Templates promise a shortcut. Then you spend three hours bending your actual business into someone else's boxes and rows. Congrats, you've saved like zero time!
Abacum's new AI Spaces skips that bad trade. Prompt it, or pick a starting point - either way you get a full board-ready dashboard or planning workspace in minutes, built on your model. Your variables. Your versions. Your dimensions. Not a generic template you then have to rewire.
It's not just about doing things "faster." (Although it is nice to not let formatting eat your afternoon.) It’s so when the board asks for a new cut on the spot, you're spending your time on the variance story and the recommendation.
That's the job they're actually paying you for.
Masking Your Metrics
I was helping my daughter make these paper masks over the weekend.
They’re a replica of something you’d see at a Catalan ball (not the Catalina wine mixer, which is more my speed).
She likes to trace them on construction paper, poke holes for the eyes, and bedazzle them with sticker jewels.

By the sixth one I noticed she had stopped using the original mask outline, which had the sharpest curves and most symmetrical measurements, and was now using whatever mask she’d just finished.
While they were all technically masks, with each iteration the contours drifted further and further from the original shape.
What was once a sleek Victorian era mask with pronounced curves was now a set of wide rimmed ski googles. Or something you’d wear to rob a bank.

Gimme all the money in the register. No dye packs.
The ground truth beneath her replica drifted.
In many ways this is what we see happen when companies communicate the progress of their business. They drift away from the metrics they are actually using to run the company internally, opting for a set of proxy metrics they think smart people who hold their stock want to hear.
And it’s not just a public company problem. I’ve been guilty of doing this when presenting to my board (and even my boss internally) at private companies.
You feel the pull of a narrative that looks sexier with a slightly upgraded set of characters. You stop talking about customer activations on a quarterly cohorted basis (which is what the sales team is comp’d on) and begin publicly pontificating on enterprise customers above a certain dollar threshold (where you have only two reps working).
Aurelien Nolf, CFO of Navan and former SVP of IR at Lyft reinforced my observation:
If you don’t drive a metric, at some point it’s going to derail. It’s going to go in a direction you don’t want.
And then you will have to explain, and backtrack.
Or even worse, you have to make unnatural choices in the business so that the metric goes back in the right direction. But it’s not something good for your business.
For a while, maybe a couple of quarters, companies can get away with kinda sorta hiding the ball. But eventually whatever they are using as a proxy shifts out from where the business really sits.
A proxy, in my simple mind, means a “stand in” or “representative” for someone or something else. In this case, the metric is a representative for an underlying theme in the business - like keeping customers happy… or expanding wallet share… or making sure employees like working for you.
So it’s very important that the management team aligns on the metrics they’ll disclose externally. Because those metrics will go south at some point… as there’s no such thing as a business without an issue.
All good finance leaders will need to communicate bad news. And what’s important is less how you say it on the day of the bad news but in all the quarters before, educating people on your business and bringing them along for the ride. If investors can understand why things can go wrong in your business, then when that thing happens they won’t be as surprised.
And more importantly everyone knows what the team is doing to fix it.
“At Lyft we had great quarters and not so great quarters. It’s a journey.
I think what we did very successfully is helping people understand what’s driving the business, what’s driving growth, what’s driving profitability.
So when something was derailing a little bit at least we could have candid conversations on how we were going to fix it”
BTW - people really hate surprises when it comes to their money. Investors have unlimited options as to where they deploy it. If they are going to select your company, whether it’s in the private or public markets, they want to understand what the risks and opportunities are, which means they need the right metrics to inform their world view so they’re brought along on that journey.
This type of transparent and aligned communication around metrics allows them to understand your business model so they can believe that whatever went wrong is fixable (or on the positive side, whatever is going right will keep going right).
But if they don’t have the right handles to understand what’s in the black box, then they’ll make up their own narrative… And it’s human nature - if you don’t give someone the tools to figure it out, they’ll make up their own narrative in their head, which is rarely a generous interpretation.
While you want your business to look as good as possible, resist the urge to put a mask on it.
Ask yourself this week:
Do we talk about any metrics externally that don’t show up as much internally?
Do we put more emphasis than we should on certain numbers when telling our company story?
Can we clearly explain how to influence the metrics we talk about if we don’t like the answer?
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















