Your forecast was right. Until something changed.
A deal slips. Hiring speeds up. Costs come in higher than expected. Suddenly someone wants to know what that means for the rest of the year.
The old answer? Duplicate the model, change a few assumptions, fix everything that broke, and hope you're comparing the right versions.
Abacum makes the "what if" part the easy part. Build scenarios off your actual plan, change the assumptions that matter, and see the impact flow through the business.
Because scenario planning shouldn't be a modeling exercise. It should help you answer the question everyone actually cares about:
So, what should we do next?
The Nightman Cometh
On Tuesday news broke that Airtable sold to Bending Spoons for $1.285B.
Bending Spoons is the company (conglomerate? holding company? island of misfit toys?) that went public just last month, and this is their first acquisition since listing on the Nasdaq. As a reminder, they are the owners of companies like AOL, Evernote, Eventbrite, and Vimeo.
Airtable is a ZIRP darling, raising at $1.17B in 2018, then $5.77B in 2019, and finally $11.7B in 2021. The company is generating $480M in revenue, growing at 20%, and sold for an enterprise value of $1.285B and an equity value of $2.15B when you add in the cash on the balance sheet that will be distributed to shareholders.
Here’s a rough estimate of what the acquisition shakes out at:

Ten Lessons

Late-stage SaaS is having its own coming-of-age story. It's just not landing the way the writers intended.
1) It's not always as bad as it looks
In this scenario there's a big difference between Enterprise Value and Equity Value
Enterprise Value is the value of the standalone business, meaning it's tech, team, and customers
That's what Bending Spoons is buying for $1.285B
And companies are bought on a cashless, debtless basis
Which means Bending Spoons does not get the net cash and cash equivalents on the balance sheet, which clocks in at $965M at time of acquisition
The remaining cash gets distributed to equity shareholders, increasing the share price above and beyond the Enterprise Value
That means the numerator for equity holders is around $2.25B, which changes the multiple math and return profile from their end.
But at the same time…
2) What you raise at is not the same thing as what you sell for
When you raise money you are selling 10%, maybe 20% of the company
The investors at that point in time are coming at it from the perspective of "what can go right"
On the other hand, when you go to sell a company you are selling… well, the whole thing
That takes an entirely different approach to risk, opportunity, and upside
The acquirers are thinking about what can go right, but mostly thinking about "what could go wrong"
That calls for a much more contemplated price
And they took it anyway…
3) Selling with that much cash is a sign
They didn't need to sell to stay alive
The company reached profitability in late 2024 after a series of restructurings
In many ways it feels like punting on third down when you sell with so much cash on the balance sheet
It's a sign they didn't have any bullets left in the chamber to reaccelerate growth and thought the valuation would only go down from here
Or did they?
4) They kept the AI unit
Right before the deal went down they carved out an AI unit
So the legacy business is sold off and they keep the new, relatively unproven AI assets to try to do something cool with them
So does that mean the founders and investors thought the legacy business was going to eventually go to zero?
Which reminds me…
5) The garbage truck only smells when it stops moving
Is this a good acquisition by Bending Spoons?
IDK, but more importantly, it's an acquisition, and they need to keep doing acquisitions to keep the wheels turning
Their entire business model is predicated on doing acquisitions
Despite the fact that the majority of M&A transactions actually destroy value
As homie Upton Sinclair once said: "It is difficult to get a man to understand something, when his salary depends on his not understanding it."
And now…
6) A lot of employees are about to learn how a pref stack works
Assuming all investors had a 1x liquidation multiple, they at least get their investment back
And they get paid FIRST
Paul at 20vc did some back of the envelope math and thinks it will be a round trip exercise (sans the interest) for investors from the C, D, E, and F rounds

Source: Paul at 20vc
To say that again - no one after March 2018 "made" money
Which includes employees… if you are an employee who joined post Series C, the only money you made above and beyond your salary is from secondary sales
Which makes me think…
7) Pre IPO rounds are a dying breed for both investors and employees
How many VCs raised money off their paper markups on Airtable?
In fact, given it's been nearly a decade, some VCs may have raised TWO funds off the floor Airtable's multiple of money valuation presented
As far as tech workers go, post Series C used to be a great time to join - proven product market fit, investor credibility, cash in the bank and a decent salary with equity upside
That mid ground (not too risky, but also still some meat on the bone) feels dead as a doornail
For investors and employees, cometh early, or cometh post IPO
8) Fish are released to the wild
On the bright side, moves like this unlock a bunch of "dormant" talent stuck at late stage SaaS companies with no credible path of going public
Everyday the founders and employees kept chipping away at Airtable, a clear candidate to be gut punched by AI, was another day they were not working on AI to gut punch someone else
Sometimes we need parts of the rainforest to burn down to make space for light to shine through the canopy and nourish new businesses and ideas
Still…
9) Building an enduring company of scale is really, really hard
Anyone who wants to dunk on this outcome has no idea how hard it is to build anything worth over a BILLION dollars
While this is below their expected outcome given their prior funding rounds, they still created more than a billion dollars in value for equity holders (the math is up in lesson one)
This is not how the writers (investors, founders, and employees) intended for the story to end
This is not how "they drew it up"
And the ending is juxtaposed to the fact that the company has a ton of customer love, 500,000 organizations using the product, was still growing double digits, and close to half a billion in revenue.
These are all amazing characteristics if you strip out the funding dynamics
And yet… despite a shitty plot, this is not the only version of this show we're going to get
10) There will be sequels
Anyone who received Series C or D or E funding in 2019 / 2020 timeframe is a candidate for a Nightman Cometh sequel
Investors are tired of waiting for a return.
Many would rather just get swallow their 1x liq pref and move on.
The dam has broken, and they can save face if there's a wave of others accepting a similar faith (a broad industry based mea culpa of sorts)
The same goes for employees who are even more tired.
Imagine sticking it out through two, three, even four rounds of layoffs? Working on something for six, seven, eight years on something with negative compounding equity value?
It's time to get the show on the road
The Nightman Cometh and it's always darkest before the dawn.

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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
















