Category Archives: Venture Capital

Slides from My SaaStr Annual 2019 Presentation (5 Questions CEOs Struggle With)

Thanks to everyone who attended my session today at the amazing — and huge — SaaStr Annual 2019 conference in San Jose.  In this post, I’ll share the slides from my presentation, Five Questions SaaS CEOs Wrestle With (and some thoughts on how to answer them).

The folks at SaaStr recorded the session, so at some point a video of it will be available (but that probably won’t be for a while).  When it is up, I will also post it to Kellblog.

In some sense definitionally, there were two types of people in the audience:

  • CEOs, who hopefully received some fresh perspective on these age-old, never-quite-put-to-bed questions.
  • Those who work for them, who hopefully received some insights into the mind of the CEO that will help make you more valuable team members and help you advance your career.

As mentioned, please send me feedback if you have examples where something in the presentation resonated with you, you applied it in some way, and it made a positive impact on your working life.  I’d love to hear it.

Here are the slides from the presentation.

Rule of 40 Glideslope Planning

Enterprise SaaS companies need a lot of money to grow. The median company spends $1.32 to acquire $1.00 in annual recurring revenue (ARR) [1].  They need to make that investment for 14 years before getting to an IPO.  It all adds up to a median of $300M in capital raised prior to an IPO.

With such vast amounts of money in play, some say “it’s a growth at all costs” game.  But others hold to the Rule of 40 which attempts to balance growth and profitability with a simple rule:  grow as fast as you want as long as your revenue growth rate + your free cashflow margin >= 40%.

The Rule of 40 gets a lot of attention, but I think that companies are not asking the right question about it.  The right question is not “when should my growing startup be Rule of 40 compliant?” [2]

For more than half of all public SaaS companies, the answer to that question, by the way, is “not yet.”  Per multiple studies I’ve read the median Rule of 40 score for public SaaS companies is ~31%, meaning that more than half of public SaaS companies are not Rule of 40 compliant [3].

So, unless you’re an absolutely amazing company like Elastic (which had a Rule of 40 score of 87% at its IPO), you probably shouldn’t be unrealistically planning to become Rule of 40 compliant three years before your IPO [4].  If you do, especially if you’re well funded and don’t need additional expense constraints, you might well compromise growth with a premature focus on the Rule of 40, which could shoot off your corporate foot in terms of your eventual valuation.

If “when should we be Rule of 40 compliant” is the wrong question, then what’s the right one?

What should my company’s Rule of 40 glideslope be?

That is, over the next several years what is your eventual Rule of 40 score target and how do you want to evolve to it?  The big advantage of this question is that the answer isn’t “a year” and it doesn’t assume Rule of 40 compliance.  But it does get you to start thinking about and tracking your Rule of 40 score.

I built a little model to help do some what-if analysis around this question.  You can download it here.

r40-1

In our example, we’ve got a 5 year-old, $30M ARR SaaS company planning the next five years of its evolution, hopefully with an IPO in year 8 or 9.  The driver cells (orange) define how fast you want to grow and what you want your Rule of 40 glideslope to be.  Everything else is calculated.  At the bottom we have an overall efficiency analysis:  in each year how much more are we spending than the previous year, how much more revenue do we expect to get, and what’s the ratio between the two (i.e., which works like kind of an incremental revenue CAC).  As we improve the Rule of 40 score you can see that we need to improve efficiency by spending less for each incremental dollar of revenue.  You can use this as a sanity check on your results as we’ll see in a minute.

Let me demonstrate why I predict that 9 out 10 ten CFOs will love this modeling approach.  Let’s look at every CFO’s nightmare scenario.  Think:  “we can’t really control revenues but we can control expenses so my wake up in the middle of the night sweating outcome is that we build expenses per the plan and miss the revenues.”

r40-2

In the above (CFO nightmare) scenario, we hold expenses constant with the original plan and come in considerably lighter on revenue.  The drives us miles off our desired Rule of 40 glideslope (see red cells).  We end up needing to fund $42.4M more in operating losses than the original plan, all to generate a company that’s $30.5M smaller in revenue and generating much larger losses.  It’s no wonder why CFOs worry about this.  They should.

What would the CFO really like?  A Rule-of-40-driven autopilot.

As in, let’s agree to a Rule of 40 glideslope and then if revenues come up short, we have all pre-agreed to adjust expenses to fall in line with the new, reduced revenues and the desired Rule of 40 score.

r40-3

That’s what the third block shows above.  We hold to the reduced revenues of the middle scenario but reduce expenses to hold to the planned Rule of 40 glideslope.  Here’s the bad news:  in this scenario (and probably most real-life ones resembling it) you can’t actually do it — the required revenue-gathering efficiency more than doubles (see red cells).  You were spending $1.38 to get an incremental $1 of revenue and, to hold to the glideslope, you need to instantly jump to spending only $0.49.  That’s not going to happen.  While it’s probably impossible to hold to the original {-10%, 0%, 5%} glideslope, if you at least try (and, e.g., don’t build expenses fully to plan when other indicators don’t support it), then you will certainly do a lot better than the {-10%, -32%, -42%} glideslope in the second scenario.

In this post, we’ve talked about the Rule of 40 and why startups should think about it as a glideslope rather than a short- or mid-term destination.  We’ve provided you with a downloadable model where you can play with your Rule of 40 glideslope.  And we’ve shown why CFOs will inherently be drawn to the Rule of 40 as a long-term planning constraint, because in many ways it will help your company act like a self-righting ship.

# # #

Notes

[1] The 75th percentile spends $1.92.  And 25% spend more than that.  Per KeyBanc.

[2] Rule of 40 compliant means a company has an rule of 40 score >= 40%.  See next note.

[3] Rule of 40 score is generally defined as revenue growth rate + free cashflow (FCF) margin.  Sometimes operating margin or EBITDA margin is used instead because FCF margin can be somewhat harder to find.

[4] I’m trying to find data a good data set of Rule of 40 scores at IPO time but thus far haven’t found one.  Anecdotally, I can say that lots of successful high-growth SaaS IPOs (e.g., MongoDB, Anaplan, and Blackline) were not Rule of 40 compliant at IPO time — nor were they well after, e.g., as of Oct 2018 per JMP’s quarterly software review.  It seems that if growth is sufficiently there, that the profitability constraint can be somewhat deferred in the mind of the market.

SaaStr 2019 Presentation Preview: Five Questions SaaS CEO Wrestle With

I’m super excited for the upcoming SaaStr Annual 2019 conference in San Jose from February 5th through the 7th at the San Jose Convention Center.  I hope to see you there — particularly for my session from 10:00 AM to 10:30 AM on Tuesday, February 5th.  Last year they ended up repeating my session but that won’t be possible this year as I’m flying to Europe for a board meeting later in the week — so if you want to see it live, please come by at 10:00 AM on Tuesday!

saastr 2019

I’d quibble with the subtitle, “Lessons from Host Analytics,” because it’s actually more, “Lessons From a Lifetime of Doing This Stuff,” and examples will certainly include but also span well beyond Host Analytics.  In fact, I think one thing that’s reasonably unique about my background is that I have 10+ years’ tenure in two different, key roles within an enterprise software company:

  • CEO of two startups, combined for over ten years (MarkLogic, Host Analytics).
  • CMO of two startups, combined for over ten years (BusinessObjects, Versant).

I’ve also been an independent director on the board of 4 enterprise software startups, two of which have already had outstanding exits.  And I just sold a SaaS startup in an interesting process during which I learned a ton.  So we’ve got a lot of experience to draw upon.

SaaS startup CEO is hard job.  It’s a lonely job, something people don’t typically understand until they do it.  It’s an odd job — for what might be the first time in your career you have no boss, per se, just a committee.  You’re responsible for the life and death of the company.  Scores or hundreds of people depend on you to make payroll.  You need to raise capital, likely in the tens of millions of dollars — but these days increasingly in the hundreds — to build your business.

You’re driving your company into an uncertain future and, if you’re good, you’re trying to define that future your way in the mind of the market.  You’re trying to build an executive team that not only will get the job done today, but that can also scale with you for the next few years.  You’re trying to systematize the realization of a vision, breaking it down into the right parts in the right order to ensure market victory.  And, while you’re trying to do all that, you need to keep a board happy that may have interests divergent from your own and those of the company.  Finally, it’s an accelerating treadmill of a job – the better you do, the more is expected of you.

Wait!  Why do we do this again?  Because it’s also a fantastic job.  You get to:

  • Define and realize a vision for a market space.
  • Evangelize new and better ways of doing things.
  • Compete to win key customers, channels, and partners.
  • Work alongside incredibly talented and accomplished people.
  • Serve the most leading and progressive customers in the market.
  • Manage a growing organization, building ideally not just a company but a culture that reflects your core values.
  • Leverage that growth internationally, exploring and learning about the planet and the business cultures across it.

Basically, you get to play strategic N-dimensional wizard chess against some of the finest minds in the business.  Let’s face it.  It’s cool.  Despite the weight that comes with the job, any SaaS startup CEO should feel privileged every day about the job that they “get to” do.

But there are certain nagging questions that hound any SaaS startup CEO.  Questions that never quite get answered and put to bed.  Ones that need to asked and re-asked.  Those are the 5 questions we’ll discuss in my talk.  And here they are:

  1. When do I next raise money?
  2. Do I have the right team?
  3. How can I better manage the board?
  4. To what extent should I worry about competitors?
  5. Are we focused enough?

Each one is a question that can cost you the company, the market, or your job.  They’re all hard.  In my estimation, number 4 is the trickiest and most subtle.  There’s even a bonus question 6 – “are we winning?” — that is perhaps the most important of them all.

I look forward to speaking with you and hope you can attend the session.  If you have any advance questions to stimulate my thinking while preparing for the session, please do send them along via email, DM, or comment.

You don’t need to be a CEO to benefit from this session.  There are lots of lessons for everyone involving in creating and running a startup.  (If nothing else, you might get some insight to how your CEO might think about you and your team.)

I hope to see you there.

Highlights from the Fenwick & West 3Q18 Venture Capital Survey

It’s been a few years since I wrote about this survey, which I post about less to communicate recent highlights and more to generate awareness of its existence.  The Fenwick & West Venture Capital Survey is must-read material for any entrepreneur or startup CEO because it not only makes you aware of trends in financing, but also provides an excellent overview of venture capital terminology as well as answering the important question of “what’s normal” in today’s venture funding environment (also known as “what’s market.”)

So if you’re not yet subscribed to it, you can sign up here.

3Q18 F&W Venture Capital Survey Highlights

  • 215 VC financing rounds were closed by companies with headquarters in Silicon Valley
  • Up rounds beat down rounds 78% to 9%
  • The average price increase (from the prior round) was 71%
  • 24% of rounds had a senior liquidation preference
  • 8% of rounds had multiple liquidation preferences
  • 11% of rounds has participation
  • 6% of rounds had cumulative dividends
  • 98% of rounds had weighted-average anti-dilution provisions
  • 2% of rounds had pay-to-play provisions
  • 6% of rounds had redemption rights

In summary, terms remained pretty friendly and valuations high.  Below is Fenwick’s venture capital barometer which focuses on price changes from the prior financing round.  It’s a little tricky to interpret because the amount of time between rounds varies by company, but it does show in any given quarter what the price difference is, on average, across all the financings closed in that quarter.  In 3Q18, it was 71%, slightly down from the prior quarters, but well above the average of 57%.

vc barometer

 

# # #

Lost and Founder: A Painful Yet Valuable Read

Some books are almost too honest.  Some books give you too much information (TMI).  Some books can be hard to read at times.  Lost and Founder is all three.  But it’s one of the best books I’ve seen when it comes to giving the reader a realistic look at the inside of Silicon Valley startups.NeueHouse_Programming_LostandFound

In an industry obsessed with the 1 in 10,000 decacorns and the stories of high-flying startups and their larger-than-life founders, Lost and Founder takes a real look at what it’s like to found, fund, work at, and build a quite successful but not media- and Sand-Hill-Road-worshiped startup.

Rand Fishkin, the founder of Moz, tells the story of his company from its founding as a mother/son website consultancy in 2001 until his handing over the reins, in the midst of battling depression, to a new CEO in February 2014.  But you don’t read Lost and Founder to learn about Moz.  You read it to learn about Rand and the lessons he learned along the way.

Excerpt:

In 2001, I started working with my mom, Gillian, designing websites for small businesses in the shadow of Microsoft’s suburban Seattle-area campus. […] The dot-com bust and my sorely lacking business acumen meant we struggled for years, but eventually, after trial and error, missteps and heartache, tragedy and triumph, I found myself CEO of a burgeoning software company, complete with investors, employees, customers, and write-ups in TechCrunch.

By 2017, my company, Moz, was a $45 million/ year venture-backed B2B software provider, creating products for professionals who help their clients or teams with search engine optimization (SEO). In layman’s terms, we make software for marketers. They use our tools to help websites rank well in Google’s search engine, and as Google became one of the world’s richest, most influential companies, our software rose to high demand.

Moz is neither an overnight, billion-dollar success story nor a tragic tale of failure. The technology and business press tend to cover companies on one side or the other of this pendulum, but it’s my belief that, for the majority of entrepreneurs and teams, there’s a great deal to be learned from the highs and lows of a more middle-of-the-road startup life cycle.

Fishkin’s style is transparent and humble.  While the book tells a personal tale, it is laden with important lessons.  In particular, I love his views on:

  • Pivots (chapter 4).  While it’s a hip word, the reality is that pivoting — while sometimes required and which sometimes results in an amazing second efforts — means that you have failed at your primary strategy.  While I’m a big believer in emergent strategy, few people discuss pivots as honestly as Fishkin.
  • Fund-raising (chapters 6 and 7).  He does a great job explaining venture capital from the VC perspective which then makes his conclusions both logical and clear.  His advice here is invaluable.  Every founder who’s unfamiliar with VC 101 should read this section.
  • Making money (chapter 8) and the economics of founding or working at a startup.
  • His somewhat contrarian thoughts on the Minimum Viable Product (MVP) concept (chapter 12).  I think in brand new markets MVPs are fine — if you’ve never seen a car then you’re not going to look for windows, leather seats, or cup-holders.  But in more established markets, Fishkin has a point — the Exceptional Viable Product (EVP) is probably a better concept.
  • His very honest thoughts on when to sell a startup (chapter 13) which reveal the inherent interest conflicts between founders, VCs, and employees.
  • His cheat codes for next itme (Afterword).

Finally, in a Silicon Valley where failure is supposedly a red badge of courage, but one only worn after your next big success, Fishkin has an unique take on vulnerability (chapter 15) and his battles with depression, detailed in this long, painful blog post which he wrote the night before this story from the book about a Foundry CEO summit:

Near the start of the session, Brad asked all the CEOs in the room to raise their hand if they had experienced severe anxiety, depression, or other emotional or mental disorders during their tenure as CEO. Every hand in the room went up, save two. At that moment, a sense of relief washed over me, so powerful I almost cried in my chair. I thought I was alone, a frail, former CEO who’d lost his job because he couldn’t handle the stress and pressure and caved in to depression. But those hands in the air made me realize I was far from alone— I was, in fact, part of an overwhelming majority, at least among this group. That mental transition from loneliness and shame to a peer among equals forever changed the way I thought about depression and the stigma around mental disorders.

Overall, in a world of business books that are often pretty much the same, Lost and Founder is both quite different and worth reading.  TMI?  At times, yes.  TLDR?  No way.

Thanks, Rand, for sharing.

Video of my SaaStr 2018 Presentation: Ten Non-Obvious Things About Scaling SaaS

While I’ve blogged about this presentation before, I only recently stumbled into this full-length video of this very popular session — a 30-minute blaze through some subtle SaaS basics.  Enjoy!

I look forward to seeing everyone again at SaaStr Annual 2019.

The Big Mistake You Might Be Making In Calculating Churn: Failing to Annualize Multi-Year ATR Churn Rates

Most of the thinking, definitions, and formulas regarding SaaS unit economics is based on assumptions that no longer reflect the reality of the enterprise SaaS environment.  For example, thinking in terms of MRR (monthly recurring revenue) is outdated because most enterprise SaaS companies run on annual contracts and thus we should think in terms of ARR (annual recurring revenue) instead.

Most enterprise SaaS companies today do a minimum one-year contract and many do either prepaid or non-prepaid multi-year contracts beyond that. In the case of prepaid multi-year contracts, metrics like the CAC payback period break (or at the very least, get difficult to interpret).  In the case of multi-year contacts, calculating churn correctly gets a lot more complicated – and most people aren’t even aware of the issue, let alone analyze it correctly.

If your company does multi-year contracts and you are not either sidestepping this issue (by using only ARR-pool-based rates) or correcting for it in your available-to-renew (ATR) churn calculations, keep reading.  You are possibly making a mistake and overstating your churn rate.

A Multi-Year Churn Example
Let’s demonstrate my point with an example where Company A does 100% one-year deals and Company B does 100% three-year deals.  For simplicity’s sake, we are going to ignore price increases and upsell [1].  We’re also not going to argue the merits of one- vs. three-year contracts; our focus is simply how to calculate churn in a world of them.

In the example below, you can see that Company A has an available-to-renew-based (ATR-based) [2] churn rate of 10%.  Company B has a 27% ATR-based churn rate.  So we can quickly conclude that Company A’s a winner, and Company B is a loser, right?

Capture

Not so fast.

At the start of year 4, a cohort of Company A customers is worth 72.9 units, the exact same as a cohort of Company B customers.  In fact, if you look at lifetime value (LTV), the Company B cohort is worth nearly 10% more than the Company A cohort [3].

my churn1

Wait a minute!  How can a company with 27% churn rate be “better” than a company with 10% churn rate?

It’s All About Exposure:  How Often are Deals Exposed to the Churn Rate?
One big benefit of multi-year deals is that they are exposed to the churn rate less frequently than one-year deals.  When you exclude the noise (e.g., upsell, discounts, and price increases), and look at churn solely as a decay function, you see that the N-year retention rate [4] is (1-churn rate)^N.  With 10% churn, your 2-year retention rate is (1-0.1)^2 = 0.9^2 = 0.81.  Your 3-year retention rate is (1-0.1)^3 = 0.9^3 = 0.729, or a retention rate of 73%, equivalent to a churn rate of 27%.

Simply put, churn compounds so exposing a contract to the churn rate less often is a good thing:  multi-year deals do this by excluding contracts from the ATR pool, typically for one or two years, before they come up for renewal [5].  This also means that you cannot validly compare churn rates on contracts with different duration.

This is huge.  As we have just shown, a 10% churn rate on one-year deals is equivalent to a 27% churn rate on three-year deals, but few people I know recognize this fact.

I can imagine two VCs talking:

“Yo, Trey.”

“Yes.”

“You’re not going to believe it, I saw a company today with a 27% churn rate.”

“No way.”

“Yep, and it crushed their LTV/CAC — it was only 1.6.”

“Melting ice cube.  Run away.”

“I did.”

Quite sad, in fact, because with a correct (annualized) churn rate of 10% and holding the other assumptions constant [6], the LTV/CAC jumps to healthy 4.4.  But any attempt to explain a 27% churn rate is as likely to be seen as a lame excuse for a bad number as it is to be seen as valid analysis.

Best Alternative Option:  Calculate Churn Rates off the Entire ARR Pool
I’m going to define the 27% figure as the nominal ATR-based churn rate.  It’s what you get when you take churn ARR / ATR in any given period.  I call it a nominal rate because it’s not annualized and it doesn’t reflect the varying distribution of 1Y, 2Y, and 3Y deals that are mixed in the ATR pool in any given quarter.  I call it nominal because you can’t validly compare it to anything [7].

Because correcting this to a more meaningful rate is going to involve a lot of brute force math, I’ll first advise you to do two things:

  • Banish any notion from your mind that ATR rates are somehow “more real” than churn rates calculated against the entire ARR pool [8].
  • Then use churn rates calculated against the entire ARR pool and sidestep the mess we’re about to enter in the next section [9] where we correct ATR-based churn rates.

In a world of mixed-duration contracts calculating churn rates off the entire ARR pool effectively auto-corrects for the inability of some contracts to churn.  I have always believed that if you were going to use the churn rate in a math function (e.g., as the discount rate in an NPV calculation) that you should only use churn rates calculated against the entire ARR pool because, in a mixed multi-year contract world, only some of the contracts come up for renewal in any given period.  In one sense you can think of some contracts as “excluded from the available-to-churn (ATC) pool.”  In another, you can think of them as auto-renewing.  Either way, it doesn’t make sense in a mixed pool to apply the churn rate of those contracts up for renewal against the entire pool which includes contracts that are not.

If you want to persist in using ATR-based churn rates, then we must correct for two problems:  we need to annualize the multi-year rates, and we then need to calculate ATR churn using an ATR-weighted average of the annualized churn rates by contract duration.

Turning Nominal ATR Churn into Effective, Annualized ATR Churn
Here’s how to turn nominal ATR churn into an effective, annualized ATR churn rate [10] [11]:

Step 1:  categorize your ATR and churn ARR by contract duration.  Calculate a 1Y churn rate and nominal 2Y and 3Y ATR churn rates.

Step 2:  annualize the nominal multi-year (N-year) churn rates by flipping to retention rates and taking the Nth root of the retention rate.  For example, our 27% 3-year churn rate is equivalent to a 73% 3-year retention rate, so take the cube root of 0.73 to get 0.9.  Then flip back to churn rates and get 10%.

Step 3:  do an ATR-weighted average of the 1Y and annualized 2Y and 3Y churn rates.  Say your ATR was 50% 1Y, 25% 2Y, and 25% 3Y contracts and your annualized churn rates were 10%, 12%, and 9%.  Then the weighted average would be (0.5*0.10) + (0.25*0.12) + (0.25*0.09) = 10.25%, as your annualized, effective ATR churn rate.

That’s it.  You’ve now produced an ATR churn rate that is comparable to a one in a company that does only 1-year contracts.

Conclusion
If nothing else, I hope I have convinced that you it is invalid to compare churn rates on contracts of different duration and ergo that is simpler to generally calculate churn rates off the entire ARR pool.  If, however, you still want to see ATR-based churn rates, then I hope I’ve convinced you that you must do the math and calculate ATR churn as a weighted average of annualized one-, two-, and three-year ATR churn rates.

# # #

Notes
[1] In a world of zero upsell there is no difference between gross and net churn rates, thus I will simply say “churn rate” in this post.

[2] As soon as you start doing multi-year contracts then the entire ARR base is no longer up for renewal each year.  You therefore need a new concept, available to renew (ATR), which reflects only that ARR up for renewal in a given period.

[3] Thanks to its relatively flatter step-wise decay compared to Company A’s more linear decay.

[4] Retention rate = 1 – churn rate.

[5] If it helps, you can think of the ATR pool in a glass half-empty way as the available-to-churn pool.

[6] Assuming CAC ratio of 1.8 and subscription gross margins of 80%.

[7] Unless your company has a fixed distribution of deals by contract duration – e.g., a degenerate case being 100% 3Y deals.  For most companies the average contract duration in the inbound ATR pool is going to vary each quarter.  Ergo, you can’t even validly compare this rate to itself over time without factoring in the blending.

[8] Most people I meet seem to think ATR rates are more real than rates based on the entire ARR pool.  Sample conversation  — “what’s your churn rate?”  “6%.”  “Gross or net?  “Gross.”  “No, I mean your real churn rate – what gets churned divided only by what was up for renewal.”    The mistake here is in thinking that using ATR makes it comparable to a pure one-year churn rate – and it doesn’t.

[9] Gross churn = churn / starting period ARR.  Net churn = (gross churn – upsell) / starting period ARR.

[10] I thought about trying a less brute-force way using average contract duration (ACD) of the ATR pool, but decided against it because this method, while less elegant, is more systematic.

[11] Note that this method will still understate the LTV advantage of the more step-wise multi-year contract decay because it’s not integrating the area under the curve, but instead intersecting what’s left of the cohort after N years.  In our first example, the 1Y and 3Y cohorts both had 73 units of ARR, but because the multi-year cohort decayed more slowly it’s LTV to that point was about 10% higher.