5K.
Source: Gitlab Investor Day Deck. Customers are greater than $5K in ARR.
Net net:
Customer count tells you how wide your funnel is.
It doesn't tell you what's sitting at the bottom.
Customer count is not LTV.
It may not even be a leading indicator of revenue.
For that, you have to look at where the revenue weight actually lives, and be honest about whether the number you're reporting reflects that or not.
Because even worse than reporting the wrong number is making staffing and resourcing decisions off of it.
TL;DR: Medan Multiples are UP week over week.
The overall tech median is 3.1x (UP 0.1x w/w).
What Great Looks Like - Top 10 Medians:
EV / NTM Revenue = 13.2x (UP 0.3x w/w)
CAC Payback = 23 months
Rule of 40 = 49%
Revenue per Employee = $646k
Figures for each index are measured at the Median
Median and Top 10 Median are measured across the entire data set, where n = 144
Recent changes
Added: Navan, Bullish, Figure, Gemini, Stubhub, Klarna, Figma
Removed: Jamf, OneStream, Olo, Couchbase, Dayforce, Vimeo
Population Sizes:
Security & Identity = 17
Data Infrastructure & Dev Tools = 13
Cloud Platforms & Infra = 15
Horizontal SaaS & Back office = 17
GTM (MarTech & SalesTech) = 18
Marketplaces & Consumer Platforms = 18
FinTech & Payments = 28
Vertical SaaS = 17
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
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 smooths 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.
OPEX
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 in the cloud, 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.
Please check out our data partner, Koyfin. It’s dope.
Wishing you trade at a high revenue and EBITDA multiple,
CJ
