The tech FOMO bubble has officially burst
Or why private tech companies are letting go thousands of employees
Private and public markets are taking a beating. We’ve all seen the headlines—cuts at Amazon, Meta, Twitter, Salesforce, and elsewhere have dominated headlines now for months.
But it’s not just tech giants experiencing slow growth and cutting headcount. Private software companies are reacting to challenging market conditions by reducing the size of their workforce. We’re halfway through January, and layoffs are flying fast and furious.
Where did we go wrong?
Investors couldn’t see the party stopping.
In the heady investment boom of 2021, the markets were flush with cash—partly due to cash payments to Americans for COVID relief and major checks cut to businesses as PPP loans. We’d managed to push on through the shock of COVID and keep valuations high—too high. It felt like we were minting a new billion-dollar tech unicorn every other day. The Federal Reserve had interest rates at a historic low, and everyone had access to capital. We were in the midst of a nearly 15-year bull market.
Then the checks stopped flowing out, the cost of goods inflated, and the Fed hiked interest rates.
The music stopped, and quickly.
No more growth at all costs
If you’re a private software as a service (SaaS) business, your job is to grow quickly. If you talk to venture capitalists, they’ll tell you that a successful SaaS business selling to other businesses (B2B) should triple its annual reoccurring revenue (ARR) in one year, triple again the next, then double, and double again.
Here’s what that looks like for a company that starts with $1M in yearly revenue and some initial product-market fit:
Year 1: $1M x 3 = $3 million ARR
Year 2: $3 million x 3 = $9 million ARR
Year 3: $9 million x 2 = $18 million ARR
Year 4: $18 million x 2 = $36 million ARR
By the end of year 4, they expect that company to have at least grown 36x. To do that, companies were burning through cash and hiring rapidly.
But were they doing that efficiently?
The new (old) metrics that matter
The open secret to hypergrowth is that these companies usually aren’t profitable. They’re fueled by venture capital dollars with a growth-at-all-costs mindset, and too many companies grow inefficiently while trying to capture market share. The rationale is that with reoccurring revenue models, if you own enough of a market and can retain your customers (ie, make your product sticky), you’ll make lots of money in the long run.
Now, investors see choppy economic waters continuing for months, if not years. Consumers are tightening their wallets, with a cascade of revenue impacts across businesses. It’s getting a lot harder to sell software to other businesses—and to retain the customers you just spent so much acquiring.
With revenue and growth dipping, venture capitalists—who form the boards of these startups while they’re private—start looking more closely at efficiency metrics.
They ask:
What’s your Customer Acquisition Cost (CAC) & CAC payback period?
What’s your revenue churn rate?
What’s your sales efficiency?
What’s your monthly cash burn?
CAC & CAC Payback
CAC = Total $ spent on sales & marketing over a period / the number of customer acquired within period
CAC measures the amount you spend on sales, marketing, and other associated costs to acquire a new customer. Flush with cash; many SaaS companies had been relying on high CAC spending, with the expectation that the lifetime value of the customer was worth it—and the assumption that they’d be able to raise more money at a good valuation to continue to fuel growth.
The second important dimension of CAC is the payback period. With B2B businesses, it will often take months to years to return the cost of acquiring their customers. The faster your business recovers CAC, the faster it can reinvest in acquiring more customers and continue to seize market share. The lower your CAC payback period, the more excited investors likely are—sub 12 months is considered especially strong as most B2B contracts are annual at least. But if 30%+ of your customers only stay a year and your CAC payback period is longer than 15 months (considered solid), you’ve got a problem.
Revenue Churn rate
Churn rate = (# of churned customers in a period ÷ total # of customers to start period) × 100
A crucial part of understanding if your company’s CAC and CAC payback period are acceptable to investors is your churn rate—both logo churn (ie, the number of customers/accounts leaving your service as a percentage of your overall customer count) and revenue churn (the amount of money leaving your revenue stream each month as a percentage of overall revenue).
In the current cost-cutting and efficiency environment, technology costs, particularly reoccurring subscriptions, are on the chopping block along with employee salaries. Hence many SaaS companies have seen churn rates increase, and their CAC payback period suddenly looks unsustainable. With pressure to cut costs and to cut CAC, companies cut headcounts.
The next year will be a proving ground—companies that can’t lower their CAC & churn rate may not survive the next year—or will be acquired by larger cash-rich companies.
It’s also important to understand that the monthly churn rate will compound over time, creating worsening problems. Sure, your 2% monthly revenue churn rate doesn’t seem like a lot, but annualized, that’s nearly 25% of your revenue that needs to be replaced by new growth just to maintain the same revenue figures—and for companies still looking to raise more money by hitting that next 2x growth year, that just creates a steeper hill to climb.
Sales Efficiency, aka the Magic Number
Sales Efficiency = amount of new revenue generated for every dollar invested in sales and marketing over the prior period
The ‘Magic Number’ or Sales Efficiency—is here to tell you how efficiently your company is gathering value by comparing the revenue you accrue over a given period to the sales + marketing spend over that period. It’s a crucial indicator of your overall company efficiency.
In the Scale Studio dataset of 1,000+ growth-stage SaaS and cloud businesses, the long-term median Sales Efficiency hoovers around 0.7.* That means that a typical SaaS startup generates $0.70 in new ARR for every $1.00 it spends on Sales & Marketing.
Occasionally, you’ll see companies with incredible efficiency models and execution that go above the number 1 in sales efficiency—these are the kind of companies that investors are beating down the doors of. They’re rare and have unique value propositions in their go-to-market model.
What happens if investors don’t like these numbers?
The short answer is reductions in workforce aka layoffs. The longer answer is that cash burn (operating cashflow less capital expenditure) is crucial context to the above metrics and that companies with high rates of cash burn look to reduce those by cutting expenses—of which salaries are generally the largest.
It’s also important to remember that this cost-cutting is part of why B2B companies are seeing increasing churn rates as companies look to cut technology costs. The companies doing the most cuts are generally those that faced the most investor pressure to grow rapidly during prior years—and built unsustainable headcount models with the expectation of low customer churn and another round of funding just around the corner.
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Dive deeper into SaaS and engineering metrics
For a broader look at SaaS metrics than what I have above, check out David Sacks & Ethan Ruby’s seminal post on SaaS KPIs.
I also interviewed Laura Tacho, VP of Engineering and Leadership Coach on the Dev Interrupted Podcast, about what metrics engineering leaders need to understand 👇
What else I’m paying attention to
A thought-provoking look at Big Tech and how they bring in revenue by Peter Yang, who also writes a great newsletter on the creator economy A couple of observations:
Microsoft has an intriguing position if they can complete a purchase of 49% of OpenAI and use it to enhance their diverse product revenue streams
Google has to be highly wary, given it’s reliance on Search and the potential Bing + ChatGPT integration
Pushing major amounts of AI onto Azure would further entrench their position as the #2 in the cloud market or even let them threaten AWS in size
Apple’s hardware/software orientation and incoming VR/AR product line could leave them in a great position to partner with some would-be rivals.
Excited to see the FDA grant Accelerated Approval for Alzheimer’s Disease Treatment Leqembi, which has thus far shown efficacy at combatting one of the scariest threats to tens of millions of families worldwide. Lots more data to come, and the cost of care is a concern, but it’s a great sign to see Alzheimer treatment options improving from essentially none.
I’ve enjoyed TheMoonMidas’s new daily AI bites newsletter, Artificial Genie. Last week’s post on stepping up your Twitter game with AI is an actionable favorite.
Interested to see if the Terra blockchain can continue to climb back from the ashes of last year’s massive collapse. Building a better interchain wallet with Station is a step in the right direction.
New from me
Not every tech company has stopped hiring. Well-capitalized startups, particularly in the AI/ML space, are still hiring to build out our foundations. LinearB, where I work, went from 40 to 95 team members in 2022 and plan to be at 120 at the end of 2023—which Jon Swartz highlighted in Market Watch.
If you’re looking for a new startup job, AI and climate tech are a good bet.
In December, I noted that Dev Interrupted would be doubling down on YouTube. We’ve already seen some traction with shorts, including this one with Google’s Head of Developer Media Forrest Brazeal where he highlights why the phrase “skills gap” is often bull shit.
You can listen to my full interview with Forrest here.
What’s up next?
So I lied to you in my December edition 😅—I’d told you I was going to include some personal goals for 2023 and successes/failures from 2022.
But I got too fired up writing about the changes happening in SaaS, and I’ve kicked the can until the next edition—which will be headed your way next week. You can also expect to see more on what’s happening in AI, crypto, and the markets.
Thanks for reading another edition of Test Lab, and be sure to drop any feedback in the comments (or Tweet it at me).
Cheers,
Conor