Career Development: What It Really Means to be a Manager, Director, or VP. The number two post of 2018 was actually written in 2015! That says a lot about this very special post which appears to have simply nailed it in capturing the hard-to-describe but incredibly important differences between operating at the manager, director, or VP level. I must admit I love this post, too, because it was literally twenty years in the making. I’d been asked so many times “what does it really mean to operate at the director level” that it was cathartic when I finally found the words to express the answer.
The SaaS Rule of 40. No surprise here. Love it or not, understanding the rule of 40 is critical when running a SaaS business. Plenty of companies don’t obey the rule of 40 — it’s a very high bar. And it’s not appropriate in all circumstances. But something like 80% of public company SaaS market capitalization is captured by the companies that adhere to it. It’s the PEG ratio of modern SaaS.
The Role of Professional Services in a SaaS Company. I was surprised and happy to see that this post made the top five. In short, the mission of services in a SaaS company is “to maximize ARR while not losing money.” SaaS companies don’t need the 25-35% services margins of their on-premises counterparts. They need happy, renewing customers. Far better to forgo modest profits on services in favor of subsidizing ARR both in new customer acquisition and in existing customer success to drive renewals. Services are critical in a SaaS company, but you shouldn’t measure them by services margins.
The Customer Acquisition Cost Ratio: Another Subtle SaaS Metric. The number five post of 2018 actually dates back to 2013! The post covers all the basics of measuring your cost to acquire a customer or a $1 of ARR. In 2019 I intend to update my fundamentals posts on CAC and churn, but until then, this post stands strong in providing a comprehensive view of the CAC ratio and how to calculate it. Most SaaS companies lose money on customer acquisition (i.e., “sell dollars for 80 cents”) which in turn begs two critical questions: how much do they lose and how quickly do they get it back? I’m happy to see a “fun with fundamentals” type post still running in the top five.
 See disclaimer that I’m not a financial analyst and I don’t make buy/sell recommendations.
I preferred Silicon Valley  back in the day when companies raised modest amounts of capital (e.g., $30M) prior to an IPO that took 4-6 years from inception, where burn rates of $10M/year looked high, and where $100M raise was the IPO, not one or more rounds prior to it. When cap tables had 1x, non-participating preferred and that all converted to a single class of common stock in the IPO. 
These days, companies increasingly raise $200M to $300M prior to an IPO that takes 10-12 years from inception, the burn might look more like $10M/quarter than $10M/year, the cap table loaded up with “structure” (e.g., ratcheting, multiple liquidation preferences). And at IPO time you might end up with two classes common stock, one for the founder with super-voting rights, and one for everybody else.
I think these changes are in general bad:
Employees get more diluted, can end up alternative minimum tax (AMT) prisoners unable to leave jobs they may be unhappy doing, have options they are restricted from selling entirely or are sold into opaque secondary markets with high legal and transaction fees, and/or even face option expiration at 10 years. (I paid a $2,500 “administrative fee” plus thousands in legal fees to sell shares in one startup in a private transaction.)
John Q. Public is unable to buy technology companies at $30M in revenue and with a commission of $20/trade. Instead they either have to wait until $100 to $200M in revenue or buy in opaque secondary markets with limited information and high fees.
Governance can be weak, particularly in cases where a founder exercises directly (or via a nuclear option) total control over a company.
Moreover, the Silicon Valley game changes from “who’s smartest and does the best job serving customers” on relatively equivalent funding to “who can raise the most capital, generate the most hype, and buy the most customers.” In the old game, the customers decide the winners; in the new one, Sand Hill Road tries to, picking them in a somewhat self-fulfilling prophecy.
The Hype Factor
In terms of hype, one metric I use is what I call the hype ratio = VC / ARR. On the theory that SaaS startups input venture capital (VC) and output two things — annual recurring revenue (ARR) and hype — by analogy, heat and light, this is a good way to measure how efficiently they generate ARR.
The higher the ratio, the more light and the less heat. For example, Adaptive Insights raised $175M and did $106M in revenue  in the most recent fiscal year, for a ratio of 1.6. Zuora raised $250M to get $138M in ARR, for a ratio of 1.8. Avalara raised $340M to $213M in revenue, for a ratio of 1.6.
By comparison, Domo’s hype ratio is 6.4. Put the other way, Domo converts VC into ARR at a 15% rate. The other 85% is, per my theory, hype. You give them $1 and you get $0.15 of heat, and $0.85 of light. It’s one of the most hyped companies I’ve ever seen.
As I often say, behind every “marketing genius” is a giant budget, and Domo is no exception .
Sometimes things go awry despite the most blue-blooded of investors and the greenest of venture money. Even with funding from the likes of NEA and Lightspeed, Tintri ended up a down-round IPO of last resort and now appears to be singing its swan song. In the EPM space, Tidemark was the poster child for more light than heat and was sold in what was rumored to be fire sale  after raising over $100M in venture capital and having turned that into what was supposedly less than $10M in ARR, an implied hype ratio of over 10.
The Top-Level View on Domo
Let’s come back and look at the company. Roughly speaking , Domo:
Created a circa $100M business, growing at 45% (and decelerating).
Burns about $150M per year in operating cash flow.
Will have a two-class common stock system where class A shares have 40x the voting rights of class B, with class A totally controlled by the founder. That is, weak governance.
Oh, and we’ve got a highly unprofitable, venture-backed startup using a private jet for a bit less than $1M year . Did I mention that it’s leased back from the founder? Or the $300K in catering from a company owned by the founder and his brother. (Can’t you order lunch from a non-related party?)
As one friend put it, “the Domo S-1 is everything that’s wrong with Silicon Valley in one place: huge losses, weak governance, and now modest growth.”
Personally, I view Domo as the Kardashians of business intelligence – famous for being famous. While the S-1 says they have 85 issued patents (and 45 applications in process), does anyone know what they actually do or what their technology advantage is? I’ve worked in and around BI for nearly two decades – and I have no idea.
Maybe this picture will help.
Uh, not so much.
The company itself admits the current financial situation is unsustainable.
If other equity or debt financing is not available by August 2018, management will then begin to implement plans to significantly reduce operating expenses. These plans primarily consist of significant reductions to marketing costs, including reducing the size and scope of our annual user conference, lowering hiring goals and reducing or eliminating certain discretionary spending as necessary
A Top-to-Bottom Skim of the S-1
So, with that as an introduction, let’s do a quick dig through the S-1, starting with the income statement:
G&A expense of 29% of revenue, not even efficient there.
Operating margin of -162%, huge.
$803M accumulated deficit. Stop, read that number again and then continue.
Decelerating revenue growth, 45% year over year, but only 32% Q1 over Q1.
Cashflow from operations around -$150M/year for the past two years. Stunning.
38% of customers did multi-year contracts during FY18. Up from prior year.
Don’t see any classical SaaS unit economics, though they do a 2016 cohort analysis arguing contribution margin from that cohort of -196%, 52%, 56% over the past 3 years. Seems to imply a CAC ratio of nearly 4, twice what is normally considered on the high side.
Cumulative R&D investment from inception of $333.9M in the platform.
82% revenues from USA in FY18.
1,500 customers, with 385 having revenues of $1B+.
Believe they are <4% penetrated into existing customers, based on Domo users / total headcount of top 20 penetrated customers.
14% of revenue from top 20 customers.
Three-year retention rate of 186% in enterprise customers (see below). Very good.
Three-year retention rate of 59% in non-enterprise customers. Horrific. Pay a huge CAC to buy a melting ice cube. (Only the 1-year cohort is more than 100%.)
As of January 31, 2018, for the cohort of enterprise customers that licensed our product in the fiscal year ended January 31, 2015, the current ACV is 186% of the original license value, compared to 129% and 160% for the cohorts of enterprise customers that subscribed to our platform in the fiscal years ended January 31, 2016 and 2017, respectively. For the cohort of non-enterprise customers that licensed our product in the fiscal year ended January 31, 2015, the current ACV as of January 31, 2018 was 59% of the original license value, compared to 86% and 111% for the cohorts of non-enterprise customers that subscribed to our platform in the fiscal years ended January 31, 2016 and 2017, respectively.
$12.4M in churn ARR in FY18 which strikes me as quite high coming off subscription revenues of $58.6M in the prior year (21%). See below.
Our gross subscription dollars churned is equal to the amount of subscription revenue we lost in the current period from the cohort of customers who generated subscription revenue in the prior year period. In the fiscal year ended January 31, 2018, we lost $12.4 million of subscription revenue generated by the cohort in the prior year period, $5.0 million of which was lost from our cohort of enterprise customers and $7.4 million of which was lost from our cohort of non-enterprise customers.
What appears to be reasonable revenue retention rates in the 105% to 110% range overall. Doesn’t seem to foot to the churn figure about. See below:
For our enterprise customers, our quarterly subscription net revenue retention rate was 108%, 122%, 116%, 122% and 115% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively. For our non-enterprise customers, our quarterly subscription net revenue retention rate was 95%, 95%, 99%, 102% and 98% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively. For all customers, our quarterly subscription net revenue retention rate was 101%, 107%, 107%, 111% and 105% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively.
Another fun quote and, well, they did take about the cash it takes to build seven startups.
Historically, given building Domo was like building seven start-ups in one, we had to make significant investments in research and development to build a platform that powers a business and provides enterprises with features and functionality that they require.
Most customers invoiced on annual basis.
Quarterly income statements, below.
$72M in cash as of 4/30/18, about 6 months worth at current burn.
$71M in “backlog,” multi-year contractual commitments, not prepaid and ergo not in deferred revenue. Of that $41M not expected to be invoiced in FY19.
Business description, below. Everything a VC could want in one paragraph.
Domo is an operating system that powers a business, enabling all employees to access real-time data and insights and take action from their smartphone. We believe digitally connected companies will increasingly be best positioned to manage their business by leveraging artificial intelligence, machine learning, correlations, alerts and indices. We bring massive amounts of data from all departments of a business together to empower employees with real-time data insights, accessible on any device, that invite action. Accordingly, Domo enables CEOs to manage their entire company from their phone, including one Fortune 50 CEO who logs into Domo almost every day and over 10 times on some days.
Let’s see if a computer could read it any better than I could. Not really.
They even have Mr. Roboto to help with data analysis.
Through Mr. Roboto, which leverages machine learning algorithms, artificial intelligence and predictive analytics, Domo creates alerts, detects anomalies, optimizes queries, and suggests areas of interest to help people focus on what matters most. We are also developing additional artificial intelligence capabilities to enable users to develop benchmarks and indexes based on data in the Domo platform, as well as automatic write back to other systems.
796 employees as of 4/30/18, of which 698 are in the USA.
Cash comp of $525K for CEO, $450K for CFO, and $800K for chief product officer
Pre-offering it looks like founder Josh James owns 48.9M shares of class A and 8.9M shares of class B, or about 30% of the shares. With the 40x voting rights, he has 91.7% of the voting power.
Does the Emperor Have Any Clothes?
One thing is clear. Domo is not “hot” because they have some huge business blossoming out from underneath them. They are “hot” because they have raised and spent an enormous amount of money to get on your radar.
Will they pull off they IPO? There’s a lot not to like: the huge losses, the relatively slow growth, the non-enterprise retention rates, the presumably high CAC, the $12M in FY18 churn, and the 40x voting rights, just for starters.
However, on the flip side, they’ve got a proven charismatic entrepreneur / founder in Josh James, an argument about their enterprise customer success, growth, and penetration (which I’ve not had time to crunch the numbers on), and an overall story that has worked very well with investors thus far.
While the Emperor’s definitely not fully dressed, he’s not quite naked either. I’d say the Domo Emperor’s donning a Speedo — and will somehow probably pull off the IPO parade.
 Yes, I know they’re in Utah, but this is still about Silicon Valley culture and investors.
 I’ll use revenue rather than trying to get implied ARR to keep the math simple. In a more perfect world, I’d use ARR itself and/or impute it. I’d also correct for debt and a cash, but I don’t have any MBAs working for me to do that, so we’ll keep it back of the envelope.
 You can argue that part of the “genius” is allocating the budget, and it probably is. Sometimes that money is well spent cultivating a great image of a company people want to buy from and work at (e.g., Salesforce). Sometimes, it all goes up in smoke.
 I am not a financial analyst, I do not give buy/sell guidance, and I do not have a staff working with me to ensure I don’t make transcription or other errors in quickly analyzing a long and complex document. Readers are encouraged to go the S-1 directly. Like my wife, I assume that my conclusions are not always correct; readers are encouraged to draw their own conclusions. See my FAQ for complete disclaimer.
 $900K, $700K, and $800K run-rate for FY17, FY18, and 1Q19 respectively.
While I credited Domo with creating a huge hype bubble through secrecy and mystery, big events, and raising tremendous amounts of money (yet again today) at unicorn valuations — I also questioned how much (as Gertrude Stein said of Oakland) “there there” Domo has when it comes to the company and its products.
Specifically, I began to wonder how to quantify the hype around a company. Let’s say that, as organisms, SaaS companies convert venture capital into two things: annual recurring revenue (ARR) and hype. ARR has direct value as every year it turns into GAAP revenue. Hype has value to the extent it creates halo effects that drive interest in the company that ultimately increase ARR. 
Hype Factor = Capital Raised / Annual Recurring Revenue
Now, unlike some bloggers, I don’t have any freshly minted MBAs doing my legwork, so I’m going to need to do some very back of the envelop analysis here.
Looking at some recent JMP research, I can see that the average SaaS company goes public at around $25M/quarter in revenue, a $100M annual run-rate, and which also suggests an ARR base of around $100M.
Looking at this post by Tomasz Tunguz, I can see that the average SaaS company has raised about $100M if you include everyone or $68M if you exclude companies that I don’t really consider enterprise software.
So, back of the envelope, this suggests that 1.5 (=100/68) is a typical capital-to-ARR ratio on the eve of an IPO. Let’s look at some specific companies for more (all figures are approx as I’m eye-balling off charts in some cases and looking at S-1s in others) :
NetSuite: raised $125M, run-rate at IPO $92M –> 1.3
Cornerstone: raised $41M, run-rate $44M –> 1.0
Box: raised $430M, run-rate $228M –> 1.8
Xactly: raised $83M, run-rate $50M –> 1.7
Workday: raised $200M, run-rate $168M –> 1.2
There are numerous limitations to this analysis.
I do not make any effort to take into account either how much VC was left over on the eve of the IPO or how much debt the company had raised.
Capital consumption per category may vary as a function of the category as a CFO friend of mine reminded me today.
Some companies don’t break out subscription and services revenue and the ARR run-rate calculations should only apply to subscription.
Since private companies raise capital and burn it down until an IPO, you should expect that the above values represent minima from a lifecycle perspective. (In theory, you’d arrive on IPO day broke, having raised no more cash than you needed to get there.)
So I’m going to rather subjectively assign some buckets based on this data and my own estimates about earlier stages.
A hype factor of 1-2 is target
A hype factor of 2-3 is good, particularly well before an IPO
A hype factor of 3-5 is not good, too much hype and too little ARR
A hype factor of 5+ suggests there is very little “there there” at all.
I know of at least one analytics company where I suspect the hype factor is around 10. If I had to take a swag at Domo’s hype factor based on the comments in this interview:
Quote from the article: “contracted revenue is $100M.” Hopefully this means ARR and not TCV.
Capital raised: $613M per Crunchbase, including today’s round.
This suggests Domo’s hype factor is 6.1 including today’s capital and 4.8 excluding it. So if you’ve heard of Domo, think they are cool, are wowed by the speakers and rappers at Domopalooza, you should be. As I like to say: behind every marketing genius, there is usually a massive budget. 
Domo’s spending heavily, that’s for sure. How efficient they are at converting that spending to ARR remains to be seen. My instinct, and this rough math, says they are more efficient at generating hype than revenue. 
Time will tell. Gosh, life was simpler (if less interesting) when companies went public at $30M.
# # #
 In a sense, I’m arguing that hype takes two forms: good hype that drives ARR and wasted hype that simply makes the company, like the Kardashians, famous for being famous.
 And having some trouble making the different data sources foot. For example, the SFSF S-1 indicates $45M in convertible preferred stock, but the Tunguz post suggests $70M. Where’s my freshly minted MBA to help?
 You can argue that the first step in marketing genius is committing to spend large amounts of money and I won’t debate you. But I do think many people completely overlook the massive spend behind many marketing geniuses and, from a hype factor perspective, forget that the purpose of all that genius is not to impress TechCrunch and turn B2B brands into household words, but to win customers and drive ARR.
 Note that Domo says they have $200M in the bank unspent which, if true, both skews this analysis and prompts the question: why raise more money at a flat valuation in smaller quantity when you don’t need it? While my formula deliberately does not take cash or debt into account (because it’s hard enough to just triangulate on ARR at private companies), if you want to factor that claim into the math, I think you’d end up with a hype factor of 3-4. (You can’t exclude all the cash because every startup keeps cash on hand to fund them through to their next round.)
There are two sayings I like when it comes to the unicorn bubble:
“Too much money makes you stupid”
“Any idea’s a good one when you’ve got $100M burning a hole in your pocket.”
Startups are supposed to be focused. Startups are supposed to need to prioritize ideas and opportunities. Just as startups weren’t supposed to buy Superbowl ads, startups aren’t supposed to have hundreds of millions of dollars to plow through in the name of creating brand mystique either via huge-budget events like Domo’sDomopalooza or would-be viral videos, like the one below.
But wait, you protest, didn’t Salesforce always do aggressive marketing and wasn’t that risk-taking part of their greatness? Well, yes and no. A good part of their early marketing was guerrilla PR done on the cheap. Yes, they also ran big events, but they mostly found a way to pay for them — Salesforce raised $53M in VC before going public. Domo has raised nearly 10x that.
Now, I have no particular beef with Domo. Other than being next-generation BI, I must admit to always having had some trouble figuring out what they do — in part due to the abnormal secrecy they had in their early days. I know they don’t compete with Host Analytics so I have no beef there. I also know they have sexed-up the BI category a bit, and they’ve certainly done a great job of positioning themselves as a cool company and have created a lot of buzz in the market.
But at what cost?
Domo has raised $483M. It does cause one to wonder about their capital-to-ARR ratio, which is a great overall capital efficiency metric and one that no ever seems to talk about.
While I don’t know in Domo’s case, I’d guess for many unicorns that this ratio is 10 to 20x — where the company is running a kind of perpetual motion machine strategy where you generate the Halo Effects hoping to drive the sales that justify the valuation that you got on your last financing. This strategy, as many will discover, works well until it doesn’t. If the epitaph of Bubble 1.0 was about Network Effects, that of Bubble 2.0 will be about Halo Effects. Remember Warren Buffet’s famous quote: “only when the tide goes out can you see who’s swimming naked.”
I know for a reasonably capital-efficient SaaS business the capital-to-ARR ratio might be 2-3x. Perhaps an order of magnitude difference.
Back to our core topic — what’s an example of something that looks like a good idea when you have $483M burning a hole in your pocket that, well, might not look like such a good idea if you were forced to lead a more frugal marketing existence?
How about a YouTube mini-series with Alec Baldwin? That’s exactly what Domo did.
I’m Dave Kellogg, advisor, director, consultant, angel investor, and blogger focused on enterprise software startups. I am an executive-in-residence (EIR) at Balderton Capital and principal of my own eponymous consulting business.
I bring an uncommon perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.
From 2012 to 2018, I was CEO of cloud EPM vendor Host Analytics, where we quintupled ARR while halving customer acquisition costs in a competitive market, ultimately selling the company in a private equity transaction.
Previously, I was SVP/GM of the $500M Service Cloud business at Salesforce; CEO of NoSQL database provider MarkLogic, which we grew from zero to $80M over 6 years; and CMO at Business Objects for nearly a decade as we grew from $30M to over $1B in revenues. I started my career in technical and product marketing positions at Ingres and Versant.
I love disruption, startups, and Silicon Valley and have had the pleasure of working in varied capacities with companies including Bluecore, FloQast, GainSight, Hex, MongoDB, Pigment, Recorded Future, and Tableau.
I currently serve on the boards of Cyber Guru (cybersecurity training), Jiminny (conversation intelligence), and Scoro (work management).
I previously served on the boards of Alation (data intelligence), Aster Data (big data), Granular (agtech), Nuxeo (content services), Profisee (MDM), and SMA Technologies (workload automation).
I periodically speak to strategy and entrepreneurship classes at the Haas School of Business (UC Berkeley) and Hautes Études Commerciales de Paris (HEC).