Category Archives: SaaS

Book Review:  From Impossible to Inevitable

This post reviews Aaron Ross and Jason Lemkin’s new book, From Impossible to Inevitable, which is being launched at the SaaStr Conference this week.  The book is a sequel of sorts to Ross’s first book, Predictable Revenue, published in 2011, and which was loaded with great ideas about how to build out your sales machine.

From Impossible to Inevitable is built around what they call The Seven Ingredients of Hypergrowth:

  1. Nail a niche, which is about defining your focus and ensuring you are ready to grow. (Or, as some say “nail it, then scale it.)  Far too many companies try to scale it without first nailing it, and that typically results in frustration and wasted capital.
  2. Create predictable pipeline, which about “seeds” (using existing successful customers), “nets” (classical inbound marketing programs), and “spears” (targeted outbound prospecting) campaigns to create the opportunities sales needs to drive growth.
  3. Make sales scalable, which argues convincingly that specialization is the key to scalable sales. Separate these four functions into discrete jobs:  inbound lead handing, outbound prospecting, selling (i.e., closing new business), and post-sales roles (e.g., customer success manager).  In this section they include a nice headcount analysis of a typical 100-person SaaS company.
  4. Double your deal size, which discusses your customer mix and how to build a balanced business built off a run-rate business of average deals topped up with a lumpier enterprise business of larger deals, along with specific tactics for increasing deal sizes.
  5. Do the time, which provides a nice reality check on just how long it takes to create a $100M ARR SaaS company (e.g., in a great case, 8 years, and often longer), along with the wise expectations management that somewhere along the way you’ll encounter a “Year of Hell.”
  6. Embrace employee ownership, which reminds founders and executives that employees are “renting, not owning, their jobs” and how to treat them accordingly so they can act more like owners than renters.
  7. Define your destiny, which concludes the book with thoughts for employees on how to take responsibility for managing their careers and maximizing the opportunities in front of them.

The book is chock full of practice advice and real-world stories.  What it’s not is theoretical.  If Crossing the Chasm offered a new way of thinking about product lifecycle strategy that earned it a place on the top shelf of the strategy bookcase, From Impossible to Inevitable is a cookbook that you keep in the middle of the kitchen prep table, with Post-It’s sticking out the pages and oil stains on the cover.  This is not a book that offers one big idea with a handful of chapters on how to apply it.  It’s a book full of recipes and tactics for how to improve each piece of your go-to-market machine.

This book — like Predictable Revenue, The Lean Startup, Zero to One, and SalesHood — belongs on your startup executive’s bookshelf.  Read it!  And keep up with Jason’s and Aaron’s great tweetstreams and the awesome SaaStr blog.

The SaaSacre Part II: Time for the Rebound?

In response to my post, SaaS Stocks:  How Much Punishment is in Store, a few of my banker friends have sent me over some charts and data which shine more light on the points I was trying to make about SaaS forward twelve month (FTM) enterprise value (EV) revenue multiples, normal trading ranges, and the apparent “floor” value for this metric.

This chart comes from the folks at Pacific Crest:

paccrest saas multiples

In English, it says that SaaS stocks are trading at an EV/FTM revenue multiple of 3.2, 35% below the average since 2005, and down 66% since the peak in Jan 2014.  It also shows the apparent floor at around 2.0x, which they dipped below only once in the past decade during the crisis of 2008.

This is not to say that Wall Street doesn’t over-correct, that a new floor value could not be established, or that cuts in revenue forecasts due to macroeconomics couldn’t cause significant valuation drops at a constant, in-range EV/FTM ratio.

It is to say that, given historical norms, if you believe in reversion to the mean and that FTM revenue forecasts will not be materially reduced, that we are in “buying opportunity” territory.   The question is then which sentiment will win out in the market.

  • Fear of a potential 30% drop before hitting the floor value, breaking through the floor value, or cuts in FTM revenue forecasts.
  • Greed and the opportunity to get a nearly 50% return in a simple reversion to the mean.

My quick guess is more fear short-term, followed by some healthy greed winning out after that.

Might we see a temporary dead cat bounce before a further sell-off?  Maybe.  Should we remember the Wall Street maxim about catching falling knives?  Yes.

But at the same time remember that mixed in among the inflated, private, unicorn wreckage, that we have some high-quality, public, recurring-revenue companies trading at what’s starting to approach decades-low multiples.  At some point, that will become a real opportunity.

Disclaimers
See my FAQ for disclaimers and more background information.  I am not a financial analyst and I do not make stock recommendations.  I am simply a CEO sharing his experience and opinion which, as my wife will happily attest, is often incorrect.

SaaS Stocks: How Much Punishment is in Store?

The stock market feels like Nordstrom Rack these days:

  • Salesforce at $56/share
  • Tableau at $38/share
  • ServiceNow at $47/share
  • Zendesk at $15/share
  • Workday at $49/share
  • NetSuite at $54/share

Redpoint’s Tomasz Tunguz points out that SaaS forward revenue multiples have been more than cut in half, dropping from 7.7 in January 2014 to 3.3 today.

So where’s it all going to end?  Much as the P/E  of the S&P 500 tends to converge to around 15 over time, I have always felt that quality on-premises enterprise software companies converged to a valuation of 2.0 to 3.0x revenues and there was a floor around 1.0x revenues.  That’s not to say that Wall St doesn’t over-correct and you’d never see on-premises valuations less than 1.0x revenues — but that should be rare and anything less 2.0x could indicate a good buying opportunity and anything near 1.0x — for a healthy company — could mean a real bottom-fishing opportunity.

The question is what are the equivalent numbers for SaaS companies?  I think the norm range is 3.0 to 5.0x revenues and I think the floor is around 2.0x.  That would suggest that in a bad case — despite all the recent carnage — there’s still 30% downside potential in SaaS stocks.  And that’s not including the case where you think we’re in a macroeconomic situation such that the forward four-quarter revenue estimates drop, which would mean more downside potential on top of that.

But I do think at 3.3x, we are now near the bottom-end of the norm range so the question is which sentiment is going to win out in the market:

  • Fear of the 30%+ remaining downside potential in SaaS stocks
  • Greed to capture the potential 50%+ return of a SaaS bounce back to the mid/high-end of the range.

I’d speculate on more fear in the short-term followed by some nice greed in the mid-term.

See my disclaimers:  I am not a financial analyst and I do not make recommendations on specific stocks.  The purpose of this post was to share my non-scientific rule of thumb for SaaS trading ranges and do some analysis based on that.

Theoretical TCV: A Necessary New SaaS Metric?

The more I hear about SaaS companies talking up big total contract value (TCV) figures, the more I worry about The Tightening, and the more I think we should create a new SaaS metric:  TTCV = theoretical total contract value.

TTCV = PCV + NPCV

Prepaid contract value (PCV) is the prepaid portion and NPCV is the non-prepaid portion of the subscription in multi-year SaaS agreements.  We could then calculate your corporate hype ratio (CHR) with TTCV/ARR, the amount by which you overstate ARR by talking about TTCV.

I make the suggestion tongue-in-cheek, but do so to make real point.

I am not against multi-year SaaS contracts.  I am not against prepaid SaaS contracts.  In high-consideration enterprise SaaS categories (e.g., EPM), buyers have spent months in thorough evaluations validating that the software can do the job.  Thus, it can make good sense for both buyer and seller to enter into a multi-year agreement.  The seller can shield contracts from annual churn risk and the buyer can get a modest discount for the contractual commitment to renew (e.g., shielding from annual prices increases) or a bigger discount for that plus a prepayment.

But it’s all about degree.  A three-year  prepaid contract often makes sense.  But, for example, an eight-year agreement with two-years prepaid (8/2) often doesn’t.  Particularly if the seller is a startup and not well established.  Why?

Let’s pretend the 8/2 deal was written by an established leader like Salesforce.  In that case:

  • There is a very high likelihood the software will work.
  • If there are problems, Salesforce has major resources to put behind making it work.
  • If the customer is nevertheless unhappy, Salesforce will presumably not be a legal lightweight and enforce the payment provisions of the contract.

Now, let’s pretend that 8/2 deal was written by a wannacorn, a SaaS vendor who raised a lot of money, made big promises in so doing, and is way out over its skis in terms of commitments.

  • There is a lower likelihood the software will work, particularly if working means building a custom application, as opposed to simply customizing an off-the-shelf app.
  • If there are problems, the wannacorn has far fewer available resources to help drive success — particularly if they are spread thin already.
  • If the customer is unhappy they are much less likely to pay because they will be far more willing to say “sue me” to a high-burn startup than to an established leader.

So while that 8/2 deal might be a reasonable piece of business for an established leader, it looks quite different from the perspective of the startup:  three-fourths of its value may well end up noncollectable — and ergo theoretical.  That’s why startups should neither make those deals (because they are offering something for an effectively fictitious commitment) nor talk them up (because large portions of the value may never be realized).

Yet many do.  And somehow — at least before The Tightening — some investors seem to buy the hype.  Remember the corporate hype ratio:  TTCV / ARR.

 

What Marketing Costs Should be Included in CAC Calculations?

Dear Kellblog:

I’m working on my CAC calculations and I’m trying to determine if I should include all marketing costs or just my direct demand generation costs?  I’ve talked to many of my CMO peers and can’t get a consistent answer to the question?

Thanks / Bewildered CMO

Dear Bewildered CMO:

My gut reaction is that you should include all marketing costs.  Don’t try to argue that PR and product marketing don’t work on customer acquisition.  Don’t try to argue that people aren’t programs and try to exclude the cost of your demandgen team.

Why?  Three reasons:

  • Demandgen people and programs dollars should be fungible.  PR and product marketing better be doing things that help acquire customers., even if indirectly.
  • Playing counting games can hurt your credibility.  VCs aren’t just trying to compare metrics, they’re trying to get to know you by seeing how you think about and/or calculate them.  I’d think you were a weasel if I found you excluding these costs without really good reason.
  • To the extent that people try to compare these things between private and public companies, remember that there is no way to split marketing apart (or split customer success from sales) with public companies which should suggest that by default you include things.

Best / Kellblog

For fun, let’s go quickly look at some sources for CAC definitions and see what we find regarding this issue:

Kellblog defines the CAC as:

dk-cac-pic3

S&M, by default, needs to include all S&M costs, so you can’t cut anything out.

(Side note:  to the extent you amortize commissions, I would prefer to say cash sales expense as opposed to GAAP sales expense, because the latter will hide some costs — but that has nothing to do with marketing.)

The 2015 Pacific Crest Private SaaS Company Survey defines the CAC as:

How much do you spend on a fully-loaded sales & marketing cost basis to acquire $1 of new ACV from a new customer.

This seems to close one door (i.e., you better include IT and facilities allocations to your sales costs — as GAAP would require anyway), but open another because it defines the CAC not in terms of total new ACV, but new ACV from new customers.  So if, for example, you had installed base upsell marketing programs, then I would not count those costs in the CAC calculation because they are not marketing costs spent to win new ARR from new customers.  Is PR?  Is product marketing?  It’s a slippery slope.  I’m not in love with this definition for that reason.  You could never do it for public companies.

David Skok defines the CAC as:

Note that while Skok is calculating a cost to acquire a new customer as opposed to $1 of new ARR, his definition is clear when it comes to splitting marketing costs:  include all S&M costs.

Bessemer prefers talking about a CAC payback period and defines it as:

bess cac

Again, this definition is clear — include all S&M costs.

The Perils of Measuring a SaaS Business on Total Contract Value (TCV)

It’s a frothy time and during such times people can develop a tendency to get sloppy about their numbers.  The first sign of froth is when people routinely discuss company size using market capitalization instead of revenue.  This happened constantly during Bubble 1.0 and started again several years ago – e.g., all the talk of unicorns, private companies with $1B+ valuations.

Oneupsmanship becomes the name of the game in frothy times.  If your competitor’s site had 1M pageviews to your own site’s 750K, marketing quickly came up with a new metric on which you could win:  “we had 1.5M eyeballs.”  This kind of gaming, pardon the pun, is seen through rather easily.

The more disturbing distortions are those intended to impress industry influencers to validate strategy.  Analysts – whose job is supposedly to analyze – have a troubling tendency to not judge strategies on their logical merits but on their results.  So if vendor has a silly, unfocused, or simply bad strategy, the vendor doesn’t need to argue that it actually makes sense, they just need find a way to show that it is producing results – and the ensuing Halo Effects will serve as validation.

Public companies try to demonstrate results through revenue allocation games, robbing from non-strategic SKUs to pump up strategic ones (e.g., “cloudwashing” as the megavendors are now often accused).   Private companies have free reign and can either point to unverifiable lofty financing valuations as supposed proof that their strategy is working, or to unverifiable sales growth figures where sales is typically defined as the metric that looked best last quarter.

Most people would quickly agree that at a SaaS business, the best metric for measuring sales is growth in new annual recurring revenue (ARR).  They’d also agree that the best metric for valuing the business is ending ARR and its growth.  (LTV/CAC would come in right behind.)  Using my leaky bucket analogy, the best way to measure sales is by how fast they pour water in the bucket.  The best way to measure the value of the business is the water level of the bucket and how fast it is going up.

But it’s a frothy time, and sometimes the numbers produced using the correct SaaS measures don’t produces numbers that, well, sufficiently impress.  So what’s a poor CEO to do?  Embellish.  The Wall Street Journal recently ran a piece that compared company claims about size/growth made while the company was still private to those later revealed in the S-1.  The results were disappointing, if not perhaps surprising.

Put differently, what’s the SaaS equivalent of “eyeballs”?

The answer is simple:  bookings or, more precisely, total contract value (TCV) bookings.  To show this, we’ll need to define some terms.

  • ARR = annual recurring revenue, the annual subscription fee
  • NSB = new subscription bookings, the prepaid (and – no gaming — quickly collectible) portion of the contract. Since enterprise SaaS contracts are often multi-year and can be fully, partially, or only first-year prepaid, we need a metric to understand the cash implications of the deal.
  • TCV = total contract value, including both prepaid and non-prepaid subscription as well as services. TCV is the largest metric because it includes everything.  Some people exclude services but, to me, total means total.

Now, let’s look at several ways to transform a simple $100K ARR deal in the following spreadsheet:

peril1

Note that in each case, the ARR is $100K.  But by varying deal terms the TCV can vary from $150K to $750K.  Now in the real world if someone was going to pay you $100K for one-year deal, they are unlikely to pay $300K for a three-year prepay or contractual commitment.  They will want something in return; typically a discount.

Let’s combine these ideas in one more example.  Say you run a SaaS company and want to impress everyone that you’re doing really well.  The trouble is you’re not.  You sold $10M in new ARR in 2014 (all one-year, prepaid) and think you can sell $10M again in 2015 on those same terms.   If you measure yourself on new ARR growth, that’s 0% and no one is going to think you are cool or write you up on the tech blogs.  But if you switch to TCV and increase your contract duration, you get a lot more flexibility:

peril2

If you switch to TCV, the good news is you can grow literally as fast as you want just by playing with contract terms.  Want to grow at 60%?  Switch to 2-year prepaids and give a 20% discount.  That’s not fast enough and you want to grow at 101%?  Move to 3-year prepaids by effectively doing a year-long “buy 2 get 1 free” promotion.   That’s not good enough?  Move to 5-year non-prepaids and you can grow at a dazzling 235% and get nice TechCrunch articles about your strategic vision, your hypergrowth, and your unique culture (that is, most probably, just like everyone else’s unique culture).

This is great.  Why doesn’t everybody do it?  Because you’re mortgaging the future:

  • The discounts you’re giving to get multi-year deals are crushing ARR; new ARR growth is shrinking in all cases.
  • You are therefore crushing both revenue and cash collections over the time period(s)
  • The prepaid deals create a drug addiction problem because you’re not collecting cash in the out years. So you build a dependency either on lots of capital or lots more prepaid deals.
  • Worse yet, on the non-prepaid deals you may not ever collect the money at all.

Wait, what did he say?

In my opinion, non-prepaid multi-year deals are often not worth the paper they are written on.  Why?  Just look at it from the customer’s perspective.  Say you sign a $100K five-year deal with only the first year paid up-front.  And say the software’s not delivering.  It took more work to implement than you thought.  You’ve fallen short on the requirements.  It’s not performing very well.  You’ve called for help but the company can’t fix it because they’re too busy doing other 5-year non-prepaid deals with other customers.

What do you do?  Simple:  you don’t pay the invoice when it comes.  Technically,  yes, you are very much breaking the contract that you signed — but if the software really isn’t delivering, when the vendor calls you say:  “sue me.”

Since software companies generally don’t like suing customers, the vendor – especially if they know the implementation failed – will generally walk away and write it your receivable as bad debt.   If they are particularly devious (and incorrect) they might not even take it as churn until the end of the five-year period when the contract is supposed to renew.   I wouldn’t be shocked if you could find a company that did it this way.

Most sophisticated SaaS people know that SaaS companies shouldn’t be run on TCV or bookings and are well aware of the problems doing so creates with ARR, revenue, and cash.

However, I have never heard anyone make the simple additional point I’m making here:  in a frothy environment dubious companies can create a fictitious bubble around themselves using TCV.  However, because non-prepaid multi-year deals only work when the customers are happy, if the company is out over its skis on promises and implementations, then many of the customers will not end up happy, and the company will never collect much of that TCV.  Meaning, that it was never really “value” in the first place.

Beware Greeks bearing gifts and SaaS vendors talking TCV.

Survivor Bias in Churn Calculations: Say It’s Not So!

I was chatting with a fellow SaaS executive the other day and the conversation turned to churn and renewal rates.  I asked how he calculated them and he said:

Well, we take every customer who was also a customer 12 months ago and then add up their ARR 12 months ago and add up their ARR today, and then divide today’s ARR by year-ago ARR to get an overall retention or expansion rate.

Well, that sounds dandy until you think for a minute about survivor bias, the often inadvertent logical error in analyzing data from only the survivors of a given experiment or situation.  Survivor bias is subtle, but here are some common examples:

  • I first encountered survivor bias in mutual funds when I realized that look-back studies of prior 5- or 10-year performance include only the funds still in existence today.  If you eliminate my bogeys I’m actually an below-par golfer.
  • My favorite example is during World War II, analysts examined the pattern of anti-aircraft fire on returning bombers and argued to strengthen them  in the places that were most often hit.  This was exactly wrong — the places where returning bombers were hit were already strong enough.  You needed to reinforce them in the places that the downed bombers were hit.

So let’s turn back to churn rates.  If you’re going to calculate an overall expansion or retention rate, which way should you approach it?

  1. Start with a list of customers today, look at their total ARR, and then go compare that to their ARR one year ago, or
  2. Start with a list of customers from one year ago and look at their ARR today.

Number 2 is the obvious answer.  You should include the ARR from customers who choose to stop being customers in calculating an overall churn or expansion rate.  Calculating it the first way can be misleading because you are looking at the ARR expansion only from customers who chose to continue being customers.

Let’s make this real via an example.

survivor bias

The ARR today is contained in the boxed area.  The survivor bias question comes down to whether you include or exclude the orange rows from year-ago ARR.  The difference can be profound.  In this simple example, the survivor-biased expansion rate is a nice 111%.  However, the non-biased rate is only 71% which will get you a quick “don’t let the door hit your ass on the way out” at most VCs.  And while the example is contrived, the difference is simply one of calculation off identical data.

Do companies use survivor-biased calculations in real life?  Let’s look at my post on the Hortonworks S-1 where I quote how they calculate their net expansion rate:

We calculate dollar-based net expansion rate as of a given date as the aggregate annualized subscription contract value as of that date from those customers that were also customers as of the date 12 months prior, divided by the aggregate annualized subscription contract value from all customers as of the date 12 months prior.

When I did my original post on this, I didn’t even catch it.  But therein lies the subtle head of survivor bias.

# # #

Disclaimers:

  • I have not tracked the Hortonworks in the meantime so I don’t know if they still report this metric, at what frequency, how they currently calculate it, etc.
  • To the extent that “everyone calculates it this way” is true, then companies might report it this way for comparability, but people should be aware of the bias.  One approach is to create a present back-looking and a past forward-looking metric and show both.
  • See my FAQ for additional disclaimers, including that I am not a financial analyst and do not make recommendations on stocks.