Category Archives: Entrepreneurship

A Look at the Tintri S-1

Every now and then I take a dive into an S-1 to see what clears the current, ever-changing bar for going public.  After a somewhat rocky IPO process, Tintri went public June 30 after cutting the IPO offering price and has traded flat thus far since then.

Let’s read an excerpt from this Business Insider story before taking a look at the numbers.

Before going public, Tintri had raised $260 million from venture investors and was valued at $800 million.

With the performance of this IPO, the company is now valued at about about $231 million, based on $7.50 a share and its roughly 31 million outstanding shares, (if the IPO’s bankers don’t buy their optional, additional roughly 1.3 million shares.)

In other words, this IPO killed a good $570 million of the company’s value.

In other words, Tintri looks like a “down-round IPO” (or an “IPO of last resort“) — something that frankly almost never happened before the recent mid/late stage private valuation bubble of the past 4 years.

Let’s look at some numbers.

tintri p+l

Of note:

  • $125M in FY2017 revenue.  (They have scale, but this is not a SaaS company so the revenue is mostly non-recurring, making it easier to get to grow quickly and making the revenue is worth less because only the support/maintenance component of it renews each year.)
  • 45% YoY total revenue growth.  (On the low side, especially given that they have a traditional license/maintenance model and recognize revenue on shipment.)
  • 65% gross margins  (Low, but they do seem to sell flash memory hardware as part of their storage solutions.)
  • 87% of revenue spent on S&M (High, again particularly for a non-SaaS company.)
  • 43% of revenue spent on R&D  (High, but usually seen as a good thing if you view the R&D money as well spent.)
  • -81% operating margins (Low, particularly for a non-SaaS company.)
  • -$70.4M in cashflow from operating activities in 2017 ($17M average quarterly cash burn from operations)
  • Incremental S&M / incremental product revenue = 73%, so they’re buying $1 worth of incremental (YoY) revenue for an incremental 73 cents in S&M.  Expensive but better than some.

Overall, my impression is of an on-premises (and to a lesser extent, hardware) company in SaaS clothing — i.e., Tintri’s metrics look like a SaaS company, but they aren’t so they should look better.  SaaS company metrics typically look worse than traditional software companies for two reasons:  (1) revenue growth is depressed by the need to amortize revenue over the course of the subscription and (2) subscriptions companies are willing to spend more on S&M to acquire a customer because of the recurring nature of a subscription.

Concretely, if you compare two 100-unit customers, the SaaS customer is worth twice the license/maintenance customer over 5 years.

saas compare

Moreover, even if Tintri were a SaaS company, it is quite out of compliance with the Rule of 40, that says growth rate + operating margin >= 40%.  In Tintri’s case, we get -35%, 45% growth plus -81% operating margin, so they’re 75 points off the rule.

Other Notes

  • 1250+ customers
  • 21 of the Fortune 100
  • 527 employees as of 1/31/17
  • CEO 2017 cash compensation $525K
  • CFO 2017 cash compensation $330K
  • Issued special retention stock grants in May 2017 that vest in the two years following an IPO
  • Did option repricing in May 2017 to $2.28/share down from weighted average exercise price of $4.05.
  • $260M in capital raised prior to IPO
  • Loans to CFO and CEO to exercise stock options at 1.6% to 1.9% interest in 2013
  • NEA 22.7% ownership prior to opening
  • Lightspeed 14.5% ownership
  • Insight Venture Partners 20.2% ownership
  • Silver Lake 20.4% ownership
  • CEO 3.8% ownership
  • CFO 0.7% ownership
  • $48.9M in long-term debt
  • $13.8M in 2017 stock-based compensation expense

Overall, and see my disclaimers, but this is one that I’ll be passing on.


The Strategy Compiler: How To Avoid the “Great” Strategy You Couldn’t Execute

Few phrases bother me more than this one:

“I know it didn’t work, but it was a great strategy.  We just didn’t have the resources to execute it.”

Huh.  Wait minute.  If you didn’t have the resources to execute it, then it wasn’t a great strategy.  Maybe it was a great strategy for some other company that could have applied the appropriate resources.  But it wasn’t a great strategy for you.  Ergo, it wasn’t a great strategy.  QED.

I learned my favorite definition of strategy at a Stanford executive program I attended a few years back.  Per Professor Robert Burgelman, author of Strategy is Destiny, strategy is simply “the plan to win.”  Which begets an important conversation about the definition of winning.  In my experience, defining winning is more important than making the plan, because if everyone is focused on taking different hills, any resultant strategy will be a mishmash of plans to support different objectives.

But, regardless of your company’s definition of winning, I can say that any strategy you can’t execute definitionally won’t succeed and is ergo a bad strategy.

It sounds obvious, but nevertheless a lot of companies fall into this trap.  Why?

  • A lack of focus.
  • A failure to “compile” strategy before executing it.

Focus:  Think Small to Grow Big

Big companies that compete in lots of broad markets almost invariably didn’t start out that way.

BusinessObjects started out focused on the Oracle financials installed base.  Facebook started out on Harvard students, then Ivy league students.  Amazon, it’s almost hard to remember at this point, started out in books.  Salesforce started out in SMB salesforce automation.  ServiceNow on IT ticket management.  This list goes on and on.

Despite the evidence and despite the fame Geoffrey Moore earned with Crossing the Chasm, focus just doesn’t come naturally to people.  The “if I could get 1% share of a $10B market, I’d be a $100M company” thought pattern is just far too common. (And investors often accidentally reinforce this.)

The fact is you will be more dominant, harder to dislodge, and probably more profitable if, as a $100M company, you control 30% of a $300M target as opposed to 1% of a $10B target.

So the first reason startups make strategies they can’t execute is because they forget to focus.  They aim too broadly. They sign up for too much.  The forget that strategy should be sequence of actions over time.  Let’s start with Harvard. Then go Ivy League.  Then go Universities in general.  Then go everyone.

Former big company executives often compound the problem.  They’re not used to working with scarce resources and are more accustomed to making “laundry list” strategies that check all the boxes than making focused strategies that achieve victory step by step.

A Failure to Compile Strategy Before Execution

The second reason companies make strategies they can’t execute is that they forget a critical step in the planning process that I call the strategy compiler.  Here’s what I think a good strategic planning process looks like.

  • Strategy offsite. The executive team spends a week offsite focused on situation assessment and strategy.  The output of this meeting should be (1) a list of strategic goals for the company for the following year and (2) a high-level financial model that concretizes what the team is trying to accomplish over the next three years.  (With an eye, at a startup, towards cash.)


  • First round budgeting. Finance issues top-down financial targets.  Executives who own the various objectives make strategic plans for how to attain them.  The output of this phase is (1) first-draft consolidated financials, (2) a set of written strategies along with proposed organizational structures and budgets for attaining each of the company’s ten strategic objectives.


  • Strategy compilation, resources. The team meets for a day to review the consolidated plans and financials. Invariably there are too many objectives, too much operating expense, and too many new hires. The right answer here is to start cutting strategic goals.  The wrong answer is to keep the original set of goals and slash the budget 20% across the board.  It’s better to do 100% of 8 strategic initiatives than do 80% of 10.


  • Strategy compilation, skills. The more subtle assessment that must happen is a sanity check on skills and talent.  Do your organization have the competencies and do your people have the skills to execute the strategic plans?  If a new engineering project requires the skills of 5 founder-level, Stanford computer science PHDs who each would want 5% of a company, you are simply not going to be able to hire that kind of talent as regular employees. (This is one reason companies do “acquihires”).  The output of this phase is a presumably-reduced set of strategic goals.


  • Second round budgeting. Executives to build new or revised plans to support the now-reduced set of strategic goals.


  • Strategy compilation. You run the strategy compiler again on the revised plan — and iterate until the strategic goals match the resources and the skills of the proposed organization.


  • Board socialization. As you start converging via the strategy compiler you need to start working with the board to socialize and eventually sell the proposed operating plan.  (This process could easily be the subject of another post.)


If you view strategy as the plan to win, then successful strategies include only those strategies that your organization can realistically execute from both a resources and skills perspective.  Instead of doing a single-pass process that moves from strategic objectives to budgets, use an iterative approach with a strategy compiler to ensure your strategic code compiles before you try to execute it.

If you do this, you’ll increase your odds of success and decrease the odds ending up in the crowded section of the corporate graveyard where the epitaphs all read:

Here Lies a Company that Had a “Great” Strategy  It Had No Chance of Executing

Blocking the End Run: Eleven Words to Reduce Politics in Your Organization

People are people.  Sometimes they’re conflict averse and just not comfortable saying certain things to their peers.  Sometimes they don’t like them and are actively trying to undermine them. Sometimes they’re in a completely functional relationship, but have been too darn busy to talk.

So when this happens, how do you — as a manager — what should you do?

“Hey Dave, I wanted to say that Sarah’s folks really messed up on the Acme call this morning.  They weren’t ready with the proposal and were completely not in line with my sales team.”

Do you pile on?

“Again?  Sarah’s folks are out of control, I’m going to go blast her.”  (The “Young Dave” response.)

Do you investigate?

“You know my friend Marcy always said there are three sides to every story:  yours, mine, and what actually happened.  So let me give Sarah a call and look into this.”

Do you defend?

“Well, that doesn’t sound like Sarah.  Her team’s usually buttoned up.”

In the first case, you’re going off half-cocked without sufficient information which, while emotionally satisfying in the short-term, often leads to a mess followed by several apologies in the mid-term.  In the second case, you’re being manipulated into investigating something when perhaps you were planning a better use of your time that day.  In the third case, you’re going off half-cocked again, but in the other direction.

In all three cases, you’re getting sucked into politics.  Politics?  Is it really politics?  Well, how do you think Sarah is going to feel in when you show up asking a dozen questions about the Acme call?  She’ll certainly consider it politics and, among other things, there’s about a 98% chance that she will say:

“Gosh, I wish Bill came and talked to me first.”

At which point, if you’re like me, you’re going to say:

“No, no, no.  I know what you’re thinking.  Don’t worry, this isn’t political.  It’s not like Bill was avoiding you on this one.  He just happened to be talking to me about another issue and he brought this up at the end.  It’s not political, no.”

But can you be sure?  Maybe it just did pop into Bill’s mind during the last minute of the other call.  Or maybe it didn’t.  Maybe the reason Bill called you was a masterfully political pretext.  Can you know the difference?

So what do you say to Bill when he drops the comment about Sarah’s team into your call?  The eleven words that reduce politics in any organization:

“What did Sarah say when you talked to her about this?”

[Mike Drop.]

# # #

(Props to Martin Cooke for teaching me the eleven words.)

Why has Standalone Cloud BI been such a Tough Slog?

I remember when I left Business Objects back in 2004 that it was early days in the cloud.  We were using Salesforce internally (and one of their larger customers at the time) so I was familiar with and a proponent of cloud-based applications, but never felt great about BI in the cloud.  Despite that, Business Objects and others were aggressively ramping on-demand offerings all of which amounted to pretty much nothing a few years later.

Startups were launched, too.  Specifically, I remember:

  • Birst, née Success Metrics, and founded in 2004 by Siebel BI veterans Brad Peters and Paul Staelin, which was originally supposed to be vertical industry analytic applications.
  • LucidEra, founded in 2005 by Salesforce and Siebel veteran Ken Rudin (et alia) whose original mission was to be to BI what Salesforce was to CRM.
  • PivotLink, which did their series A in 2007 (but was founded in 1998), positioned as on-demand BI and later moved into more vertically focused apps in retail.
  • GoodData, founded in 2007 by serial entrepreneur Roman Stanek, which early on focused on SaaS embedded BI and later moved to more of a high-end enterprise positioning.

These were great people — Brad, Ken, Roman, and others were brilliant, well educated veterans who knew the software business and their market space.

These were great investors — names like Andreessen Horowitz, Benchmark, Emergence, Matrix, Sequoia, StarVest, and Tenaya invested over $300M in those four companies alone.

This was theoretically a great, straightforward cloud-transformation play of a $10B+ market, a la Siebel to Salesforce.

But of the four companies named above only GoodData is doing well and still in the fight (with a high-end enterprise platform strategy that bears little resemblance to a straight cloud transformation play) and the three others all came to uneventful exits:

So, what the hell happened?

Meantime, recall that Tableau, founded in 2003, and armed in its early years with a measly $15M in venture capital, and with an exclusively on-premises business model, literally blew by all the cloud BI vendors, going public in May 2013 and despite the stock being cut by more than half since its July 2015 peak is still worth $4.2B today.

I can’t claim to have the definitive answer to the question I’ve posed in the title.  In the early days I thought it was related to technical issues like trust/security, trust/scale, and the complexities of cloud-based data integration.  But those aren’t issues today.  For a while back in the day I thought maybe the cloud was great for applications, but perhaps not for platforms or infrastructure.  While SaaS was the first cloud category to take off, we’ve obviously seen enormous success with both platforms (PaaS) and infrastructure (IaaS) in the cloud, so that can’t be it.

While some analysts lump EPM under BI, cloud-based EPM has not had similar troubles.  At Host, and our top competitors, we have never struggled with focus or positioning and we are all basically running slightly different variations on the standard cloud transformation play.  I’ve always believed that lumping EPM under BI is a mistake because while they use similar technologies, they are sold to different buyers (IT vs. finance) and the value proposition is totally different (tool vs. application).  While there’s plenty of technology in EPM, it is an applications play — you can’t sell it or implement it without domain knowledge in finance, sales, marketing or whatever domain for which you’re building the planning system.  So I’m not troubled to explain why cloud EPM hasn’t been a slog while cloud BI absolutely has been.

My latest belief is that the business model wasn’t the problem in BI.  The technology was.  Cloud transformation plays are all about business model transformation.  On-premises applications business models were badly broken:  the software cost $10s of millions to buy and $10s of millions more to implement (for large customers).  SMBs were often locked out of the market because they couldn’t afford the ante.  ERP and CRM were exposed because of this and the market wanted and needed a business model transformation.

With BI, I believe, the business model just wasn’t the problem.  By comparison to ERP and CRM, it was fraction of the cost to buy and implement.  A modest BusinessObjects license might have cost $150K and less than that to implement.  That problem was not that BI business model was broken, it was that the technology never delivered on the democratization promise that it made.  Despite shouting “BI for the masses” in 1995, BI never really made it beyond the analyst’s desk.

Just as RDBMS themselves failed to deliver information democracy with SQL (which, believe it or not, was part of the original pitch — end users could write SQL to answer their own queries!), BI tools — while they helped enable analysts — largely failed to help Joe User.  They weren’t easy enough to use.  They lacked information discovery.  They lacked, importantly, easy-yet-powerful visualization.

That’s why Tableau, and to a lesser extent Qlik, prospered while the cloud BI vendors struggled.  (It’s also why I find it profoundly ironic that Tableau is now in a massive rush to “go cloud” today.)  It’s also one reason why the world now needs companies like Alation — the information democracy brought by Tableau has turned into information anarchy and companies like Alation help rein that back in (see disclaimers).

So, I think that cloud BI proved to be such a slog because the cloud BI vendors solved the wrong problem. They fixed a business model that wasn’t fundamentally broken, all while missing the ease of use, data discovery, and visualization power that both required the horsepower of on-premises software and solved the real problems the users faced.

I suspect it’s simply another great, if simple, lesson is solving your customer’s problem.

Feel free to weigh in on this one as I know we have a lot of BI experts in the readership.

Do You Want to be Judged on Intentions or Results?

It was early in my career, maybe 8 years in, and I was director of product marketing at a startup.  One day, my peer, the directof of marketing programs hit me with this in an ops review meeting:

You want to be judged on intentions, not results.

I recall being dumbfounded at the time.  Holy cow, I thought.  Is he right?  Am I standing up arguing about mitigating factors and how things might have been when all the other people in the room were thinking only about black-and-white results?

It was one of those rare phrases that really stuck with me because, among other reasons, he was so right.  I wasn’t debating whether things happened or not.  I wasn’t making excuses or being defensive.  But I was very much judging our performance in the theoretical, hermetically sealed context of what might have been.

Kind of like sales saying a deal slipped instead of did not close.   Or marketing saying we got all the MQLs but didn’t get the requisite pipeline.  Or alliances saying that we signed up the 4 new partners, but didn’t get the new opportunities that were supposed to come with them.

Which phrase of the following sentence matters more — the first part or the second?

We did what we were supposed to, but it didn’t have the desired effect.

We would have gotten the 30 MQLS from the event if it hadn’t snowed in Boston.  But who decided to tempt fate by doing a live event in Boston in February?  People who want to be judged on intentions think about the snowstorm; people who want to be judged on results think about the MQLs.

People who want to judged on intentions build in what they see as “reasons” (which others typically see as “excuses”) for results not being achieved.

I’m six months late hiring the PR manager, but that’s because it’s hard to find great PR people right now.  (And you don’t want me to hire a bad one, do you?)

No, I don’t want you to hire a bad one.  I want you to hire a great one and I wanted you to hire them 6 months ago.  Do you think every other PR manager search in the valley took 6 months more than plan?  I don’t.

Fine lines exist here, no doubt.  Sometimes reasons are reasons and sometimes they are actually excuses.  The question isn’t about any one case.  It’s about, deep down, are you judging yourself by intentions or results?

You’d be surprised how many otherwise very solid people get this one thing wrong — and end up career-limited as a result.

10 Questions to Ask Yourself Before Moving into Management

I went looking for a post to help someone decide if they should move into management, but couldn’t find one that I really loved.  These three posts aren’t bad.  Nor is this HBR article.  But since I couldn’t find a post that I thought nails the spirit of the question, I thought I’d write one myself.

So here are the ten questions you should consider before making a move into management.

 1. Do you genuinely care about people?  

Far and away this is the most important question because management is all about people.  If you don’t enjoy working with people, if you don’t enjoy helping people, or if you’d prefer to be left alone to work on tasks or projects, then do not go into management.  If you do not genuinely care about people, then do not go into management.

2. Are you organized?

While a small number of organizational leaders and founders can get away with being unstructured and disorganized, the rest of us in management need to be organized.  If you are naturally disorganized, management will be hard for you — and the people who work for you — because your job is to make the plan and coordinate work on it.

This is why one of my managment interview questions is:  “if I opened up your kitchen cabinets what would I see?”

3.  Are you willing to continuously overcommunicate?

In a world filled with information pollution, constant distractions, and employees who think that they can pay continuous partial attention, you’d be amazed how clearly you need to state things and how often you need to repeat them in order to minimize confusion.  A big part of management is communication, so if you don’t like communicating, aren’t good at it, or don’t relish the idea of deliberately and continuously overcommunicating, then don’t go into management.

4.  Can you say “No” when you need to do?

Everybody loves yes-people managers except, of course, the people who work for them.  While saying yes to the boss and internal customers feels good, you will run your team ragged if you lack the backbone to say no when you need to.  If you can’t say no to a bad idea or offer up reprioritization options when the team is red-lining, then don’t go into management.  Saying no is an important part of the job.

5. Are you conflict averse?

Several decades I read the book Tough-Minded Management:  A Guide for Managers Too Nice for Their Own Good, and it taught me the importance of toughness in management.  Management is a tough job.  You need to layout objectives and hold people accountable for achieving them.  You need to hold peers accountable for delivering on dependencies.  You need to give people feedback that they may not want to hear.  If you’re conflict averse and loathe the idea of doing these things, don’t go into management.  Sadly, conflict averse managers actually generate far more conflict than then non-conflict-averse peers.

6. Do you care more about being liked than being effective?

If you are someone who desperately needs to be liked, then don’t go into management.  Managers need to focus on effectiveness.  The best way to be liked in management is to not care about being liked.  Employees want to be on a winning team that is managed fairly and drives results.  Focus on that and your team will like you.  If you focus on being liked and want to be everyone’s buddy, you will fail as both buddy and manager.

7. Are you willing to let go?  

Everybody knows a micromanager who can’t let go.  Nobody likes working for one.  Good managers aim to specify what needs to be done without detailing precisely how to do it.  Bad managers either over-specify or simply jump in and do it themselves.  This causes two problems:  they anger the employee whose job it was to perform the task and they abdicate their responsibility to manage the team.  If the manager’s doing the employee’s job then whose doing the manager’s?  All too often, no one.

8.  Do you have thick skin?

Managers make mistakes and managers get criticized.  If you can’t handle either, then don’t go into management.  Put differently, how many times in your career have your run into your boss’s office and said, “I just want to thank you for the wonderful job you do managing me.”  For me, that answer is zero.  (I have,  however, years later thanked past managers for putting up with my flaws.)

People generally don’t complement their managers; they criticize them.  You probably have criticized most of yours.  Don’t expect things to be any different once you become the manager.

9.  Do you enjoy teaching and coaching?

A huge positive of management is the joy you get from helping people develop their skills and advance in their careers.  That joy results from your investment in them with teaching and coaching.  Great employees want to be mentored.  If you don’t enjoy teaching and coaching, you’ll be cheating your employees out of learning opportunities and cheating yourself out of a valuable part of the management experience.

10.  Are you willing to lead?

Managers need not just to manage, but to lead.  If stepping up, definining a plan, proposing a solution, or taking an unpopular position scares you, well, part of that is normal, but if you’re not willing to do it anyway, then don’t go into management.  Management requires the courage to lead.  Remember the Peter Drucker quote that differentiates leadership and management.

“Management is doing things right, leadership is doing the right things.”

As a good manager, you’ll need to do both.

Introducing a New SaaS Metric: The Hype Factor

I said in yesterday’s post, entitled Too Much Money Makes You Stupid, that while I don’t have much of a beef with Domo, that I did want to observe in today’s fund-to-excess environment that any idea — including making a series of Alec Baldwin would-be viral videos — can sound like a good one.

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. [1]

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) [2]:

  • 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. [3]

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. [4]

Time will tell.  Gosh, life was simpler (if less interesting) when companies went public at $30M.

# # #


[1] 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 Kardashiansfamous for being famous.

[2] 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?

[3] 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.

[4] 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.)