Happening this Friday! If AI in finance still feels more theoretical than practical, this one's for you!
Abacum is closing out their Summer Fridays series with a session featuring customer RapidSOS and they're going deep. Expect a live walkthrough of how their finance team actually uses NetSuite alongside Abacum AI Spaces to cut time out of the close, reduce the back-and-forth on data requests, and get to insights faster without adding headcount.
This isn't a product pitch, it's a finance leader showing their real workflow and the tools that power it.
If you're still spending too much of the close chasing numbers instead of analyzing them, it's worth the time!
Catch and Release: Too Big to Acquire
I’m happy to announce that after 30 consecutive Father’s Days of gifting my dad a box of Titleist golf balls, I splurged for something different: a charter fishing trip (technically sponsored by Abacum).
So me, my dad, brother, and brother-in-law braved the pristine 75 degree elements of Cape Cod Bay to catch not one, but six striped bass.
As an added bonus, we got to listen to a first mate named Cookie tell us classic fisherman stories (not suitable for work, and def not sponsored by Abacum).
The first water animal we reeled in put up a formidable fight. My dad battled it on the line for what seemed like an eternity (approx 7 minutes), until it finally flopped onto the weathered deck of the Bad Dog with a deep thud.
High fiving in the background, me and my brother encouraged my dad to take a pic.
The Original Carl (that’s my govt. name)
Then Cookie said,
“Alrite, we’ll have to throw this sucker back in.”
Throw it back in? This thing weighs more than my one year old son. What do you mean?
“It’s too big.”
Apparently there’s such a thing as doing too good at fishing.
The exact language from Massachusetts regulation 322 CMR 6.07(5)(a) is:
“Only striped bass measuring at least 28 inches and less than 31 inches in total length may be retained.”
Turns out the big ones are protected because they’re the most valuable breeders. They make the new fish, which keeps the larger ecosystem healthy. MA decided some striped bass are too systematically important to eat.
But, like, that’s an incredibly narrow range of “successful” outcomes.
Less than 28 inches? Throw it back.
More than 31 inches? Also, throw it back.
Someone get the rulebook a Busch Light.
While I don’t take issue with the low end of the spectrum, the ceiling felt antithetical to the ethos of fishing.
In many ways it reminded me of trying to sell a company. There is, in fact, such a thing as being “too big” to acquire.
Ironically, the day we went fishing, SpaceX closed on Cursor for $60 billion in stock. That is the most money anyone has ever paid for a venture-backed company.
It passed Wiz ($32 billion paid by Google) and WhatsApp ($22 billion paid by Meta) on the way. While the bar continues to grind upwards, there are still laws of gravity and physics when it comes to exits.
With each successful funding round you raise your chances of commercial success. You have more money to hire people, build product, and acquire customers.
You also shrink the number of companies that can realistically buy you.
Every funding round increases your operating optionality while decreasing your exit optionality.
Each rung you climb requires someone with a bigger wallet and a bigger appetite for risk (and the patience to sit through a lengthy and expensive FTC review).
Congrats, you’re too big to keep.
I remember working at a company in a very specific sector where we were contemplating a fundraise that would push us above a $10 billion valuation. As Russ Hanneman would say, the tres commas club.
Someone remarked at the time,
“If you take this money, you should be damn sure you’re going public. Because at that valuation the only companies who could realistically afford to acquire you are Google and Microsoft.”
So just like that, the buyer universe went from maybe 25 to less than 5.
(We took the money anyways.)
I wonder what happens to many of the super well funded AI companies like Harvey and Legora in legal, or Lovable and Vercel in design and coding. They’re raising enormous rounds at enormous valuations, and every round makes the eventual buyer universe a lot smaller.
There ain’t any legal tech companies that can afford to buy Harvey at that size. There ain’t many design companies that can afford Lovable (also, see: Adobe - Figma).
The capital gives them more ammunition to win their markets, while the valuation pushes them further toward a much narrower set of outcomes: go public, get acquired by one of a handful of megacaps, or keep swimming.
So back to the boat.
While we were able to reel in six deck thumpers, we were only able to keep one.
And while ya boy didn’t catch the largest striper, he was the only one to take a fish home.
Acquired in an all stock deal.
Weekly Valuation and Efficiency Metrics
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.
Companies Included
1. Security & Identity (16 companies) Endpoint, network, IAM, security operations. The CISO budget.
CrowdStrike, Palo Alto Networks, Fortinet, Cloudflare, Zscaler, Okta, SentinelOne, SailPoint, Check Point, Qualys, Tenable, Rapid7, Varonis, Rubrik, Mitek, OneSpan
2. Data & AI Infrastructure (12 companies) Modern data stack, AI/ML platforms, vector and analytics infra, GPU compute. Software-native by design.
Snowflake, Arista Networks, Equinix, CoreWeave, MongoDB, DigitalOcean, Elastic, Akamai, Fastly, Teradata, C3.ai, Cerebras
3. Dev Tools & Observability (10 companies) Anything bought out of the engineering budget.
Datadog, Atlassian, Figma, Dynatrace, Nutanix, GitLab, UiPath, JFrog, AvePoint, PagerDuty
4. Horizontal SaaS & Back Office (18 companies) Software sold across industries to ops, HR, finance, and collaboration teams. Not vertical-specific.
Oracle, ServiceNow, Workday, ADP, Paychex, Paycom, Paylocity, Zoom, DocuSign, Navan, monday.com, Asana, Workiva, BlackLine, RingCentral, 8x8, Box, Dropbox
5. GTM (MarTech & SalesTech) (18 companies) Anything bought out of the revenue org. Marketing automation, sales engagement, CRM, ad tech, customer experience.
Salesforce, Adobe, HubSpot, The Trade Desk, Twilio, Klaviyo, Braze, ZoomInfo, Freshworks, Amplitude, Semrush, Five9, Zeta Global, Wix, Sprout Social, ON24, Yext, Criteo
6. Vertical SaaS (15 companies) Software built for a specific industry without take-rate or transaction economics.
Palantir, Autodesk, Veeva, Samsara, ServiceTitan, Guidewire, Tyler Technologies, Doximity, Procore, AppFolio, CCC Intelligent Solutions, Blackbaud, nCino, CareCloud, CS Disco
7. Take-Rate Platforms (18 companies) Marketplaces and commerce platforms that earn money on transaction volume.
Uber, Airbnb, Shopify, MercadoLibre, DoorDash, eBay, Zillow, CarGurus, Instacart, Etsy, Toast, Lyft, Opendoor, StubHub, Upwork, Coursera, Ethos, Fiverr
8. Payments & Money Movement (10 companies) The rails. Payment processors, payment infrastructure, B2B payments, treasury. Volume game, utility margins.
Intuit, Fiserv, Adyen, PayPal, Block, Shift4, BILL, Flywire, Marqeta, Lightspeed
9. Consumer Fintech, Lending & Crypto (15 companies) The front-end. Consumer-facing financial apps, BNPL, lending platforms, crypto exchanges. CAC-driven, marketing-heavy, totally different unit economics from #8.
Coinbase, Robinhood, SoFi, Chime, Affirm, Upstart, Circle, Bullish, Figure, Klarna, Sezzle, Gemini, Blend, Remitly, LendingClub
Please check out our data partner, Koyfin. It’s dope.
Wishing you trade at a high revenue and EBITDA multiple,
CJ
